* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 54289 tid 54390 thread 3 bound to OS proc set {3}
OMP: pid 54289 tid 54392 thread 5 bound to OS proc set {5}
OMP: pid 54289 tid 54396 thread 9 bound to OS proc set {9}
OMP: pid 54289 tid 54391 thread 4 bound to OS proc set {4}
OMP: pid 54289 tid 54289 thread 0 bound to OS proc set {0}
OMP: pid 54289 tid 54393 thread 6 bound to OS proc set {6}
OMP: pid 54289 tid 54399 thread 12 bound to OS proc set {12}
OMP: pid 54289 tid 54400 thread 13 bound to OS proc set {13}
OMP: pid 54289 tid 54395 thread 8 bound to OS proc set {8}
OMP: pid 54289 tid 54404 thread 17 bound to OS proc set {17}
OMP: pid 54289 tid 54394 thread 7 bound to OS proc set {7}
OMP: pid 54289 tid 54397 thread 10 bound to OS proc set {10}
OMP: pid 54289 tid 54401 thread 14 bound to OS proc set {14}
OMP: pid 54289 tid 54398 thread 11 bound to OS proc set {11}
OMP: pid 54289 tid 54402 thread 15 bound to OS proc set {15}
OMP: pid 54289 tid 54388 thread 1 bound to OS proc set {1}
OMP: pid 54289 tid 54420 thread 33 bound to OS proc set {33}
OMP: pid 54289 tid 54405 thread 18 bound to OS proc set {18}
OMP: pid 54289 tid 54389 thread 2 bound to OS proc set {2}
OMP: pid 54289 tid 54406 thread 19 bound to OS proc set {19}
OMP: pid 54289 tid 54421 thread 34 bound to OS proc set {34}
OMP: pid 54289 tid 54436 thread 49 bound to OS proc set {49}
OMP: pid 54289 tid 54422 thread 35 bound to OS proc set {35}
OMP: pid 54289 tid 54403 thread 16 bound to OS proc set {16}
OMP: pid 54289 tid 54437 thread 50 bound to OS proc set {50}
OMP: pid 54289 tid 54438 thread 51 bound to OS proc set {51}
OMP: pid 54289 tid 54419 thread 32 bound to OS proc set {32}
OMP: pid 54289 tid 54408 thread 21 bound to OS proc set {21}
OMP: pid 54289 tid 54412 thread 25 bound to OS proc set {25}
OMP: pid 54289 tid 54407 thread 20 bound to OS proc set {20}
OMP: pid 54289 tid 54435 thread 48 bound to OS proc set {48}
OMP: pid 54289 tid 54409 thread 22 bound to OS proc set {22}
OMP: pid 54289 tid 54416 thread 29 bound to OS proc set {29}
OMP: pid 54289 tid 54411 thread 24 bound to OS proc set {24}
OMP: pid 54289 tid 54413 thread 26 bound to OS proc set {26}
OMP: pid 54289 tid 54424 thread 37 bound to OS proc set {37}
OMP: pid 54289 tid 54415 thread 28 bound to OS proc set {28}
OMP: pid 54289 tid 54417 thread 30 bound to OS proc set {30}
OMP: pid 54289 tid 54414 thread 27 bound to OS proc set {27}
OMP: pid 54289 tid 54410 thread 23 bound to OS proc set {23}
OMP: pid 54289 tid 54423 thread 36 bound to OS proc set {36}
OMP: pid 54289 tid 54425 thread 38 bound to OS proc set {38}
OMP: pid 54289 tid 54440 thread 53 bound to OS proc set {53}
OMP: pid 54289 tid 54418 thread 31 bound to OS proc set {31}
OMP: pid 54289 tid 54428 thread 41 bound to OS proc set {41}
OMP: pid 54289 tid 54439 thread 52 bound to OS proc set {52}
OMP: pid 54289 tid 54429 thread 42 bound to OS proc set {42}
OMP: pid 54289 tid 54426 thread 39 bound to OS proc set {39}
OMP: pid 54289 tid 54427 thread 40 bound to OS proc set {40}
OMP: pid 54289 tid 54432 thread 45 bound to OS proc set {45}
OMP: pid 54289 tid 54452 thread 65 bound to OS proc set {65}
OMP: pid 54289 tid 54444 thread 57 bound to OS proc set {57}
OMP: pid 54289 tid 54430 thread 43 bound to OS proc set {43}
OMP: pid 54289 tid 54431 thread 44 bound to OS proc set {44}
OMP: pid 54289 tid 54433 thread 46 bound to OS proc set {46}
OMP: pid 54289 tid 54443 thread 56 bound to OS proc set {56}
OMP: pid 54289 tid 54442 thread 55 bound to OS proc set {55}
OMP: pid 54289 tid 54434 thread 47 bound to OS proc set {47}
OMP: pid 54289 tid 54453 thread 66 bound to OS proc set {66}
OMP: pid 54289 tid 54445 thread 58 bound to OS proc set {58}
OMP: pid 54289 tid 54454 thread 67 bound to OS proc set {67}
OMP: pid 54289 tid 54456 thread 69 bound to OS proc set {69}
OMP: pid 54289 tid 54455 thread 68 bound to OS proc set {68}
OMP: pid 54289 tid 54460 thread 73 bound to OS proc set {73}
OMP: pid 54289 tid 54459 thread 72 bound to OS proc set {72}
OMP: pid 54289 tid 54458 thread 71 bound to OS proc set {71}
OMP: pid 54289 tid 54448 thread 61 bound to OS proc set {61}
OMP: pid 54289 tid 54451 thread 64 bound to OS proc set {64}
OMP: pid 54289 tid 54464 thread 77 bound to OS proc set {77}
OMP: pid 54289 tid 54461 thread 74 bound to OS proc set {74}
OMP: pid 54289 tid 54447 thread 60 bound to OS proc set {60}
OMP: pid 54289 tid 54468 thread 81 bound to OS proc set {81}
OMP: pid 54289 tid 54463 thread 76 bound to OS proc set {76}
OMP: pid 54289 tid 54457 thread 70 bound to OS proc set {70}
OMP: pid 54289 tid 54465 thread 78 bound to OS proc set {78}
OMP: pid 54289 tid 54462 thread 75 bound to OS proc set {75}
OMP: pid 54289 tid 54450 thread 63 bound to OS proc set {63}
OMP: pid 54289 tid 54469 thread 82 bound to OS proc set {82}
OMP: pid 54289 tid 54466 thread 79 bound to OS proc set {79}
OMP: pid 54289 tid 54441 thread 54 bound to OS proc set {54}
OMP: pid 54289 tid 54449 thread 62 bound to OS proc set {62}
OMP: pid 54289 tid 54446 thread 59 bound to OS proc set {59}
OMP: pid 54289 tid 54467 thread 80 bound to OS proc set {80}
OMP: pid 54289 tid 54476 thread 89 bound to OS proc set {89}
OMP: pid 54289 tid 54471 thread 84 bound to OS proc set {84}
OMP: pid 54289 tid 54480 thread 93 bound to OS proc set {93}
OMP: pid 54289 tid 54472 thread 85 bound to OS proc set {85}
OMP: pid 54289 tid 54481 thread 94 bound to OS proc set {94}
OMP: pid 54289 tid 54478 thread 91 bound to OS proc set {91}
OMP: pid 54289 tid 54475 thread 88 bound to OS proc set {88}
OMP: pid 54289 tid 54473 thread 86 bound to OS proc set {86}
OMP: pid 54289 tid 54482 thread 95 bound to OS proc set {95}
OMP: pid 54289 tid 54470 thread 83 bound to OS proc set {83}
OMP: pid 54289 tid 54479 thread 92 bound to OS proc set {92}
OMP: pid 54289 tid 54474 thread 87 bound to OS proc set {87}
OMP: pid 54289 tid 54477 thread 90 bound to OS proc set {90}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_0 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 54504 tid 54603 thread 1 bound to OS proc set {1}
OMP: pid 54504 tid 54604 thread 2 bound to OS proc set {2}
OMP: pid 54504 tid 54504 thread 0 bound to OS proc set {0}
OMP: pid 54504 tid 54605 thread 3 bound to OS proc set {3}
OMP: pid 54504 tid 54606 thread 4 bound to OS proc set {4}
OMP: pid 54504 tid 54607 thread 5 bound to OS proc set {5}
OMP: pid 54504 tid 54608 thread 6 bound to OS proc set {6}
OMP: pid 54504 tid 54610 thread 8 bound to OS proc set {8}
OMP: pid 54504 tid 54611 thread 9 bound to OS proc set {9}
OMP: pid 54504 tid 54612 thread 10 bound to OS proc set {10}
OMP: pid 54504 tid 54614 thread 12 bound to OS proc set {12}
OMP: pid 54504 tid 54616 thread 14 bound to OS proc set {14}
OMP: pid 54504 tid 54609 thread 7 bound to OS proc set {7}
OMP: pid 54504 tid 54615 thread 13 bound to OS proc set {13}
OMP: pid 54504 tid 54613 thread 11 bound to OS proc set {11}
OMP: pid 54504 tid 54619 thread 17 bound to OS proc set {17}
OMP: pid 54504 tid 54617 thread 15 bound to OS proc set {15}
OMP: pid 54504 tid 54635 thread 33 bound to OS proc set {33}
OMP: pid 54504 tid 54621 thread 19 bound to OS proc set {19}
OMP: pid 54504 tid 54651 thread 49 bound to OS proc set {49}
OMP: pid 54504 tid 54620 thread 18 bound to OS proc set {18}
OMP: pid 54504 tid 54637 thread 35 bound to OS proc set {35}
OMP: pid 54504 tid 54618 thread 16 bound to OS proc set {16}
OMP: pid 54504 tid 54653 thread 51 bound to OS proc set {51}
OMP: pid 54504 tid 54622 thread 20 bound to OS proc set {20}
OMP: pid 54504 tid 54636 thread 34 bound to OS proc set {34}
OMP: pid 54504 tid 54667 thread 65 bound to OS proc set {65}
OMP: pid 54504 tid 54652 thread 50 bound to OS proc set {50}
OMP: pid 54504 tid 54623 thread 21 bound to OS proc set {21}
OMP: pid 54504 tid 54628 thread 26 bound to OS proc set {26}
OMP: pid 54504 tid 54639 thread 37 bound to OS proc set {37}
OMP: pid 54504 tid 54627 thread 25 bound to OS proc set {25}
OMP: pid 54504 tid 54624 thread 22 bound to OS proc set {22}
OMP: pid 54504 tid 54630 thread 28 bound to OS proc set {28}
OMP: pid 54504 tid 54626 thread 24 bound to OS proc set {24}
OMP: pid 54504 tid 54625 thread 23 bound to OS proc set {23}
OMP: pid 54504 tid 54631 thread 29 bound to OS proc set {29}
OMP: pid 54504 tid 54629 thread 27 bound to OS proc set {27}
OMP: pid 54504 tid 54669 thread 67 bound to OS proc set {67}
OMP: pid 54504 tid 54634 thread 32 bound to OS proc set {32}
OMP: pid 54504 tid 54638 thread 36 bound to OS proc set {36}
OMP: pid 54504 tid 54656 thread 54 bound to OS proc set {54}
OMP: pid 54504 tid 54642 thread 40 bound to OS proc set {40}
OMP: pid 54504 tid 54644 thread 42 bound to OS proc set {42}
OMP: pid 54504 tid 54640 thread 38 bound to OS proc set {38}
OMP: pid 54504 tid 54632 thread 30 bound to OS proc set {30}
OMP: pid 54504 tid 54633 thread 31 bound to OS proc set {31}
OMP: pid 54504 tid 54647 thread 45 bound to OS proc set {45}
OMP: pid 54504 tid 54668 thread 66 bound to OS proc set {66}
OMP: pid 54504 tid 54659 thread 57 bound to OS proc set {57}
OMP: pid 54504 tid 54643 thread 41 bound to OS proc set {41}
OMP: pid 54504 tid 54650 thread 48 bound to OS proc set {48}
OMP: pid 54504 tid 54646 thread 44 bound to OS proc set {44}
OMP: pid 54504 tid 54660 thread 58 bound to OS proc set {58}
OMP: pid 54504 tid 54648 thread 46 bound to OS proc set {46}
OMP: pid 54504 tid 54641 thread 39 bound to OS proc set {39}
OMP: pid 54504 tid 54657 thread 55 bound to OS proc set {55}
OMP: pid 54504 tid 54671 thread 69 bound to OS proc set {69}
OMP: pid 54504 tid 54664 thread 62 bound to OS proc set {62}
OMP: pid 54504 tid 54654 thread 52 bound to OS proc set {52}
OMP: pid 54504 tid 54666 thread 64 bound to OS proc set {64}
OMP: pid 54504 tid 54662 thread 60 bound to OS proc set {60}
OMP: pid 54504 tid 54649 thread 47 bound to OS proc set {47}
OMP: pid 54504 tid 54676 thread 74 bound to OS proc set {74}
OMP: pid 54504 tid 54661 thread 59 bound to OS proc set {59}
OMP: pid 54504 tid 54655 thread 53 bound to OS proc set {53}
OMP: pid 54504 tid 54670 thread 68 bound to OS proc set {68}
OMP: pid 54504 tid 54663 thread 61 bound to OS proc set {61}
OMP: pid 54504 tid 54680 thread 78 bound to OS proc set {78}
OMP: pid 54504 tid 54645 thread 43 bound to OS proc set {43}
OMP: pid 54504 tid 54675 thread 73 bound to OS proc set {73}
OMP: pid 54504 tid 54672 thread 70 bound to OS proc set {70}
OMP: pid 54504 tid 54681 thread 79 bound to OS proc set {79}
OMP: pid 54504 tid 54678 thread 76 bound to OS proc set {76}
OMP: pid 54504 tid 54674 thread 72 bound to OS proc set {72}
OMP: pid 54504 tid 54665 thread 63 bound to OS proc set {63}
OMP: pid 54504 tid 54677 thread 75 bound to OS proc set {75}
OMP: pid 54504 tid 54658 thread 56 bound to OS proc set {56}
OMP: pid 54504 tid 54679 thread 77 bound to OS proc set {77}
OMP: pid 54504 tid 54683 thread 81 bound to OS proc set {81}
OMP: pid 54504 tid 54682 thread 80 bound to OS proc set {80}
OMP: pid 54504 tid 54684 thread 82 bound to OS proc set {82}
OMP: pid 54504 tid 54673 thread 71 bound to OS proc set {71}
OMP: pid 54504 tid 54685 thread 83 bound to OS proc set {83}
OMP: pid 54504 tid 54688 thread 86 bound to OS proc set {86}
OMP: pid 54504 tid 54687 thread 85 bound to OS proc set {85}
OMP: pid 54504 tid 54691 thread 89 bound to OS proc set {89}
OMP: pid 54504 tid 54686 thread 84 bound to OS proc set {84}
OMP: pid 54504 tid 54694 thread 92 bound to OS proc set {92}
OMP: pid 54504 tid 54690 thread 88 bound to OS proc set {88}
OMP: pid 54504 tid 54692 thread 90 bound to OS proc set {90}
OMP: pid 54504 tid 54689 thread 87 bound to OS proc set {87}
OMP: pid 54504 tid 54693 thread 91 bound to OS proc set {91}
OMP: pid 54504 tid 54697 thread 95 bound to OS proc set {95}
OMP: pid 54504 tid 54695 thread 93 bound to OS proc set {93}
OMP: pid 54504 tid 54696 thread 94 bound to OS proc set {94}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_1 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 54719 tid 54818 thread 1 bound to OS proc set {1}
OMP: pid 54719 tid 54819 thread 2 bound to OS proc set {2}
OMP: pid 54719 tid 54820 thread 3 bound to OS proc set {3}
OMP: pid 54719 tid 54719 thread 0 bound to OS proc set {0}
OMP: pid 54719 tid 54823 thread 6 bound to OS proc set {6}
OMP: pid 54719 tid 54829 thread 12 bound to OS proc set {12}
OMP: pid 54719 tid 54821 thread 4 bound to OS proc set {4}
OMP: pid 54719 tid 54822 thread 5 bound to OS proc set {5}
OMP: pid 54719 tid 54831 thread 14 bound to OS proc set {14}
OMP: pid 54719 tid 54834 thread 17 bound to OS proc set {17}
OMP: pid 54719 tid 54826 thread 9 bound to OS proc set {9}
OMP: pid 54719 tid 54827 thread 10 bound to OS proc set {10}
OMP: pid 54719 tid 54830 thread 13 bound to OS proc set {13}
OMP: pid 54719 tid 54835 thread 18 bound to OS proc set {18}
OMP: pid 54719 tid 54824 thread 7 bound to OS proc set {7}
OMP: pid 54719 tid 54832 thread 15 bound to OS proc set {15}
OMP: pid 54719 tid 54828 thread 11 bound to OS proc set {11}
OMP: pid 54719 tid 54850 thread 33 bound to OS proc set {33}
OMP: pid 54719 tid 54825 thread 8 bound to OS proc set {8}
OMP: pid 54719 tid 54851 thread 34 bound to OS proc set {34}
OMP: pid 54719 tid 54866 thread 49 bound to OS proc set {49}
OMP: pid 54719 tid 54833 thread 16 bound to OS proc set {16}
OMP: pid 54719 tid 54836 thread 19 bound to OS proc set {19}
OMP: pid 54719 tid 54867 thread 50 bound to OS proc set {50}
OMP: pid 54719 tid 54838 thread 21 bound to OS proc set {21}
OMP: pid 54719 tid 54882 thread 65 bound to OS proc set {65}
OMP: pid 54719 tid 54852 thread 35 bound to OS proc set {35}
OMP: pid 54719 tid 54841 thread 24 bound to OS proc set {24}
OMP: pid 54719 tid 54868 thread 51 bound to OS proc set {51}
OMP: pid 54719 tid 54837 thread 20 bound to OS proc set {20}
OMP: pid 54719 tid 54883 thread 66 bound to OS proc set {66}
OMP: pid 54719 tid 54839 thread 22 bound to OS proc set {22}
OMP: pid 54719 tid 54853 thread 36 bound to OS proc set {36}
OMP: pid 54719 tid 54842 thread 25 bound to OS proc set {25}
OMP: pid 54719 tid 54854 thread 37 bound to OS proc set {37}
OMP: pid 54719 tid 54845 thread 28 bound to OS proc set {28}
OMP: pid 54719 tid 54847 thread 30 bound to OS proc set {30}
OMP: pid 54719 tid 54844 thread 27 bound to OS proc set {27}
OMP: pid 54719 tid 54858 thread 41 bound to OS proc set {41}
OMP: pid 54719 tid 54843 thread 26 bound to OS proc set {26}
OMP: pid 54719 tid 54870 thread 53 bound to OS proc set {53}
OMP: pid 54719 tid 54849 thread 32 bound to OS proc set {32}
OMP: pid 54719 tid 54859 thread 42 bound to OS proc set {42}
OMP: pid 54719 tid 54840 thread 23 bound to OS proc set {23}
OMP: pid 54719 tid 54846 thread 29 bound to OS proc set {29}
OMP: pid 54719 tid 54869 thread 52 bound to OS proc set {52}
OMP: pid 54719 tid 54874 thread 57 bound to OS proc set {57}
OMP: pid 54719 tid 54871 thread 54 bound to OS proc set {54}
OMP: pid 54719 tid 54857 thread 40 bound to OS proc set {40}
OMP: pid 54719 tid 54855 thread 38 bound to OS proc set {38}
OMP: pid 54719 tid 54875 thread 58 bound to OS proc set {58}
OMP: pid 54719 tid 54860 thread 43 bound to OS proc set {43}
OMP: pid 54719 tid 54865 thread 48 bound to OS proc set {48}
OMP: pid 54719 tid 54856 thread 39 bound to OS proc set {39}
OMP: pid 54719 tid 54884 thread 67 bound to OS proc set {67}
OMP: pid 54719 tid 54878 thread 61 bound to OS proc set {61}
OMP: pid 54719 tid 54881 thread 64 bound to OS proc set {64}
OMP: pid 54719 tid 54872 thread 55 bound to OS proc set {55}
OMP: pid 54719 tid 54873 thread 56 bound to OS proc set {56}
OMP: pid 54719 tid 54877 thread 60 bound to OS proc set {60}
OMP: pid 54719 tid 54861 thread 44 bound to OS proc set {44}
OMP: pid 54719 tid 54876 thread 59 bound to OS proc set {59}
OMP: pid 54719 tid 54889 thread 72 bound to OS proc set {72}
OMP: pid 54719 tid 54892 thread 75 bound to OS proc set {75}
OMP: pid 54719 tid 54895 thread 78 bound to OS proc set {78}
OMP: pid 54719 tid 54880 thread 63 bound to OS proc set {63}
OMP: pid 54719 tid 54894 thread 77 bound to OS proc set {77}
OMP: pid 54719 tid 54893 thread 76 bound to OS proc set {76}
OMP: pid 54719 tid 54848 thread 31 bound to OS proc set {31}
OMP: pid 54719 tid 54896 thread 79 bound to OS proc set {79}
OMP: pid 54719 tid 54885 thread 68 bound to OS proc set {68}
OMP: pid 54719 tid 54888 thread 71 bound to OS proc set {71}
OMP: pid 54719 tid 54862 thread 45 bound to OS proc set {45}
OMP: pid 54719 tid 54879 thread 62 bound to OS proc set {62}
OMP: pid 54719 tid 54891 thread 74 bound to OS proc set {74}
OMP: pid 54719 tid 54864 thread 47 bound to OS proc set {47}
OMP: pid 54719 tid 54886 thread 69 bound to OS proc set {69}
OMP: pid 54719 tid 54898 thread 81 bound to OS proc set {81}
OMP: pid 54719 tid 54887 thread 70 bound to OS proc set {70}
OMP: pid 54719 tid 54900 thread 83 bound to OS proc set {83}
OMP: pid 54719 tid 54863 thread 46 bound to OS proc set {46}
OMP: pid 54719 tid 54899 thread 82 bound to OS proc set {82}
OMP: pid 54719 tid 54890 thread 73 bound to OS proc set {73}
OMP: pid 54719 tid 54897 thread 80 bound to OS proc set {80}
OMP: pid 54719 tid 54902 thread 85 bound to OS proc set {85}
OMP: pid 54719 tid 54906 thread 89 bound to OS proc set {89}
OMP: pid 54719 tid 54901 thread 84 bound to OS proc set {84}
OMP: pid 54719 tid 54904 thread 87 bound to OS proc set {87}
OMP: pid 54719 tid 54907 thread 90 bound to OS proc set {90}
OMP: pid 54719 tid 54905 thread 88 bound to OS proc set {88}
OMP: pid 54719 tid 54910 thread 93 bound to OS proc set {93}
OMP: pid 54719 tid 54908 thread 91 bound to OS proc set {91}
OMP: pid 54719 tid 54903 thread 86 bound to OS proc set {86}
OMP: pid 54719 tid 54909 thread 92 bound to OS proc set {92}
OMP: pid 54719 tid 54911 thread 94 bound to OS proc set {94}
OMP: pid 54719 tid 54912 thread 95 bound to OS proc set {95}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_2 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 54993 tid 55094 thread 3 bound to OS proc set {3}
OMP: pid 54993 tid 55092 thread 1 bound to OS proc set {1}
OMP: pid 54993 tid 55093 thread 2 bound to OS proc set {2}
OMP: pid 54993 tid 55096 thread 5 bound to OS proc set {5}
OMP: pid 54993 tid 55100 thread 9 bound to OS proc set {9}
OMP: pid 54993 tid 55095 thread 4 bound to OS proc set {4}
OMP: pid 54993 tid 54993 thread 0 bound to OS proc set {0}
OMP: pid 54993 tid 55097 thread 6 bound to OS proc set {6}
OMP: pid 54993 tid 55099 thread 8 bound to OS proc set {8}
OMP: pid 54993 tid 55098 thread 7 bound to OS proc set {7}
OMP: pid 54993 tid 55104 thread 13 bound to OS proc set {13}
OMP: pid 54993 tid 55101 thread 10 bound to OS proc set {10}
OMP: pid 54993 tid 55103 thread 12 bound to OS proc set {12}
OMP: pid 54993 tid 55108 thread 17 bound to OS proc set {17}
OMP: pid 54993 tid 55105 thread 14 bound to OS proc set {14}
OMP: pid 54993 tid 55102 thread 11 bound to OS proc set {11}
OMP: pid 54993 tid 55106 thread 15 bound to OS proc set {15}
OMP: pid 54993 tid 55124 thread 33 bound to OS proc set {33}
OMP: pid 54993 tid 55109 thread 18 bound to OS proc set {18}
OMP: pid 54993 tid 55125 thread 34 bound to OS proc set {34}
OMP: pid 54993 tid 55110 thread 19 bound to OS proc set {19}
OMP: pid 54993 tid 55140 thread 49 bound to OS proc set {49}
OMP: pid 54993 tid 55126 thread 35 bound to OS proc set {35}
OMP: pid 54993 tid 55107 thread 16 bound to OS proc set {16}
OMP: pid 54993 tid 55141 thread 50 bound to OS proc set {50}
OMP: pid 54993 tid 55123 thread 32 bound to OS proc set {32}
OMP: pid 54993 tid 55112 thread 21 bound to OS proc set {21}
OMP: pid 54993 tid 55116 thread 25 bound to OS proc set {25}
OMP: pid 54993 tid 55111 thread 20 bound to OS proc set {20}
OMP: pid 54993 tid 55128 thread 37 bound to OS proc set {37}
OMP: pid 54993 tid 55115 thread 24 bound to OS proc set {24}
OMP: pid 54993 tid 55139 thread 48 bound to OS proc set {48}
OMP: pid 54993 tid 55120 thread 29 bound to OS proc set {29}
OMP: pid 54993 tid 55127 thread 36 bound to OS proc set {36}
OMP: pid 54993 tid 55129 thread 38 bound to OS proc set {38}
OMP: pid 54993 tid 55114 thread 23 bound to OS proc set {23}
OMP: pid 54993 tid 55117 thread 26 bound to OS proc set {26}
OMP: pid 54993 tid 55132 thread 41 bound to OS proc set {41}
OMP: pid 54993 tid 55121 thread 30 bound to OS proc set {30}
OMP: pid 54993 tid 55156 thread 65 bound to OS proc set {65}
OMP: pid 54993 tid 55118 thread 27 bound to OS proc set {27}
OMP: pid 54993 tid 55133 thread 42 bound to OS proc set {42}
OMP: pid 54993 tid 55119 thread 28 bound to OS proc set {28}
OMP: pid 54993 tid 55136 thread 45 bound to OS proc set {45}
OMP: pid 54993 tid 55131 thread 40 bound to OS proc set {40}
OMP: pid 54993 tid 55113 thread 22 bound to OS proc set {22}
OMP: pid 54993 tid 55130 thread 39 bound to OS proc set {39}
OMP: pid 54993 tid 55122 thread 31 bound to OS proc set {31}
OMP: pid 54993 tid 55134 thread 43 bound to OS proc set {43}
OMP: pid 54993 tid 55137 thread 46 bound to OS proc set {46}
OMP: pid 54993 tid 55135 thread 44 bound to OS proc set {44}
OMP: pid 54993 tid 55138 thread 47 bound to OS proc set {47}
OMP: pid 54993 tid 55158 thread 67 bound to OS proc set {67}
OMP: pid 54993 tid 55144 thread 53 bound to OS proc set {53}
OMP: pid 54993 tid 55157 thread 66 bound to OS proc set {66}
OMP: pid 54993 tid 55146 thread 55 bound to OS proc set {55}
OMP: pid 54993 tid 55160 thread 69 bound to OS proc set {69}
OMP: pid 54993 tid 55145 thread 54 bound to OS proc set {54}
OMP: pid 54993 tid 55142 thread 51 bound to OS proc set {51}
OMP: pid 54993 tid 55147 thread 56 bound to OS proc set {56}
OMP: pid 54993 tid 55161 thread 70 bound to OS proc set {70}
OMP: pid 54993 tid 55149 thread 58 bound to OS proc set {58}
OMP: pid 54993 tid 55155 thread 64 bound to OS proc set {64}
OMP: pid 54993 tid 55164 thread 73 bound to OS proc set {73}
OMP: pid 54993 tid 55163 thread 72 bound to OS proc set {72}
OMP: pid 54993 tid 55143 thread 52 bound to OS proc set {52}
OMP: pid 54993 tid 55165 thread 74 bound to OS proc set {74}
OMP: pid 54993 tid 55162 thread 71 bound to OS proc set {71}
OMP: pid 54993 tid 55154 thread 63 bound to OS proc set {63}
OMP: pid 54993 tid 55151 thread 60 bound to OS proc set {60}
OMP: pid 54993 tid 55152 thread 61 bound to OS proc set {61}
OMP: pid 54993 tid 55153 thread 62 bound to OS proc set {62}
OMP: pid 54993 tid 55169 thread 78 bound to OS proc set {78}
OMP: pid 54993 tid 55150 thread 59 bound to OS proc set {59}
OMP: pid 54993 tid 55166 thread 75 bound to OS proc set {75}
OMP: pid 54993 tid 55159 thread 68 bound to OS proc set {68}
OMP: pid 54993 tid 55167 thread 76 bound to OS proc set {76}
OMP: pid 54993 tid 55168 thread 77 bound to OS proc set {77}
OMP: pid 54993 tid 55172 thread 81 bound to OS proc set {81}
OMP: pid 54993 tid 55148 thread 57 bound to OS proc set {57}
OMP: pid 54993 tid 55174 thread 83 bound to OS proc set {83}
OMP: pid 54993 tid 55170 thread 79 bound to OS proc set {79}
OMP: pid 54993 tid 55171 thread 80 bound to OS proc set {80}
OMP: pid 54993 tid 55176 thread 85 bound to OS proc set {85}
OMP: pid 54993 tid 55175 thread 84 bound to OS proc set {84}
OMP: pid 54993 tid 55180 thread 89 bound to OS proc set {89}
OMP: pid 54993 tid 55173 thread 82 bound to OS proc set {82}
OMP: pid 54993 tid 55184 thread 93 bound to OS proc set {93}
OMP: pid 54993 tid 55181 thread 90 bound to OS proc set {90}
OMP: pid 54993 tid 55182 thread 91 bound to OS proc set {91}
OMP: pid 54993 tid 55179 thread 88 bound to OS proc set {88}
OMP: pid 54993 tid 55183 thread 92 bound to OS proc set {92}
OMP: pid 54993 tid 55178 thread 87 bound to OS proc set {87}
OMP: pid 54993 tid 55186 thread 95 bound to OS proc set {95}
OMP: pid 54993 tid 55185 thread 94 bound to OS proc set {94}
OMP: pid 54993 tid 55177 thread 86 bound to OS proc set {86}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_3 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 55208 tid 55307 thread 1 bound to OS proc set {1}
OMP: pid 55208 tid 55309 thread 3 bound to OS proc set {3}
OMP: pid 55208 tid 55208 thread 0 bound to OS proc set {0}
OMP: pid 55208 tid 55315 thread 9 bound to OS proc set {9}
OMP: pid 55208 tid 55312 thread 6 bound to OS proc set {6}
OMP: pid 55208 tid 55310 thread 4 bound to OS proc set {4}
OMP: pid 55208 tid 55311 thread 5 bound to OS proc set {5}
OMP: pid 55208 tid 55319 thread 13 bound to OS proc set {13}
OMP: pid 55208 tid 55308 thread 2 bound to OS proc set {2}
OMP: pid 55208 tid 55316 thread 10 bound to OS proc set {10}
OMP: pid 55208 tid 55318 thread 12 bound to OS proc set {12}
OMP: pid 55208 tid 55314 thread 8 bound to OS proc set {8}
OMP: pid 55208 tid 55317 thread 11 bound to OS proc set {11}
OMP: pid 55208 tid 55321 thread 15 bound to OS proc set {15}
OMP: pid 55208 tid 55320 thread 14 bound to OS proc set {14}
OMP: pid 55208 tid 55340 thread 34 bound to OS proc set {34}
OMP: pid 55208 tid 55325 thread 19 bound to OS proc set {19}
OMP: pid 55208 tid 55341 thread 35 bound to OS proc set {35}
OMP: pid 55208 tid 55323 thread 17 bound to OS proc set {17}
OMP: pid 55208 tid 55322 thread 16 bound to OS proc set {16}
OMP: pid 55208 tid 55356 thread 50 bound to OS proc set {50}
OMP: pid 55208 tid 55313 thread 7 bound to OS proc set {7}
OMP: pid 55208 tid 55339 thread 33 bound to OS proc set {33}
OMP: pid 55208 tid 55357 thread 51 bound to OS proc set {51}
OMP: pid 55208 tid 55373 thread 67 bound to OS proc set {67}
OMP: pid 55208 tid 55372 thread 66 bound to OS proc set {66}
OMP: pid 55208 tid 55355 thread 49 bound to OS proc set {49}
OMP: pid 55208 tid 55327 thread 21 bound to OS proc set {21}
OMP: pid 55208 tid 55326 thread 20 bound to OS proc set {20}
OMP: pid 55208 tid 55354 thread 48 bound to OS proc set {48}
OMP: pid 55208 tid 55331 thread 25 bound to OS proc set {25}
OMP: pid 55208 tid 55332 thread 26 bound to OS proc set {26}
OMP: pid 55208 tid 55330 thread 24 bound to OS proc set {24}
OMP: pid 55208 tid 55328 thread 22 bound to OS proc set {22}
OMP: pid 55208 tid 55329 thread 23 bound to OS proc set {23}
OMP: pid 55208 tid 55343 thread 37 bound to OS proc set {37}
OMP: pid 55208 tid 55342 thread 36 bound to OS proc set {36}
OMP: pid 55208 tid 55348 thread 42 bound to OS proc set {42}
OMP: pid 55208 tid 55324 thread 18 bound to OS proc set {18}
OMP: pid 55208 tid 55335 thread 29 bound to OS proc set {29}
OMP: pid 55208 tid 55347 thread 41 bound to OS proc set {41}
OMP: pid 55208 tid 55334 thread 28 bound to OS proc set {28}
OMP: pid 55208 tid 55371 thread 65 bound to OS proc set {65}
OMP: pid 55208 tid 55346 thread 40 bound to OS proc set {40}
OMP: pid 55208 tid 55338 thread 32 bound to OS proc set {32}
OMP: pid 55208 tid 55337 thread 31 bound to OS proc set {31}
OMP: pid 55208 tid 55359 thread 53 bound to OS proc set {53}
OMP: pid 55208 tid 55345 thread 39 bound to OS proc set {39}
OMP: pid 55208 tid 55344 thread 38 bound to OS proc set {38}
OMP: pid 55208 tid 55360 thread 54 bound to OS proc set {54}
OMP: pid 55208 tid 55358 thread 52 bound to OS proc set {52}
OMP: pid 55208 tid 55352 thread 46 bound to OS proc set {46}
OMP: pid 55208 tid 55333 thread 27 bound to OS proc set {27}
OMP: pid 55208 tid 55349 thread 43 bound to OS proc set {43}
OMP: pid 55208 tid 55361 thread 55 bound to OS proc set {55}
OMP: pid 55208 tid 55351 thread 45 bound to OS proc set {45}
OMP: pid 55208 tid 55350 thread 44 bound to OS proc set {44}
OMP: pid 55208 tid 55336 thread 30 bound to OS proc set {30}
OMP: pid 55208 tid 55376 thread 70 bound to OS proc set {70}
OMP: pid 55208 tid 55368 thread 62 bound to OS proc set {62}
OMP: pid 55208 tid 55380 thread 74 bound to OS proc set {74}
OMP: pid 55208 tid 55364 thread 58 bound to OS proc set {58}
OMP: pid 55208 tid 55367 thread 61 bound to OS proc set {61}
OMP: pid 55208 tid 55363 thread 57 bound to OS proc set {57}
OMP: pid 55208 tid 55366 thread 60 bound to OS proc set {60}
OMP: pid 55208 tid 55377 thread 71 bound to OS proc set {71}
OMP: pid 55208 tid 55362 thread 56 bound to OS proc set {56}
OMP: pid 55208 tid 55379 thread 73 bound to OS proc set {73}
OMP: pid 55208 tid 55378 thread 72 bound to OS proc set {72}
OMP: pid 55208 tid 55383 thread 77 bound to OS proc set {77}
OMP: pid 55208 tid 55375 thread 69 bound to OS proc set {69}
OMP: pid 55208 tid 55382 thread 76 bound to OS proc set {76}
OMP: pid 55208 tid 55353 thread 47 bound to OS proc set {47}
OMP: pid 55208 tid 55381 thread 75 bound to OS proc set {75}
OMP: pid 55208 tid 55369 thread 63 bound to OS proc set {63}
OMP: pid 55208 tid 55365 thread 59 bound to OS proc set {59}
OMP: pid 55208 tid 55370 thread 64 bound to OS proc set {64}
OMP: pid 55208 tid 55384 thread 78 bound to OS proc set {78}
OMP: pid 55208 tid 55385 thread 79 bound to OS proc set {79}
OMP: pid 55208 tid 55388 thread 82 bound to OS proc set {82}
OMP: pid 55208 tid 55389 thread 83 bound to OS proc set {83}
OMP: pid 55208 tid 55374 thread 68 bound to OS proc set {68}
OMP: pid 55208 tid 55387 thread 81 bound to OS proc set {81}
OMP: pid 55208 tid 55386 thread 80 bound to OS proc set {80}
OMP: pid 55208 tid 55391 thread 85 bound to OS proc set {85}
OMP: pid 55208 tid 55390 thread 84 bound to OS proc set {84}
OMP: pid 55208 tid 55395 thread 89 bound to OS proc set {89}
OMP: pid 55208 tid 55394 thread 88 bound to OS proc set {88}
OMP: pid 55208 tid 55400 thread 94 bound to OS proc set {94}
OMP: pid 55208 tid 55393 thread 87 bound to OS proc set {87}
OMP: pid 55208 tid 55399 thread 93 bound to OS proc set {93}
OMP: pid 55208 tid 55392 thread 86 bound to OS proc set {86}
OMP: pid 55208 tid 55398 thread 92 bound to OS proc set {92}
OMP: pid 55208 tid 55401 thread 95 bound to OS proc set {95}
OMP: pid 55208 tid 55396 thread 90 bound to OS proc set {90}
OMP: pid 55208 tid 55397 thread 91 bound to OS proc set {91}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_4 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 55423 tid 55524 thread 3 bound to OS proc set {3}
OMP: pid 55423 tid 55423 thread 0 bound to OS proc set {0}
OMP: pid 55423 tid 55522 thread 1 bound to OS proc set {1}
OMP: pid 55423 tid 55527 thread 6 bound to OS proc set {6}
OMP: pid 55423 tid 55523 thread 2 bound to OS proc set {2}
OMP: pid 55423 tid 55530 thread 9 bound to OS proc set {9}
OMP: pid 55423 tid 55526 thread 5 bound to OS proc set {5}
OMP: pid 55423 tid 55531 thread 10 bound to OS proc set {10}
OMP: pid 55423 tid 55529 thread 8 bound to OS proc set {8}
OMP: pid 55423 tid 55533 thread 12 bound to OS proc set {12}
OMP: pid 55423 tid 55535 thread 14 bound to OS proc set {14}
OMP: pid 55423 tid 55534 thread 13 bound to OS proc set {13}
OMP: pid 55423 tid 55532 thread 11 bound to OS proc set {11}
OMP: pid 55423 tid 55538 thread 17 bound to OS proc set {17}
OMP: pid 55423 tid 55528 thread 7 bound to OS proc set {7}
OMP: pid 55423 tid 55536 thread 15 bound to OS proc set {15}
OMP: pid 55423 tid 55540 thread 19 bound to OS proc set {19}
OMP: pid 55423 tid 55554 thread 33 bound to OS proc set {33}
OMP: pid 55423 tid 55570 thread 49 bound to OS proc set {49}
OMP: pid 55423 tid 55537 thread 16 bound to OS proc set {16}
OMP: pid 55423 tid 55525 thread 4 bound to OS proc set {4}
OMP: pid 55423 tid 55539 thread 18 bound to OS proc set {18}
OMP: pid 55423 tid 55556 thread 35 bound to OS proc set {35}
OMP: pid 55423 tid 55586 thread 65 bound to OS proc set {65}
OMP: pid 55423 tid 55555 thread 34 bound to OS proc set {34}
OMP: pid 55423 tid 55542 thread 21 bound to OS proc set {21}
OMP: pid 55423 tid 55541 thread 20 bound to OS proc set {20}
OMP: pid 55423 tid 55558 thread 37 bound to OS proc set {37}
OMP: pid 55423 tid 55547 thread 26 bound to OS proc set {26}
OMP: pid 55423 tid 55557 thread 36 bound to OS proc set {36}
OMP: pid 55423 tid 55559 thread 38 bound to OS proc set {38}
OMP: pid 55423 tid 55588 thread 67 bound to OS proc set {67}
OMP: pid 55423 tid 55571 thread 50 bound to OS proc set {50}
OMP: pid 55423 tid 55551 thread 30 bound to OS proc set {30}
OMP: pid 55423 tid 55553 thread 32 bound to OS proc set {32}
OMP: pid 55423 tid 55563 thread 42 bound to OS proc set {42}
OMP: pid 55423 tid 55546 thread 25 bound to OS proc set {25}
OMP: pid 55423 tid 55550 thread 29 bound to OS proc set {29}
OMP: pid 55423 tid 55548 thread 27 bound to OS proc set {27}
OMP: pid 55423 tid 55572 thread 51 bound to OS proc set {51}
OMP: pid 55423 tid 55549 thread 28 bound to OS proc set {28}
OMP: pid 55423 tid 55574 thread 53 bound to OS proc set {53}
OMP: pid 55423 tid 55561 thread 40 bound to OS proc set {40}
OMP: pid 55423 tid 55543 thread 22 bound to OS proc set {22}
OMP: pid 55423 tid 55587 thread 66 bound to OS proc set {66}
OMP: pid 55423 tid 55562 thread 41 bound to OS proc set {41}
OMP: pid 55423 tid 55575 thread 54 bound to OS proc set {54}
OMP: pid 55423 tid 55566 thread 45 bound to OS proc set {45}
OMP: pid 55423 tid 55544 thread 23 bound to OS proc set {23}
OMP: pid 55423 tid 55585 thread 64 bound to OS proc set {64}
OMP: pid 55423 tid 55560 thread 39 bound to OS proc set {39}
OMP: pid 55423 tid 55552 thread 31 bound to OS proc set {31}
OMP: pid 55423 tid 55569 thread 48 bound to OS proc set {48}
OMP: pid 55423 tid 55589 thread 68 bound to OS proc set {68}
OMP: pid 55423 tid 55565 thread 44 bound to OS proc set {44}
OMP: pid 55423 tid 55590 thread 69 bound to OS proc set {69}
OMP: pid 55423 tid 55579 thread 58 bound to OS proc set {58}
OMP: pid 55423 tid 55591 thread 70 bound to OS proc set {70}
OMP: pid 55423 tid 55567 thread 46 bound to OS proc set {46}
OMP: pid 55423 tid 55595 thread 74 bound to OS proc set {74}
OMP: pid 55423 tid 55577 thread 56 bound to OS proc set {56}
OMP: pid 55423 tid 55573 thread 52 bound to OS proc set {52}
OMP: pid 55423 tid 55578 thread 57 bound to OS proc set {57}
OMP: pid 55423 tid 55568 thread 47 bound to OS proc set {47}
OMP: pid 55423 tid 55576 thread 55 bound to OS proc set {55}
OMP: pid 55423 tid 55580 thread 59 bound to OS proc set {59}
OMP: pid 55423 tid 55593 thread 72 bound to OS proc set {72}
OMP: pid 55423 tid 55545 thread 24 bound to OS proc set {24}
OMP: pid 55423 tid 55599 thread 78 bound to OS proc set {78}
OMP: pid 55423 tid 55597 thread 76 bound to OS proc set {76}
OMP: pid 55423 tid 55582 thread 61 bound to OS proc set {61}
OMP: pid 55423 tid 55594 thread 73 bound to OS proc set {73}
OMP: pid 55423 tid 55598 thread 77 bound to OS proc set {77}
OMP: pid 55423 tid 55596 thread 75 bound to OS proc set {75}
OMP: pid 55423 tid 55592 thread 71 bound to OS proc set {71}
OMP: pid 55423 tid 55602 thread 81 bound to OS proc set {81}
OMP: pid 55423 tid 55583 thread 62 bound to OS proc set {62}
OMP: pid 55423 tid 55603 thread 82 bound to OS proc set {82}
OMP: pid 55423 tid 55581 thread 60 bound to OS proc set {60}
OMP: pid 55423 tid 55604 thread 83 bound to OS proc set {83}
OMP: pid 55423 tid 55600 thread 79 bound to OS proc set {79}
OMP: pid 55423 tid 55609 thread 88 bound to OS proc set {88}
OMP: pid 55423 tid 55601 thread 80 bound to OS proc set {80}
OMP: pid 55423 tid 55584 thread 63 bound to OS proc set {63}
OMP: pid 55423 tid 55607 thread 86 bound to OS proc set {86}
OMP: pid 55423 tid 55564 thread 43 bound to OS proc set {43}
OMP: pid 55423 tid 55614 thread 93 bound to OS proc set {93}
OMP: pid 55423 tid 55613 thread 92 bound to OS proc set {92}
OMP: pid 55423 tid 55608 thread 87 bound to OS proc set {87}
OMP: pid 55423 tid 55610 thread 89 bound to OS proc set {89}
OMP: pid 55423 tid 55605 thread 84 bound to OS proc set {84}
OMP: pid 55423 tid 55616 thread 95 bound to OS proc set {95}
OMP: pid 55423 tid 55615 thread 94 bound to OS proc set {94}
OMP: pid 55423 tid 55612 thread 91 bound to OS proc set {91}
OMP: pid 55423 tid 55606 thread 85 bound to OS proc set {85}
OMP: pid 55423 tid 55611 thread 90 bound to OS proc set {90}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_5 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 55698 tid 55797 thread 1 bound to OS proc set {1}
OMP: pid 55698 tid 55798 thread 2 bound to OS proc set {2}
OMP: pid 55698 tid 55799 thread 3 bound to OS proc set {3}
OMP: pid 55698 tid 55698 thread 0 bound to OS proc set {0}
OMP: pid 55698 tid 55801 thread 5 bound to OS proc set {5}
OMP: pid 55698 tid 55805 thread 9 bound to OS proc set {9}
OMP: pid 55698 tid 55804 thread 8 bound to OS proc set {8}
OMP: pid 55698 tid 55800 thread 4 bound to OS proc set {4}
OMP: pid 55698 tid 55802 thread 6 bound to OS proc set {6}
OMP: pid 55698 tid 55809 thread 13 bound to OS proc set {13}
OMP: pid 55698 tid 55806 thread 10 bound to OS proc set {10}
OMP: pid 55698 tid 55807 thread 11 bound to OS proc set {11}
OMP: pid 55698 tid 55803 thread 7 bound to OS proc set {7}
OMP: pid 55698 tid 55813 thread 17 bound to OS proc set {17}
OMP: pid 55698 tid 55814 thread 18 bound to OS proc set {18}
OMP: pid 55698 tid 55810 thread 14 bound to OS proc set {14}
OMP: pid 55698 tid 55811 thread 15 bound to OS proc set {15}
OMP: pid 55698 tid 55845 thread 49 bound to OS proc set {49}
OMP: pid 55698 tid 55815 thread 19 bound to OS proc set {19}
OMP: pid 55698 tid 55812 thread 16 bound to OS proc set {16}
OMP: pid 55698 tid 55861 thread 65 bound to OS proc set {65}
OMP: pid 55698 tid 55808 thread 12 bound to OS proc set {12}
OMP: pid 55698 tid 55817 thread 21 bound to OS proc set {21}
OMP: pid 55698 tid 55816 thread 20 bound to OS proc set {20}
OMP: pid 55698 tid 55847 thread 51 bound to OS proc set {51}
OMP: pid 55698 tid 55863 thread 67 bound to OS proc set {67}
OMP: pid 55698 tid 55831 thread 35 bound to OS proc set {35}
OMP: pid 55698 tid 55818 thread 22 bound to OS proc set {22}
OMP: pid 55698 tid 55825 thread 29 bound to OS proc set {29}
OMP: pid 55698 tid 55844 thread 48 bound to OS proc set {48}
OMP: pid 55698 tid 55828 thread 32 bound to OS proc set {32}
OMP: pid 55698 tid 55846 thread 50 bound to OS proc set {50}
OMP: pid 55698 tid 55821 thread 25 bound to OS proc set {25}
OMP: pid 55698 tid 55822 thread 26 bound to OS proc set {26}
OMP: pid 55698 tid 55820 thread 24 bound to OS proc set {24}
OMP: pid 55698 tid 55819 thread 23 bound to OS proc set {23}
OMP: pid 55698 tid 55849 thread 53 bound to OS proc set {53}
OMP: pid 55698 tid 55824 thread 28 bound to OS proc set {28}
OMP: pid 55698 tid 55850 thread 54 bound to OS proc set {54}
OMP: pid 55698 tid 55826 thread 30 bound to OS proc set {30}
OMP: pid 55698 tid 55862 thread 66 bound to OS proc set {66}
OMP: pid 55698 tid 55823 thread 27 bound to OS proc set {27}
OMP: pid 55698 tid 55830 thread 34 bound to OS proc set {34}
OMP: pid 55698 tid 55829 thread 33 bound to OS proc set {33}
OMP: pid 55698 tid 55827 thread 31 bound to OS proc set {31}
OMP: pid 55698 tid 55832 thread 36 bound to OS proc set {36}
OMP: pid 55698 tid 55852 thread 56 bound to OS proc set {56}
OMP: pid 55698 tid 55833 thread 37 bound to OS proc set {37}
OMP: pid 55698 tid 55854 thread 58 bound to OS proc set {58}
OMP: pid 55698 tid 55851 thread 55 bound to OS proc set {55}
OMP: pid 55698 tid 55834 thread 38 bound to OS proc set {38}
OMP: pid 55698 tid 55866 thread 70 bound to OS proc set {70}
OMP: pid 55698 tid 55853 thread 57 bound to OS proc set {57}
OMP: pid 55698 tid 55870 thread 74 bound to OS proc set {74}
OMP: pid 55698 tid 55865 thread 69 bound to OS proc set {69}
OMP: pid 55698 tid 55860 thread 64 bound to OS proc set {64}
OMP: pid 55698 tid 55837 thread 41 bound to OS proc set {41}
OMP: pid 55698 tid 55857 thread 61 bound to OS proc set {61}
OMP: pid 55698 tid 55869 thread 73 bound to OS proc set {73}
OMP: pid 55698 tid 55858 thread 62 bound to OS proc set {62}
OMP: pid 55698 tid 55841 thread 45 bound to OS proc set {45}
OMP: pid 55698 tid 55838 thread 42 bound to OS proc set {42}
OMP: pid 55698 tid 55867 thread 71 bound to OS proc set {71}
OMP: pid 55698 tid 55848 thread 52 bound to OS proc set {52}
OMP: pid 55698 tid 55856 thread 60 bound to OS proc set {60}
OMP: pid 55698 tid 55874 thread 78 bound to OS proc set {78}
OMP: pid 55698 tid 55836 thread 40 bound to OS proc set {40}
OMP: pid 55698 tid 55868 thread 72 bound to OS proc set {72}
OMP: pid 55698 tid 55873 thread 77 bound to OS proc set {77}
OMP: pid 55698 tid 55855 thread 59 bound to OS proc set {59}
OMP: pid 55698 tid 55877 thread 81 bound to OS proc set {81}
OMP: pid 55698 tid 55871 thread 75 bound to OS proc set {75}
OMP: pid 55698 tid 55843 thread 47 bound to OS proc set {47}
OMP: pid 55698 tid 55872 thread 76 bound to OS proc set {76}
OMP: pid 55698 tid 55839 thread 43 bound to OS proc set {43}
OMP: pid 55698 tid 55875 thread 79 bound to OS proc set {79}
OMP: pid 55698 tid 55840 thread 44 bound to OS proc set {44}
OMP: pid 55698 tid 55835 thread 39 bound to OS proc set {39}
OMP: pid 55698 tid 55842 thread 46 bound to OS proc set {46}
OMP: pid 55698 tid 55879 thread 83 bound to OS proc set {83}
OMP: pid 55698 tid 55864 thread 68 bound to OS proc set {68}
OMP: pid 55698 tid 55878 thread 82 bound to OS proc set {82}
OMP: pid 55698 tid 55876 thread 80 bound to OS proc set {80}
OMP: pid 55698 tid 55884 thread 88 bound to OS proc set {88}
OMP: pid 55698 tid 55885 thread 89 bound to OS proc set {89}
OMP: pid 55698 tid 55859 thread 63 bound to OS proc set {63}
OMP: pid 55698 tid 55880 thread 84 bound to OS proc set {84}
OMP: pid 55698 tid 55881 thread 85 bound to OS proc set {85}
OMP: pid 55698 tid 55888 thread 92 bound to OS proc set {92}
OMP: pid 55698 tid 55889 thread 93 bound to OS proc set {93}
OMP: pid 55698 tid 55891 thread 95 bound to OS proc set {95}
OMP: pid 55698 tid 55886 thread 90 bound to OS proc set {90}
OMP: pid 55698 tid 55883 thread 87 bound to OS proc set {87}
OMP: pid 55698 tid 55887 thread 91 bound to OS proc set {91}
OMP: pid 55698 tid 55890 thread 94 bound to OS proc set {94}
OMP: pid 55698 tid 55882 thread 86 bound to OS proc set {86}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_6 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 55913 tid 56014 thread 3 bound to OS proc set {3}
OMP: pid 55913 tid 56015 thread 4 bound to OS proc set {4}
OMP: pid 55913 tid 56016 thread 5 bound to OS proc set {5}
OMP: pid 55913 tid 56020 thread 9 bound to OS proc set {9}
OMP: pid 55913 tid 56017 thread 6 bound to OS proc set {6}
OMP: pid 55913 tid 55913 thread 0 bound to OS proc set {0}
OMP: pid 55913 tid 56019 thread 8 bound to OS proc set {8}
OMP: pid 55913 tid 56021 thread 10 bound to OS proc set {10}
OMP: pid 55913 tid 56024 thread 13 bound to OS proc set {13}
OMP: pid 55913 tid 56018 thread 7 bound to OS proc set {7}
OMP: pid 55913 tid 56023 thread 12 bound to OS proc set {12}
OMP: pid 55913 tid 56025 thread 14 bound to OS proc set {14}
OMP: pid 55913 tid 56012 thread 1 bound to OS proc set {1}
OMP: pid 55913 tid 56013 thread 2 bound to OS proc set {2}
OMP: pid 55913 tid 56022 thread 11 bound to OS proc set {11}
OMP: pid 55913 tid 56028 thread 17 bound to OS proc set {17}
OMP: pid 55913 tid 56026 thread 15 bound to OS proc set {15}
OMP: pid 55913 tid 56044 thread 33 bound to OS proc set {33}
OMP: pid 55913 tid 56029 thread 18 bound to OS proc set {18}
OMP: pid 55913 tid 56030 thread 19 bound to OS proc set {19}
OMP: pid 55913 tid 56045 thread 34 bound to OS proc set {34}
OMP: pid 55913 tid 56046 thread 35 bound to OS proc set {35}
OMP: pid 55913 tid 56027 thread 16 bound to OS proc set {16}
OMP: pid 55913 tid 56043 thread 32 bound to OS proc set {32}
OMP: pid 55913 tid 56032 thread 21 bound to OS proc set {21}
OMP: pid 55913 tid 56060 thread 49 bound to OS proc set {49}
OMP: pid 55913 tid 56031 thread 20 bound to OS proc set {20}
OMP: pid 55913 tid 56036 thread 25 bound to OS proc set {25}
OMP: pid 55913 tid 56040 thread 29 bound to OS proc set {29}
OMP: pid 55913 tid 56033 thread 22 bound to OS proc set {22}
OMP: pid 55913 tid 56035 thread 24 bound to OS proc set {24}
OMP: pid 55913 tid 56061 thread 50 bound to OS proc set {50}
OMP: pid 55913 tid 56034 thread 23 bound to OS proc set {23}
OMP: pid 55913 tid 56039 thread 28 bound to OS proc set {28}
OMP: pid 55913 tid 56076 thread 65 bound to OS proc set {65}
OMP: pid 55913 tid 56037 thread 26 bound to OS proc set {26}
OMP: pid 55913 tid 56047 thread 36 bound to OS proc set {36}
OMP: pid 55913 tid 56038 thread 27 bound to OS proc set {27}
OMP: pid 55913 tid 56042 thread 31 bound to OS proc set {31}
OMP: pid 55913 tid 56062 thread 51 bound to OS proc set {51}
OMP: pid 55913 tid 56077 thread 66 bound to OS proc set {66}
OMP: pid 55913 tid 56052 thread 41 bound to OS proc set {41}
OMP: pid 55913 tid 56051 thread 40 bound to OS proc set {40}
OMP: pid 55913 tid 56048 thread 37 bound to OS proc set {37}
OMP: pid 55913 tid 56053 thread 42 bound to OS proc set {42}
OMP: pid 55913 tid 56078 thread 67 bound to OS proc set {67}
OMP: pid 55913 tid 56064 thread 53 bound to OS proc set {53}
OMP: pid 55913 tid 56041 thread 30 bound to OS proc set {30}
OMP: pid 55913 tid 56068 thread 57 bound to OS proc set {57}
OMP: pid 55913 tid 56049 thread 38 bound to OS proc set {38}
OMP: pid 55913 tid 56063 thread 52 bound to OS proc set {52}
OMP: pid 55913 tid 56059 thread 48 bound to OS proc set {48}
OMP: pid 55913 tid 56055 thread 44 bound to OS proc set {44}
OMP: pid 55913 tid 56080 thread 69 bound to OS proc set {69}
OMP: pid 55913 tid 56067 thread 56 bound to OS proc set {56}
OMP: pid 55913 tid 56075 thread 64 bound to OS proc set {64}
OMP: pid 55913 tid 56066 thread 55 bound to OS proc set {55}
OMP: pid 55913 tid 56056 thread 45 bound to OS proc set {45}
OMP: pid 55913 tid 56057 thread 46 bound to OS proc set {46}
OMP: pid 55913 tid 56084 thread 73 bound to OS proc set {73}
OMP: pid 55913 tid 56079 thread 68 bound to OS proc set {68}
OMP: pid 55913 tid 56073 thread 62 bound to OS proc set {62}
OMP: pid 55913 tid 56070 thread 59 bound to OS proc set {59}
OMP: pid 55913 tid 56072 thread 61 bound to OS proc set {61}
OMP: pid 55913 tid 56083 thread 72 bound to OS proc set {72}
OMP: pid 55913 tid 56065 thread 54 bound to OS proc set {54}
OMP: pid 55913 tid 56069 thread 58 bound to OS proc set {58}
OMP: pid 55913 tid 56088 thread 77 bound to OS proc set {77}
OMP: pid 55913 tid 56071 thread 60 bound to OS proc set {60}
OMP: pid 55913 tid 56085 thread 74 bound to OS proc set {74}
OMP: pid 55913 tid 56082 thread 71 bound to OS proc set {71}
OMP: pid 55913 tid 56087 thread 76 bound to OS proc set {76}
OMP: pid 55913 tid 56089 thread 78 bound to OS proc set {78}
OMP: pid 55913 tid 56058 thread 47 bound to OS proc set {47}
OMP: pid 55913 tid 56092 thread 81 bound to OS proc set {81}
OMP: pid 55913 tid 56086 thread 75 bound to OS proc set {75}
OMP: pid 55913 tid 56090 thread 79 bound to OS proc set {79}
OMP: pid 55913 tid 56050 thread 39 bound to OS proc set {39}
OMP: pid 55913 tid 56093 thread 82 bound to OS proc set {82}
OMP: pid 55913 tid 56074 thread 63 bound to OS proc set {63}
OMP: pid 55913 tid 56081 thread 70 bound to OS proc set {70}
OMP: pid 55913 tid 56094 thread 83 bound to OS proc set {83}
OMP: pid 55913 tid 56091 thread 80 bound to OS proc set {80}
OMP: pid 55913 tid 56100 thread 89 bound to OS proc set {89}
OMP: pid 55913 tid 56096 thread 85 bound to OS proc set {85}
OMP: pid 55913 tid 56101 thread 90 bound to OS proc set {90}
OMP: pid 55913 tid 56104 thread 93 bound to OS proc set {93}
OMP: pid 55913 tid 56054 thread 43 bound to OS proc set {43}
OMP: pid 55913 tid 56098 thread 87 bound to OS proc set {87}
OMP: pid 55913 tid 56095 thread 84 bound to OS proc set {84}
OMP: pid 55913 tid 56106 thread 95 bound to OS proc set {95}
OMP: pid 55913 tid 56102 thread 91 bound to OS proc set {91}
OMP: pid 55913 tid 56097 thread 86 bound to OS proc set {86}
OMP: pid 55913 tid 56099 thread 88 bound to OS proc set {88}
OMP: pid 55913 tid 56105 thread 94 bound to OS proc set {94}
OMP: pid 55913 tid 56103 thread 92 bound to OS proc set {92}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_7 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 56128 tid 56227 thread 1 bound to OS proc set {1}
OMP: pid 56128 tid 56228 thread 2 bound to OS proc set {2}
OMP: pid 56128 tid 56229 thread 3 bound to OS proc set {3}
OMP: pid 56128 tid 56230 thread 4 bound to OS proc set {4}
OMP: pid 56128 tid 56128 thread 0 bound to OS proc set {0}
OMP: pid 56128 tid 56231 thread 5 bound to OS proc set {5}
OMP: pid 56128 tid 56232 thread 6 bound to OS proc set {6}
OMP: pid 56128 tid 56234 thread 8 bound to OS proc set {8}
OMP: pid 56128 tid 56235 thread 9 bound to OS proc set {9}
OMP: pid 56128 tid 56238 thread 12 bound to OS proc set {12}
OMP: pid 56128 tid 56236 thread 10 bound to OS proc set {10}
OMP: pid 56128 tid 56233 thread 7 bound to OS proc set {7}
OMP: pid 56128 tid 56239 thread 13 bound to OS proc set {13}
OMP: pid 56128 tid 56237 thread 11 bound to OS proc set {11}
OMP: pid 56128 tid 56240 thread 14 bound to OS proc set {14}
OMP: pid 56128 tid 56243 thread 17 bound to OS proc set {17}
OMP: pid 56128 tid 56245 thread 19 bound to OS proc set {19}
OMP: pid 56128 tid 56275 thread 49 bound to OS proc set {49}
OMP: pid 56128 tid 56241 thread 15 bound to OS proc set {15}
OMP: pid 56128 tid 56244 thread 18 bound to OS proc set {18}
OMP: pid 56128 tid 56259 thread 33 bound to OS proc set {33}
OMP: pid 56128 tid 56242 thread 16 bound to OS proc set {16}
OMP: pid 56128 tid 56277 thread 51 bound to OS proc set {51}
OMP: pid 56128 tid 56291 thread 65 bound to OS proc set {65}
OMP: pid 56128 tid 56260 thread 34 bound to OS proc set {34}
OMP: pid 56128 tid 56276 thread 50 bound to OS proc set {50}
OMP: pid 56128 tid 56246 thread 20 bound to OS proc set {20}
OMP: pid 56128 tid 56252 thread 26 bound to OS proc set {26}
OMP: pid 56128 tid 56258 thread 32 bound to OS proc set {32}
OMP: pid 56128 tid 56250 thread 24 bound to OS proc set {24}
OMP: pid 56128 tid 56247 thread 21 bound to OS proc set {21}
OMP: pid 56128 tid 56256 thread 30 bound to OS proc set {30}
OMP: pid 56128 tid 56262 thread 36 bound to OS proc set {36}
OMP: pid 56128 tid 56263 thread 37 bound to OS proc set {37}
OMP: pid 56128 tid 56251 thread 25 bound to OS proc set {25}
OMP: pid 56128 tid 56279 thread 53 bound to OS proc set {53}
OMP: pid 56128 tid 56293 thread 67 bound to OS proc set {67}
OMP: pid 56128 tid 56249 thread 23 bound to OS proc set {23}
OMP: pid 56128 tid 56253 thread 27 bound to OS proc set {27}
OMP: pid 56128 tid 56255 thread 29 bound to OS proc set {29}
OMP: pid 56128 tid 56254 thread 28 bound to OS proc set {28}
OMP: pid 56128 tid 56261 thread 35 bound to OS proc set {35}
OMP: pid 56128 tid 56280 thread 54 bound to OS proc set {54}
OMP: pid 56128 tid 56248 thread 22 bound to OS proc set {22}
OMP: pid 56128 tid 56278 thread 52 bound to OS proc set {52}
OMP: pid 56128 tid 56266 thread 40 bound to OS proc set {40}
OMP: pid 56128 tid 56292 thread 66 bound to OS proc set {66}
OMP: pid 56128 tid 56268 thread 42 bound to OS proc set {42}
OMP: pid 56128 tid 56264 thread 38 bound to OS proc set {38}
OMP: pid 56128 tid 56284 thread 58 bound to OS proc set {58}
OMP: pid 56128 tid 56282 thread 56 bound to OS proc set {56}
OMP: pid 56128 tid 56283 thread 57 bound to OS proc set {57}
OMP: pid 56128 tid 56257 thread 31 bound to OS proc set {31}
OMP: pid 56128 tid 56294 thread 68 bound to OS proc set {68}
OMP: pid 56128 tid 56296 thread 70 bound to OS proc set {70}
OMP: pid 56128 tid 56270 thread 44 bound to OS proc set {44}
OMP: pid 56128 tid 56281 thread 55 bound to OS proc set {55}
OMP: pid 56128 tid 56290 thread 64 bound to OS proc set {64}
OMP: pid 56128 tid 56271 thread 45 bound to OS proc set {45}
OMP: pid 56128 tid 56286 thread 60 bound to OS proc set {60}
OMP: pid 56128 tid 56269 thread 43 bound to OS proc set {43}
OMP: pid 56128 tid 56288 thread 62 bound to OS proc set {62}
OMP: pid 56128 tid 56287 thread 61 bound to OS proc set {61}
OMP: pid 56128 tid 56267 thread 41 bound to OS proc set {41}
OMP: pid 56128 tid 56300 thread 74 bound to OS proc set {74}
OMP: pid 56128 tid 56274 thread 48 bound to OS proc set {48}
OMP: pid 56128 tid 56304 thread 78 bound to OS proc set {78}
OMP: pid 56128 tid 56299 thread 73 bound to OS proc set {73}
OMP: pid 56128 tid 56285 thread 59 bound to OS proc set {59}
OMP: pid 56128 tid 56305 thread 79 bound to OS proc set {79}
OMP: pid 56128 tid 56307 thread 81 bound to OS proc set {81}
OMP: pid 56128 tid 56265 thread 39 bound to OS proc set {39}
OMP: pid 56128 tid 56302 thread 76 bound to OS proc set {76}
OMP: pid 56128 tid 56309 thread 83 bound to OS proc set {83}
OMP: pid 56128 tid 56297 thread 71 bound to OS proc set {71}
OMP: pid 56128 tid 56272 thread 46 bound to OS proc set {46}
OMP: pid 56128 tid 56273 thread 47 bound to OS proc set {47}
OMP: pid 56128 tid 56295 thread 69 bound to OS proc set {69}
OMP: pid 56128 tid 56298 thread 72 bound to OS proc set {72}
OMP: pid 56128 tid 56303 thread 77 bound to OS proc set {77}
OMP: pid 56128 tid 56289 thread 63 bound to OS proc set {63}
OMP: pid 56128 tid 56308 thread 82 bound to OS proc set {82}
OMP: pid 56128 tid 56306 thread 80 bound to OS proc set {80}
OMP: pid 56128 tid 56301 thread 75 bound to OS proc set {75}
OMP: pid 56128 tid 56311 thread 85 bound to OS proc set {85}
OMP: pid 56128 tid 56314 thread 88 bound to OS proc set {88}
OMP: pid 56128 tid 56312 thread 86 bound to OS proc set {86}
OMP: pid 56128 tid 56313 thread 87 bound to OS proc set {87}
OMP: pid 56128 tid 56315 thread 89 bound to OS proc set {89}
OMP: pid 56128 tid 56316 thread 90 bound to OS proc set {90}
OMP: pid 56128 tid 56318 thread 92 bound to OS proc set {92}
OMP: pid 56128 tid 56317 thread 91 bound to OS proc set {91}
OMP: pid 56128 tid 56319 thread 93 bound to OS proc set {93}
OMP: pid 56128 tid 56321 thread 95 bound to OS proc set {95}
OMP: pid 56128 tid 56320 thread 94 bound to OS proc set {94}
OMP: pid 56128 tid 56310 thread 84 bound to OS proc set {84}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_8 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 56403 tid 56504 thread 3 bound to OS proc set {3}
OMP: pid 56403 tid 56510 thread 9 bound to OS proc set {9}
OMP: pid 56403 tid 56506 thread 5 bound to OS proc set {5}
OMP: pid 56403 tid 56505 thread 4 bound to OS proc set {4}
OMP: pid 56403 tid 56507 thread 6 bound to OS proc set {6}
OMP: pid 56403 tid 56403 thread 0 bound to OS proc set {0}
OMP: pid 56403 tid 56514 thread 13 bound to OS proc set {13}
OMP: pid 56403 tid 56509 thread 8 bound to OS proc set {8}
OMP: pid 56403 tid 56508 thread 7 bound to OS proc set {7}
OMP: pid 56403 tid 56511 thread 10 bound to OS proc set {10}
OMP: pid 56403 tid 56513 thread 12 bound to OS proc set {12}
OMP: pid 56403 tid 56515 thread 14 bound to OS proc set {14}
OMP: pid 56403 tid 56518 thread 17 bound to OS proc set {17}
OMP: pid 56403 tid 56502 thread 1 bound to OS proc set {1}
OMP: pid 56403 tid 56516 thread 15 bound to OS proc set {15}
OMP: pid 56403 tid 56512 thread 11 bound to OS proc set {11}
OMP: pid 56403 tid 56519 thread 18 bound to OS proc set {18}
OMP: pid 56403 tid 56520 thread 19 bound to OS proc set {19}
OMP: pid 56403 tid 56503 thread 2 bound to OS proc set {2}
OMP: pid 56403 tid 56517 thread 16 bound to OS proc set {16}
OMP: pid 56403 tid 56534 thread 33 bound to OS proc set {33}
OMP: pid 56403 tid 56521 thread 20 bound to OS proc set {20}
OMP: pid 56403 tid 56550 thread 49 bound to OS proc set {49}
OMP: pid 56403 tid 56552 thread 51 bound to OS proc set {51}
OMP: pid 56403 tid 56536 thread 35 bound to OS proc set {35}
OMP: pid 56403 tid 56566 thread 65 bound to OS proc set {65}
OMP: pid 56403 tid 56535 thread 34 bound to OS proc set {34}
OMP: pid 56403 tid 56527 thread 26 bound to OS proc set {26}
OMP: pid 56403 tid 56567 thread 66 bound to OS proc set {66}
OMP: pid 56403 tid 56526 thread 25 bound to OS proc set {25}
OMP: pid 56403 tid 56551 thread 50 bound to OS proc set {50}
OMP: pid 56403 tid 56538 thread 37 bound to OS proc set {37}
OMP: pid 56403 tid 56537 thread 36 bound to OS proc set {36}
OMP: pid 56403 tid 56533 thread 32 bound to OS proc set {32}
OMP: pid 56403 tid 56530 thread 29 bound to OS proc set {29}
OMP: pid 56403 tid 56525 thread 24 bound to OS proc set {24}
OMP: pid 56403 tid 56522 thread 21 bound to OS proc set {21}
OMP: pid 56403 tid 56531 thread 30 bound to OS proc set {30}
OMP: pid 56403 tid 56568 thread 67 bound to OS proc set {67}
OMP: pid 56403 tid 56523 thread 22 bound to OS proc set {22}
OMP: pid 56403 tid 56541 thread 40 bound to OS proc set {40}
OMP: pid 56403 tid 56558 thread 57 bound to OS proc set {57}
OMP: pid 56403 tid 56539 thread 38 bound to OS proc set {38}
OMP: pid 56403 tid 56554 thread 53 bound to OS proc set {53}
OMP: pid 56403 tid 56529 thread 28 bound to OS proc set {28}
OMP: pid 56403 tid 56542 thread 41 bound to OS proc set {41}
OMP: pid 56403 tid 56540 thread 39 bound to OS proc set {39}
OMP: pid 56403 tid 56545 thread 44 bound to OS proc set {44}
OMP: pid 56403 tid 56546 thread 45 bound to OS proc set {45}
OMP: pid 56403 tid 56557 thread 56 bound to OS proc set {56}
OMP: pid 56403 tid 56570 thread 69 bound to OS proc set {69}
OMP: pid 56403 tid 56555 thread 54 bound to OS proc set {54}
OMP: pid 56403 tid 56559 thread 58 bound to OS proc set {58}
OMP: pid 56403 tid 56562 thread 61 bound to OS proc set {61}
OMP: pid 56403 tid 56565 thread 64 bound to OS proc set {64}
OMP: pid 56403 tid 56524 thread 23 bound to OS proc set {23}
OMP: pid 56403 tid 56549 thread 48 bound to OS proc set {48}
OMP: pid 56403 tid 56528 thread 27 bound to OS proc set {27}
OMP: pid 56403 tid 56543 thread 42 bound to OS proc set {42}
OMP: pid 56403 tid 56556 thread 55 bound to OS proc set {55}
OMP: pid 56403 tid 56578 thread 77 bound to OS proc set {77}
OMP: pid 56403 tid 56574 thread 73 bound to OS proc set {73}
OMP: pid 56403 tid 56560 thread 59 bound to OS proc set {59}
OMP: pid 56403 tid 56553 thread 52 bound to OS proc set {52}
OMP: pid 56403 tid 56532 thread 31 bound to OS proc set {31}
OMP: pid 56403 tid 56547 thread 46 bound to OS proc set {46}
OMP: pid 56403 tid 56573 thread 72 bound to OS proc set {72}
OMP: pid 56403 tid 56544 thread 43 bound to OS proc set {43}
OMP: pid 56403 tid 56548 thread 47 bound to OS proc set {47}
OMP: pid 56403 tid 56582 thread 81 bound to OS proc set {81}
OMP: pid 56403 tid 56575 thread 74 bound to OS proc set {74}
OMP: pid 56403 tid 56576 thread 75 bound to OS proc set {75}
OMP: pid 56403 tid 56579 thread 78 bound to OS proc set {78}
OMP: pid 56403 tid 56580 thread 79 bound to OS proc set {79}
OMP: pid 56403 tid 56571 thread 70 bound to OS proc set {70}
OMP: pid 56403 tid 56564 thread 63 bound to OS proc set {63}
OMP: pid 56403 tid 56583 thread 82 bound to OS proc set {82}
OMP: pid 56403 tid 56577 thread 76 bound to OS proc set {76}
OMP: pid 56403 tid 56572 thread 71 bound to OS proc set {71}
OMP: pid 56403 tid 56584 thread 83 bound to OS proc set {83}
OMP: pid 56403 tid 56561 thread 60 bound to OS proc set {60}
OMP: pid 56403 tid 56581 thread 80 bound to OS proc set {80}
OMP: pid 56403 tid 56586 thread 85 bound to OS proc set {85}
OMP: pid 56403 tid 56563 thread 62 bound to OS proc set {62}
OMP: pid 56403 tid 56590 thread 89 bound to OS proc set {89}
OMP: pid 56403 tid 56591 thread 90 bound to OS proc set {90}
OMP: pid 56403 tid 56587 thread 86 bound to OS proc set {86}
OMP: pid 56403 tid 56589 thread 88 bound to OS proc set {88}
OMP: pid 56403 tid 56585 thread 84 bound to OS proc set {84}
OMP: pid 56403 tid 56592 thread 91 bound to OS proc set {91}
OMP: pid 56403 tid 56596 thread 95 bound to OS proc set {95}
OMP: pid 56403 tid 56595 thread 94 bound to OS proc set {94}
OMP: pid 56403 tid 56588 thread 87 bound to OS proc set {87}
OMP: pid 56403 tid 56594 thread 93 bound to OS proc set {93}
OMP: pid 56403 tid 56593 thread 92 bound to OS proc set {92}
OMP: pid 56403 tid 56569 thread 68 bound to OS proc set {68}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9
To display your profiling results:
###########################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
###########################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_9 #
###########################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 56619 tid 56720 thread 3 bound to OS proc set {3}
OMP: pid 56619 tid 56721 thread 4 bound to OS proc set {4}
OMP: pid 56619 tid 56726 thread 9 bound to OS proc set {9}
OMP: pid 56619 tid 56619 thread 0 bound to OS proc set {0}
OMP: pid 56619 tid 56722 thread 5 bound to OS proc set {5}
OMP: pid 56619 tid 56723 thread 6 bound to OS proc set {6}
OMP: pid 56619 tid 56730 thread 13 bound to OS proc set {13}
OMP: pid 56619 tid 56725 thread 8 bound to OS proc set {8}
OMP: pid 56619 tid 56729 thread 12 bound to OS proc set {12}
OMP: pid 56619 tid 56727 thread 10 bound to OS proc set {10}
OMP: pid 56619 tid 56731 thread 14 bound to OS proc set {14}
OMP: pid 56619 tid 56728 thread 11 bound to OS proc set {11}
OMP: pid 56619 tid 56724 thread 7 bound to OS proc set {7}
OMP: pid 56619 tid 56734 thread 17 bound to OS proc set {17}
OMP: pid 56619 tid 56732 thread 15 bound to OS proc set {15}
OMP: pid 56619 tid 56735 thread 18 bound to OS proc set {18}
OMP: pid 56619 tid 56750 thread 33 bound to OS proc set {33}
OMP: pid 56619 tid 56718 thread 1 bound to OS proc set {1}
OMP: pid 56619 tid 56719 thread 2 bound to OS proc set {2}
OMP: pid 56619 tid 56766 thread 49 bound to OS proc set {49}
OMP: pid 56619 tid 56751 thread 34 bound to OS proc set {34}
OMP: pid 56619 tid 56752 thread 35 bound to OS proc set {35}
OMP: pid 56619 tid 56767 thread 50 bound to OS proc set {50}
OMP: pid 56619 tid 56733 thread 16 bound to OS proc set {16}
OMP: pid 56619 tid 56768 thread 51 bound to OS proc set {51}
OMP: pid 56619 tid 56782 thread 65 bound to OS proc set {65}
OMP: pid 56619 tid 56749 thread 32 bound to OS proc set {32}
OMP: pid 56619 tid 56783 thread 66 bound to OS proc set {66}
OMP: pid 56619 tid 56736 thread 19 bound to OS proc set {19}
OMP: pid 56619 tid 56739 thread 22 bound to OS proc set {22}
OMP: pid 56619 tid 56738 thread 21 bound to OS proc set {21}
OMP: pid 56619 tid 56737 thread 20 bound to OS proc set {20}
OMP: pid 56619 tid 56784 thread 67 bound to OS proc set {67}
OMP: pid 56619 tid 56765 thread 48 bound to OS proc set {48}
OMP: pid 56619 tid 56754 thread 37 bound to OS proc set {37}
OMP: pid 56619 tid 56742 thread 25 bound to OS proc set {25}
OMP: pid 56619 tid 56740 thread 23 bound to OS proc set {23}
OMP: pid 56619 tid 56746 thread 29 bound to OS proc set {29}
OMP: pid 56619 tid 56753 thread 36 bound to OS proc set {36}
OMP: pid 56619 tid 56741 thread 24 bound to OS proc set {24}
OMP: pid 56619 tid 56758 thread 41 bound to OS proc set {41}
OMP: pid 56619 tid 56755 thread 38 bound to OS proc set {38}
OMP: pid 56619 tid 56770 thread 53 bound to OS proc set {53}
OMP: pid 56619 tid 56745 thread 28 bound to OS proc set {28}
OMP: pid 56619 tid 56759 thread 42 bound to OS proc set {42}
OMP: pid 56619 tid 56744 thread 27 bound to OS proc set {27}
OMP: pid 56619 tid 56757 thread 40 bound to OS proc set {40}
OMP: pid 56619 tid 56747 thread 30 bound to OS proc set {30}
OMP: pid 56619 tid 56769 thread 52 bound to OS proc set {52}
OMP: pid 56619 tid 56756 thread 39 bound to OS proc set {39}
OMP: pid 56619 tid 56762 thread 45 bound to OS proc set {45}
OMP: pid 56619 tid 56771 thread 54 bound to OS proc set {54}
OMP: pid 56619 tid 56781 thread 64 bound to OS proc set {64}
OMP: pid 56619 tid 56748 thread 31 bound to OS proc set {31}
OMP: pid 56619 tid 56773 thread 56 bound to OS proc set {56}
OMP: pid 56619 tid 56774 thread 57 bound to OS proc set {57}
OMP: pid 56619 tid 56772 thread 55 bound to OS proc set {55}
OMP: pid 56619 tid 56761 thread 44 bound to OS proc set {44}
OMP: pid 56619 tid 56786 thread 69 bound to OS proc set {69}
OMP: pid 56619 tid 56763 thread 46 bound to OS proc set {46}
OMP: pid 56619 tid 56764 thread 47 bound to OS proc set {47}
OMP: pid 56619 tid 56760 thread 43 bound to OS proc set {43}
OMP: pid 56619 tid 56775 thread 58 bound to OS proc set {58}
OMP: pid 56619 tid 56778 thread 61 bound to OS proc set {61}
OMP: pid 56619 tid 56787 thread 70 bound to OS proc set {70}
OMP: pid 56619 tid 56776 thread 59 bound to OS proc set {59}
OMP: pid 56619 tid 56743 thread 26 bound to OS proc set {26}
OMP: pid 56619 tid 56779 thread 62 bound to OS proc set {62}
OMP: pid 56619 tid 56777 thread 60 bound to OS proc set {60}
OMP: pid 56619 tid 56785 thread 68 bound to OS proc set {68}
OMP: pid 56619 tid 56780 thread 63 bound to OS proc set {63}
OMP: pid 56619 tid 56790 thread 73 bound to OS proc set {73}
OMP: pid 56619 tid 56793 thread 76 bound to OS proc set {76}
OMP: pid 56619 tid 56792 thread 75 bound to OS proc set {75}
OMP: pid 56619 tid 56795 thread 78 bound to OS proc set {78}
OMP: pid 56619 tid 56791 thread 74 bound to OS proc set {74}
OMP: pid 56619 tid 56789 thread 72 bound to OS proc set {72}
OMP: pid 56619 tid 56798 thread 81 bound to OS proc set {81}
OMP: pid 56619 tid 56796 thread 79 bound to OS proc set {79}
OMP: pid 56619 tid 56800 thread 83 bound to OS proc set {83}
OMP: pid 56619 tid 56794 thread 77 bound to OS proc set {77}
OMP: pid 56619 tid 56797 thread 80 bound to OS proc set {80}
OMP: pid 56619 tid 56799 thread 82 bound to OS proc set {82}
OMP: pid 56619 tid 56788 thread 71 bound to OS proc set {71}
OMP: pid 56619 tid 56802 thread 85 bound to OS proc set {85}
OMP: pid 56619 tid 56801 thread 84 bound to OS proc set {84}
OMP: pid 56619 tid 56806 thread 89 bound to OS proc set {89}
OMP: pid 56619 tid 56808 thread 91 bound to OS proc set {91}
OMP: pid 56619 tid 56807 thread 90 bound to OS proc set {90}
OMP: pid 56619 tid 56811 thread 94 bound to OS proc set {94}
OMP: pid 56619 tid 56805 thread 88 bound to OS proc set {88}
OMP: pid 56619 tid 56804 thread 87 bound to OS proc set {87}
OMP: pid 56619 tid 56809 thread 92 bound to OS proc set {92}
OMP: pid 56619 tid 56803 thread 86 bound to OS proc set {86}
OMP: pid 56619 tid 56812 thread 95 bound to OS proc set {95}
OMP: pid 56619 tid 56810 thread 93 bound to OS proc set {93}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10
To display your profiling results:
############################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
############################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_10 #
############################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 56834 tid 56933 thread 1 bound to OS proc set {1}
OMP: pid 56834 tid 56934 thread 2 bound to OS proc set {2}
OMP: pid 56834 tid 56935 thread 3 bound to OS proc set {3}
OMP: pid 56834 tid 56834 thread 0 bound to OS proc set {0}
OMP: pid 56834 tid 56937 thread 5 bound to OS proc set {5}
OMP: pid 56834 tid 56938 thread 6 bound to OS proc set {6}
OMP: pid 56834 tid 56944 thread 12 bound to OS proc set {12}
OMP: pid 56834 tid 56941 thread 9 bound to OS proc set {9}
OMP: pid 56834 tid 56942 thread 10 bound to OS proc set {10}
OMP: pid 56834 tid 56946 thread 14 bound to OS proc set {14}
OMP: pid 56834 tid 56949 thread 17 bound to OS proc set {17}
OMP: pid 56834 tid 56936 thread 4 bound to OS proc set {4}
OMP: pid 56834 tid 56945 thread 13 bound to OS proc set {13}
OMP: pid 56834 tid 56943 thread 11 bound to OS proc set {11}
OMP: pid 56834 tid 56947 thread 15 bound to OS proc set {15}
OMP: pid 56834 tid 56940 thread 8 bound to OS proc set {8}
OMP: pid 56834 tid 56950 thread 18 bound to OS proc set {18}
OMP: pid 56834 tid 56965 thread 33 bound to OS proc set {33}
OMP: pid 56834 tid 56981 thread 49 bound to OS proc set {49}
OMP: pid 56834 tid 56951 thread 19 bound to OS proc set {19}
OMP: pid 56834 tid 56982 thread 50 bound to OS proc set {50}
OMP: pid 56834 tid 56966 thread 34 bound to OS proc set {34}
OMP: pid 56834 tid 56948 thread 16 bound to OS proc set {16}
OMP: pid 56834 tid 56997 thread 65 bound to OS proc set {65}
OMP: pid 56834 tid 56967 thread 35 bound to OS proc set {35}
OMP: pid 56834 tid 56953 thread 21 bound to OS proc set {21}
OMP: pid 56834 tid 56952 thread 20 bound to OS proc set {20}
OMP: pid 56834 tid 56998 thread 66 bound to OS proc set {66}
OMP: pid 56834 tid 56983 thread 51 bound to OS proc set {51}
OMP: pid 56834 tid 56957 thread 25 bound to OS proc set {25}
OMP: pid 56834 tid 56954 thread 22 bound to OS proc set {22}
OMP: pid 56834 tid 56964 thread 32 bound to OS proc set {32}
OMP: pid 56834 tid 56960 thread 28 bound to OS proc set {28}
OMP: pid 56834 tid 56955 thread 23 bound to OS proc set {23}
OMP: pid 56834 tid 56956 thread 24 bound to OS proc set {24}
OMP: pid 56834 tid 56968 thread 36 bound to OS proc set {36}
OMP: pid 56834 tid 56970 thread 38 bound to OS proc set {38}
OMP: pid 56834 tid 56973 thread 41 bound to OS proc set {41}
OMP: pid 56834 tid 56962 thread 30 bound to OS proc set {30}
OMP: pid 56834 tid 56961 thread 29 bound to OS proc set {29}
OMP: pid 56834 tid 56985 thread 53 bound to OS proc set {53}
OMP: pid 56834 tid 56980 thread 48 bound to OS proc set {48}
OMP: pid 56834 tid 56999 thread 67 bound to OS proc set {67}
OMP: pid 56834 tid 56959 thread 27 bound to OS proc set {27}
OMP: pid 56834 tid 56977 thread 45 bound to OS proc set {45}
OMP: pid 56834 tid 56969 thread 37 bound to OS proc set {37}
OMP: pid 56834 tid 56972 thread 40 bound to OS proc set {40}
OMP: pid 56834 tid 56976 thread 44 bound to OS proc set {44}
OMP: pid 56834 tid 56984 thread 52 bound to OS proc set {52}
OMP: pid 56834 tid 56978 thread 46 bound to OS proc set {46}
OMP: pid 56834 tid 56989 thread 57 bound to OS proc set {57}
OMP: pid 56834 tid 56958 thread 26 bound to OS proc set {26}
OMP: pid 56834 tid 56974 thread 42 bound to OS proc set {42}
OMP: pid 56834 tid 56988 thread 56 bound to OS proc set {56}
OMP: pid 56834 tid 56986 thread 54 bound to OS proc set {54}
OMP: pid 56834 tid 56996 thread 64 bound to OS proc set {64}
OMP: pid 56834 tid 56963 thread 31 bound to OS proc set {31}
OMP: pid 56834 tid 56975 thread 43 bound to OS proc set {43}
OMP: pid 56834 tid 57005 thread 73 bound to OS proc set {73}
OMP: pid 56834 tid 57002 thread 70 bound to OS proc set {70}
OMP: pid 56834 tid 56971 thread 39 bound to OS proc set {39}
OMP: pid 56834 tid 56994 thread 62 bound to OS proc set {62}
OMP: pid 56834 tid 56991 thread 59 bound to OS proc set {59}
OMP: pid 56834 tid 56993 thread 61 bound to OS proc set {61}
OMP: pid 56834 tid 56990 thread 58 bound to OS proc set {58}
OMP: pid 56834 tid 56992 thread 60 bound to OS proc set {60}
OMP: pid 56834 tid 57009 thread 77 bound to OS proc set {77}
OMP: pid 56834 tid 57008 thread 76 bound to OS proc set {76}
OMP: pid 56834 tid 57004 thread 72 bound to OS proc set {72}
OMP: pid 56834 tid 57013 thread 81 bound to OS proc set {81}
OMP: pid 56834 tid 57006 thread 74 bound to OS proc set {74}
OMP: pid 56834 tid 57010 thread 78 bound to OS proc set {78}
OMP: pid 56834 tid 56939 thread 7 bound to OS proc set {7}
OMP: pid 56834 tid 57014 thread 82 bound to OS proc set {82}
OMP: pid 56834 tid 57011 thread 79 bound to OS proc set {79}
OMP: pid 56834 tid 57007 thread 75 bound to OS proc set {75}
OMP: pid 56834 tid 56995 thread 63 bound to OS proc set {63}
OMP: pid 56834 tid 56987 thread 55 bound to OS proc set {55}
OMP: pid 56834 tid 57015 thread 83 bound to OS proc set {83}
OMP: pid 56834 tid 57012 thread 80 bound to OS proc set {80}
OMP: pid 56834 tid 57000 thread 68 bound to OS proc set {68}
OMP: pid 56834 tid 56979 thread 47 bound to OS proc set {47}
OMP: pid 56834 tid 57001 thread 69 bound to OS proc set {69}
OMP: pid 56834 tid 57017 thread 85 bound to OS proc set {85}
OMP: pid 56834 tid 57016 thread 84 bound to OS proc set {84}
OMP: pid 56834 tid 57022 thread 90 bound to OS proc set {90}
OMP: pid 56834 tid 57020 thread 88 bound to OS proc set {88}
OMP: pid 56834 tid 57025 thread 93 bound to OS proc set {93}
OMP: pid 56834 tid 57023 thread 91 bound to OS proc set {91}
OMP: pid 56834 tid 57021 thread 89 bound to OS proc set {89}
OMP: pid 56834 tid 57018 thread 86 bound to OS proc set {86}
OMP: pid 56834 tid 57024 thread 92 bound to OS proc set {92}
OMP: pid 56834 tid 57019 thread 87 bound to OS proc set {87}
OMP: pid 56834 tid 57026 thread 94 bound to OS proc set {94}
OMP: pid 56834 tid 57003 thread 71 bound to OS proc set {71}
OMP: pid 56834 tid 57027 thread 95 bound to OS proc set {95}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11
To display your profiling results:
############################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
############################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_11 #
############################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 57111 tid 57212 thread 3 bound to OS proc set {3}
OMP: pid 57111 tid 57210 thread 1 bound to OS proc set {1}
OMP: pid 57111 tid 57211 thread 2 bound to OS proc set {2}
OMP: pid 57111 tid 57111 thread 0 bound to OS proc set {0}
OMP: pid 57111 tid 57218 thread 9 bound to OS proc set {9}
OMP: pid 57111 tid 57215 thread 6 bound to OS proc set {6}
OMP: pid 57111 tid 57213 thread 4 bound to OS proc set {4}
OMP: pid 57111 tid 57214 thread 5 bound to OS proc set {5}
OMP: pid 57111 tid 57223 thread 14 bound to OS proc set {14}
OMP: pid 57111 tid 57222 thread 13 bound to OS proc set {13}
OMP: pid 57111 tid 57216 thread 7 bound to OS proc set {7}
OMP: pid 57111 tid 57221 thread 12 bound to OS proc set {12}
OMP: pid 57111 tid 57217 thread 8 bound to OS proc set {8}
OMP: pid 57111 tid 57220 thread 11 bound to OS proc set {11}
OMP: pid 57111 tid 57226 thread 17 bound to OS proc set {17}
OMP: pid 57111 tid 57242 thread 33 bound to OS proc set {33}
OMP: pid 57111 tid 57224 thread 15 bound to OS proc set {15}
OMP: pid 57111 tid 57228 thread 19 bound to OS proc set {19}
OMP: pid 57111 tid 57243 thread 34 bound to OS proc set {34}
OMP: pid 57111 tid 57258 thread 49 bound to OS proc set {49}
OMP: pid 57111 tid 57225 thread 16 bound to OS proc set {16}
OMP: pid 57111 tid 57227 thread 18 bound to OS proc set {18}
OMP: pid 57111 tid 57259 thread 50 bound to OS proc set {50}
OMP: pid 57111 tid 57274 thread 65 bound to OS proc set {65}
OMP: pid 57111 tid 57230 thread 21 bound to OS proc set {21}
OMP: pid 57111 tid 57275 thread 66 bound to OS proc set {66}
OMP: pid 57111 tid 57229 thread 20 bound to OS proc set {20}
OMP: pid 57111 tid 57244 thread 35 bound to OS proc set {35}
OMP: pid 57111 tid 57241 thread 32 bound to OS proc set {32}
OMP: pid 57111 tid 57238 thread 29 bound to OS proc set {29}
OMP: pid 57111 tid 57235 thread 26 bound to OS proc set {26}
OMP: pid 57111 tid 57231 thread 22 bound to OS proc set {22}
OMP: pid 57111 tid 57246 thread 37 bound to OS proc set {37}
OMP: pid 57111 tid 57234 thread 25 bound to OS proc set {25}
OMP: pid 57111 tid 57233 thread 24 bound to OS proc set {24}
OMP: pid 57111 tid 57250 thread 41 bound to OS proc set {41}
OMP: pid 57111 tid 57260 thread 51 bound to OS proc set {51}
OMP: pid 57111 tid 57245 thread 36 bound to OS proc set {36}
OMP: pid 57111 tid 57232 thread 23 bound to OS proc set {23}
OMP: pid 57111 tid 57257 thread 48 bound to OS proc set {48}
OMP: pid 57111 tid 57247 thread 38 bound to OS proc set {38}
OMP: pid 57111 tid 57262 thread 53 bound to OS proc set {53}
OMP: pid 57111 tid 57254 thread 45 bound to OS proc set {45}
OMP: pid 57111 tid 57261 thread 52 bound to OS proc set {52}
OMP: pid 57111 tid 57276 thread 67 bound to OS proc set {67}
OMP: pid 57111 tid 57237 thread 28 bound to OS proc set {28}
OMP: pid 57111 tid 57256 thread 47 bound to OS proc set {47}
OMP: pid 57111 tid 57236 thread 27 bound to OS proc set {27}
OMP: pid 57111 tid 57266 thread 57 bound to OS proc set {57}
OMP: pid 57111 tid 57249 thread 40 bound to OS proc set {40}
OMP: pid 57111 tid 57253 thread 44 bound to OS proc set {44}
OMP: pid 57111 tid 57270 thread 61 bound to OS proc set {61}
OMP: pid 57111 tid 57273 thread 64 bound to OS proc set {64}
OMP: pid 57111 tid 57268 thread 59 bound to OS proc set {59}
OMP: pid 57111 tid 57251 thread 42 bound to OS proc set {42}
OMP: pid 57111 tid 57278 thread 69 bound to OS proc set {69}
OMP: pid 57111 tid 57267 thread 58 bound to OS proc set {58}
OMP: pid 57111 tid 57282 thread 73 bound to OS proc set {73}
OMP: pid 57111 tid 57265 thread 56 bound to OS proc set {56}
OMP: pid 57111 tid 57290 thread 81 bound to OS proc set {81}
OMP: pid 57111 tid 57252 thread 43 bound to OS proc set {43}
OMP: pid 57111 tid 57240 thread 31 bound to OS proc set {31}
OMP: pid 57111 tid 57264 thread 55 bound to OS proc set {55}
OMP: pid 57111 tid 57219 thread 10 bound to OS proc set {10}
OMP: pid 57111 tid 57285 thread 76 bound to OS proc set {76}
OMP: pid 57111 tid 57277 thread 68 bound to OS proc set {68}
OMP: pid 57111 tid 57263 thread 54 bound to OS proc set {54}
OMP: pid 57111 tid 57279 thread 70 bound to OS proc set {70}
OMP: pid 57111 tid 57281 thread 72 bound to OS proc set {72}
OMP: pid 57111 tid 57255 thread 46 bound to OS proc set {46}
OMP: pid 57111 tid 57291 thread 82 bound to OS proc set {82}
OMP: pid 57111 tid 57271 thread 62 bound to OS proc set {62}
OMP: pid 57111 tid 57248 thread 39 bound to OS proc set {39}
OMP: pid 57111 tid 57280 thread 71 bound to OS proc set {71}
OMP: pid 57111 tid 57272 thread 63 bound to OS proc set {63}
OMP: pid 57111 tid 57239 thread 30 bound to OS proc set {30}
OMP: pid 57111 tid 57287 thread 78 bound to OS proc set {78}
OMP: pid 57111 tid 57286 thread 77 bound to OS proc set {77}
OMP: pid 57111 tid 57283 thread 74 bound to OS proc set {74}
OMP: pid 57111 tid 57288 thread 79 bound to OS proc set {79}
OMP: pid 57111 tid 57294 thread 85 bound to OS proc set {85}
OMP: pid 57111 tid 57269 thread 60 bound to OS proc set {60}
OMP: pid 57111 tid 57284 thread 75 bound to OS proc set {75}
OMP: pid 57111 tid 57289 thread 80 bound to OS proc set {80}
OMP: pid 57111 tid 57292 thread 83 bound to OS proc set {83}
OMP: pid 57111 tid 57298 thread 89 bound to OS proc set {89}
OMP: pid 57111 tid 57293 thread 84 bound to OS proc set {84}
OMP: pid 57111 tid 57297 thread 88 bound to OS proc set {88}
OMP: pid 57111 tid 57299 thread 90 bound to OS proc set {90}
OMP: pid 57111 tid 57296 thread 87 bound to OS proc set {87}
OMP: pid 57111 tid 57300 thread 91 bound to OS proc set {91}
OMP: pid 57111 tid 57301 thread 92 bound to OS proc set {92}
OMP: pid 57111 tid 57302 thread 93 bound to OS proc set {93}
OMP: pid 57111 tid 57303 thread 94 bound to OS proc set {94}
OMP: pid 57111 tid 57304 thread 95 bound to OS proc set {95}
OMP: pid 57111 tid 57295 thread 86 bound to OS proc set {86}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12
To display your profiling results:
############################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
############################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_12 #
############################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 57328 tid 57427 thread 1 bound to OS proc set {1}
OMP: pid 57328 tid 57428 thread 2 bound to OS proc set {2}
OMP: pid 57328 tid 57429 thread 3 bound to OS proc set {3}
OMP: pid 57328 tid 57328 thread 0 bound to OS proc set {0}
OMP: pid 57328 tid 57432 thread 6 bound to OS proc set {6}
OMP: pid 57328 tid 57430 thread 4 bound to OS proc set {4}
OMP: pid 57328 tid 57431 thread 5 bound to OS proc set {5}
OMP: pid 57328 tid 57435 thread 9 bound to OS proc set {9}
OMP: pid 57328 tid 57433 thread 7 bound to OS proc set {7}
OMP: pid 57328 tid 57443 thread 17 bound to OS proc set {17}
OMP: pid 57328 tid 57436 thread 10 bound to OS proc set {10}
OMP: pid 57328 tid 57438 thread 12 bound to OS proc set {12}
OMP: pid 57328 tid 57439 thread 13 bound to OS proc set {13}
OMP: pid 57328 tid 57437 thread 11 bound to OS proc set {11}
OMP: pid 57328 tid 57444 thread 18 bound to OS proc set {18}
OMP: pid 57328 tid 57434 thread 8 bound to OS proc set {8}
OMP: pid 57328 tid 57459 thread 33 bound to OS proc set {33}
OMP: pid 57328 tid 57441 thread 15 bound to OS proc set {15}
OMP: pid 57328 tid 57475 thread 49 bound to OS proc set {49}
OMP: pid 57328 tid 57460 thread 34 bound to OS proc set {34}
OMP: pid 57328 tid 57445 thread 19 bound to OS proc set {19}
OMP: pid 57328 tid 57442 thread 16 bound to OS proc set {16}
OMP: pid 57328 tid 57476 thread 50 bound to OS proc set {50}
OMP: pid 57328 tid 57461 thread 35 bound to OS proc set {35}
OMP: pid 57328 tid 57447 thread 21 bound to OS proc set {21}
OMP: pid 57328 tid 57446 thread 20 bound to OS proc set {20}
OMP: pid 57328 tid 57491 thread 65 bound to OS proc set {65}
OMP: pid 57328 tid 57492 thread 66 bound to OS proc set {66}
OMP: pid 57328 tid 57477 thread 51 bound to OS proc set {51}
OMP: pid 57328 tid 57451 thread 25 bound to OS proc set {25}
OMP: pid 57328 tid 57455 thread 29 bound to OS proc set {29}
OMP: pid 57328 tid 57458 thread 32 bound to OS proc set {32}
OMP: pid 57328 tid 57452 thread 26 bound to OS proc set {26}
OMP: pid 57328 tid 57450 thread 24 bound to OS proc set {24}
OMP: pid 57328 tid 57449 thread 23 bound to OS proc set {23}
OMP: pid 57328 tid 57467 thread 41 bound to OS proc set {41}
OMP: pid 57328 tid 57453 thread 27 bound to OS proc set {27}
OMP: pid 57328 tid 57464 thread 38 bound to OS proc set {38}
OMP: pid 57328 tid 57454 thread 28 bound to OS proc set {28}
OMP: pid 57328 tid 57468 thread 42 bound to OS proc set {42}
OMP: pid 57328 tid 57474 thread 48 bound to OS proc set {48}
OMP: pid 57328 tid 57462 thread 36 bound to OS proc set {36}
OMP: pid 57328 tid 57440 thread 14 bound to OS proc set {14}
OMP: pid 57328 tid 57466 thread 40 bound to OS proc set {40}
OMP: pid 57328 tid 57472 thread 46 bound to OS proc set {46}
OMP: pid 57328 tid 57465 thread 39 bound to OS proc set {39}
OMP: pid 57328 tid 57470 thread 44 bound to OS proc set {44}
OMP: pid 57328 tid 57473 thread 47 bound to OS proc set {47}
OMP: pid 57328 tid 57456 thread 30 bound to OS proc set {30}
OMP: pid 57328 tid 57469 thread 43 bound to OS proc set {43}
OMP: pid 57328 tid 57487 thread 61 bound to OS proc set {61}
OMP: pid 57328 tid 57463 thread 37 bound to OS proc set {37}
OMP: pid 57328 tid 57457 thread 31 bound to OS proc set {31}
OMP: pid 57328 tid 57482 thread 56 bound to OS proc set {56}
OMP: pid 57328 tid 57490 thread 64 bound to OS proc set {64}
OMP: pid 57328 tid 57493 thread 67 bound to OS proc set {67}
OMP: pid 57328 tid 57478 thread 52 bound to OS proc set {52}
OMP: pid 57328 tid 57494 thread 68 bound to OS proc set {68}
OMP: pid 57328 tid 57485 thread 59 bound to OS proc set {59}
OMP: pid 57328 tid 57448 thread 22 bound to OS proc set {22}
OMP: pid 57328 tid 57486 thread 60 bound to OS proc set {60}
OMP: pid 57328 tid 57479 thread 53 bound to OS proc set {53}
OMP: pid 57328 tid 57488 thread 62 bound to OS proc set {62}
OMP: pid 57328 tid 57503 thread 77 bound to OS proc set {77}
OMP: pid 57328 tid 57499 thread 73 bound to OS proc set {73}
OMP: pid 57328 tid 57483 thread 57 bound to OS proc set {57}
OMP: pid 57328 tid 57484 thread 58 bound to OS proc set {58}
OMP: pid 57328 tid 57481 thread 55 bound to OS proc set {55}
OMP: pid 57328 tid 57498 thread 72 bound to OS proc set {72}
OMP: pid 57328 tid 57480 thread 54 bound to OS proc set {54}
OMP: pid 57328 tid 57507 thread 81 bound to OS proc set {81}
OMP: pid 57328 tid 57495 thread 69 bound to OS proc set {69}
OMP: pid 57328 tid 57501 thread 75 bound to OS proc set {75}
OMP: pid 57328 tid 57504 thread 78 bound to OS proc set {78}
OMP: pid 57328 tid 57505 thread 79 bound to OS proc set {79}
OMP: pid 57328 tid 57489 thread 63 bound to OS proc set {63}
OMP: pid 57328 tid 57508 thread 82 bound to OS proc set {82}
OMP: pid 57328 tid 57496 thread 70 bound to OS proc set {70}
OMP: pid 57328 tid 57471 thread 45 bound to OS proc set {45}
OMP: pid 57328 tid 57502 thread 76 bound to OS proc set {76}
OMP: pid 57328 tid 57509 thread 83 bound to OS proc set {83}
OMP: pid 57328 tid 57511 thread 85 bound to OS proc set {85}
OMP: pid 57328 tid 57510 thread 84 bound to OS proc set {84}
OMP: pid 57328 tid 57515 thread 89 bound to OS proc set {89}
OMP: pid 57328 tid 57512 thread 86 bound to OS proc set {86}
OMP: pid 57328 tid 57497 thread 71 bound to OS proc set {71}
OMP: pid 57328 tid 57520 thread 94 bound to OS proc set {94}
OMP: pid 57328 tid 57506 thread 80 bound to OS proc set {80}
OMP: pid 57328 tid 57514 thread 88 bound to OS proc set {88}
OMP: pid 57328 tid 57519 thread 93 bound to OS proc set {93}
OMP: pid 57328 tid 57517 thread 91 bound to OS proc set {91}
OMP: pid 57328 tid 57516 thread 90 bound to OS proc set {90}
OMP: pid 57328 tid 57518 thread 92 bound to OS proc set {92}
OMP: pid 57328 tid 57500 thread 74 bound to OS proc set {74}
OMP: pid 57328 tid 57513 thread 87 bound to OS proc set {87}
OMP: pid 57328 tid 57521 thread 95 bound to OS proc set {95}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13
To display your profiling results:
############################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
############################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_13 #
############################################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in ip-172-31-47-249.ec2.internal.
If this is incorrect, rerun with number-processes-per-node=X
[0mOMP: pid 57543 tid 57644 thread 3 bound to OS proc set {3}
OMP: pid 57543 tid 57642 thread 1 bound to OS proc set {1}
OMP: pid 57543 tid 57643 thread 2 bound to OS proc set {2}
OMP: pid 57543 tid 57645 thread 4 bound to OS proc set {4}
OMP: pid 57543 tid 57646 thread 5 bound to OS proc set {5}
OMP: pid 57543 tid 57543 thread 0 bound to OS proc set {0}
OMP: pid 57543 tid 57650 thread 9 bound to OS proc set {9}
OMP: pid 57543 tid 57647 thread 6 bound to OS proc set {6}
OMP: pid 57543 tid 57654 thread 13 bound to OS proc set {13}
OMP: pid 57543 tid 57648 thread 7 bound to OS proc set {7}
OMP: pid 57543 tid 57653 thread 12 bound to OS proc set {12}
OMP: pid 57543 tid 57649 thread 8 bound to OS proc set {8}
OMP: pid 57543 tid 57658 thread 17 bound to OS proc set {17}
OMP: pid 57543 tid 57651 thread 10 bound to OS proc set {10}
OMP: pid 57543 tid 57655 thread 14 bound to OS proc set {14}
OMP: pid 57543 tid 57652 thread 11 bound to OS proc set {11}
OMP: pid 57543 tid 57659 thread 18 bound to OS proc set {18}
OMP: pid 57543 tid 57674 thread 33 bound to OS proc set {33}
OMP: pid 57543 tid 57656 thread 15 bound to OS proc set {15}
OMP: pid 57543 tid 57690 thread 49 bound to OS proc set {49}
OMP: pid 57543 tid 57660 thread 19 bound to OS proc set {19}
OMP: pid 57543 tid 57675 thread 34 bound to OS proc set {34}
OMP: pid 57543 tid 57691 thread 50 bound to OS proc set {50}
OMP: pid 57543 tid 57676 thread 35 bound to OS proc set {35}
OMP: pid 57543 tid 57692 thread 51 bound to OS proc set {51}
OMP: pid 57543 tid 57706 thread 65 bound to OS proc set {65}
OMP: pid 57543 tid 57673 thread 32 bound to OS proc set {32}
OMP: pid 57543 tid 57657 thread 16 bound to OS proc set {16}
OMP: pid 57543 tid 57689 thread 48 bound to OS proc set {48}
OMP: pid 57543 tid 57661 thread 20 bound to OS proc set {20}
OMP: pid 57543 tid 57707 thread 66 bound to OS proc set {66}
OMP: pid 57543 tid 57662 thread 21 bound to OS proc set {21}
OMP: pid 57543 tid 57663 thread 22 bound to OS proc set {22}
OMP: pid 57543 tid 57666 thread 25 bound to OS proc set {25}
OMP: pid 57543 tid 57708 thread 67 bound to OS proc set {67}
OMP: pid 57543 tid 57665 thread 24 bound to OS proc set {24}
OMP: pid 57543 tid 57664 thread 23 bound to OS proc set {23}
OMP: pid 57543 tid 57670 thread 29 bound to OS proc set {29}
OMP: pid 57543 tid 57667 thread 26 bound to OS proc set {26}
OMP: pid 57543 tid 57678 thread 37 bound to OS proc set {37}
OMP: pid 57543 tid 57694 thread 53 bound to OS proc set {53}
OMP: pid 57543 tid 57682 thread 41 bound to OS proc set {41}
OMP: pid 57543 tid 57677 thread 36 bound to OS proc set {36}
OMP: pid 57543 tid 57669 thread 28 bound to OS proc set {28}
OMP: pid 57543 tid 57671 thread 30 bound to OS proc set {30}
OMP: pid 57543 tid 57668 thread 27 bound to OS proc set {27}
OMP: pid 57543 tid 57679 thread 38 bound to OS proc set {38}
OMP: pid 57543 tid 57686 thread 45 bound to OS proc set {45}
OMP: pid 57543 tid 57681 thread 40 bound to OS proc set {40}
OMP: pid 57543 tid 57683 thread 42 bound to OS proc set {42}
OMP: pid 57543 tid 57693 thread 52 bound to OS proc set {52}
OMP: pid 57543 tid 57680 thread 39 bound to OS proc set {39}
OMP: pid 57543 tid 57685 thread 44 bound to OS proc set {44}
OMP: pid 57543 tid 57698 thread 57 bound to OS proc set {57}
OMP: pid 57543 tid 57672 thread 31 bound to OS proc set {31}
OMP: pid 57543 tid 57687 thread 46 bound to OS proc set {46}
OMP: pid 57543 tid 57688 thread 47 bound to OS proc set {47}
OMP: pid 57543 tid 57699 thread 58 bound to OS proc set {58}
OMP: pid 57543 tid 57697 thread 56 bound to OS proc set {56}
OMP: pid 57543 tid 57702 thread 61 bound to OS proc set {61}
OMP: pid 57543 tid 57684 thread 43 bound to OS proc set {43}
OMP: pid 57543 tid 57710 thread 69 bound to OS proc set {69}
OMP: pid 57543 tid 57705 thread 64 bound to OS proc set {64}
OMP: pid 57543 tid 57714 thread 73 bound to OS proc set {73}
OMP: pid 57543 tid 57709 thread 68 bound to OS proc set {68}
OMP: pid 57543 tid 57700 thread 59 bound to OS proc set {59}
OMP: pid 57543 tid 57711 thread 70 bound to OS proc set {70}
OMP: pid 57543 tid 57713 thread 72 bound to OS proc set {72}
OMP: pid 57543 tid 57701 thread 60 bound to OS proc set {60}
OMP: pid 57543 tid 57712 thread 71 bound to OS proc set {71}
OMP: pid 57543 tid 57703 thread 62 bound to OS proc set {62}
OMP: pid 57543 tid 57696 thread 55 bound to OS proc set {55}
OMP: pid 57543 tid 57695 thread 54 bound to OS proc set {54}
OMP: pid 57543 tid 57704 thread 63 bound to OS proc set {63}
OMP: pid 57543 tid 57717 thread 76 bound to OS proc set {76}
OMP: pid 57543 tid 57715 thread 74 bound to OS proc set {74}
OMP: pid 57543 tid 57719 thread 78 bound to OS proc set {78}
OMP: pid 57543 tid 57720 thread 79 bound to OS proc set {79}
OMP: pid 57543 tid 57718 thread 77 bound to OS proc set {77}
OMP: pid 57543 tid 57723 thread 82 bound to OS proc set {82}
OMP: pid 57543 tid 57722 thread 81 bound to OS proc set {81}
OMP: pid 57543 tid 57721 thread 80 bound to OS proc set {80}
OMP: pid 57543 tid 57724 thread 83 bound to OS proc set {83}
OMP: pid 57543 tid 57716 thread 75 bound to OS proc set {75}
OMP: pid 57543 tid 57736 thread 95 bound to OS proc set {95}
OMP: pid 57543 tid 57733 thread 92 bound to OS proc set {92}
OMP: pid 57543 tid 57732 thread 91 bound to OS proc set {91}
OMP: pid 57543 tid 57731 thread 90 bound to OS proc set {90}
OMP: pid 57543 tid 57726 thread 85 bound to OS proc set {85}
OMP: pid 57543 tid 57728 thread 87 bound to OS proc set {87}
OMP: pid 57543 tid 57727 thread 86 bound to OS proc set {86}
OMP: pid 57543 tid 57725 thread 84 bound to OS proc set {84}
OMP: pid 57543 tid 57734 thread 93 bound to OS proc set {93}
OMP: pid 57543 tid 57730 thread 89 bound to OS proc set {89}
OMP: pid 57543 tid 57729 thread 88 bound to OS proc set {88}
OMP: pid 57543 tid 57735 thread 94 bound to OS proc set {94}
what is a LLM? and why it matters
A Large Language Model (LLM) is a type of artificial intelligence (AI) that uses machine learning to generate human-like language. It’s a software program that can understand, analyze, and respond to natural language inputs, such as text or speech.
LLMs are trained on vast amounts of text data, which allows them to learn patterns and relationships between words, phrases, and ideas. This training enables them to generate coherent and contextually relevant text, making them useful for various applications, including:
1. Virtual assistants: LLMs can power virtual assistants like Siri, Google Assistant, and Alexa, enabling them to understand and respond to voice commands.
2. Text summarization: LLMs can summarize long pieces of text into concise, relevant summaries, saving users time and effort.
3. Content generation: LLMs can generate original content, such as articles, product descriptions, or even entire books, based on a given topic or style.
4. Language translation: LLMs can translate text from one language to another, helping to break language barriers and facilitate global communication.
5. Chatbots: LLMs can power chatbots that provide customer support, answer frequently asked questions, and engage users in conversations.
6. Research and analysis: LLMs can aid researchers and analysts by providing insights, identifying patterns, and generating reports based on large datasets.
LLMs matter because they have the potential to revolutionize the way we interact with information and each other. They can:
1. Automate repetitive tasks: LLMs can free up human time and effort by automating tasks such as data entry, content moderation, and language translation.
2. Enhance customer experience: By providing personalized and contextually relevant responses, LLMs can improve customer satisfaction and loyalty.
3. Unlock new forms of creativity: LLMs can generate new ideas, concepts, and content, opening up new possibilities for artistic expression, scientific discovery, and innovation.
4. Enable more effective communication: LLMs can facilitate better understanding and collaboration across languages, cultures, and domains, bridging the gap between people and ideas.
However, LLMs also raise concerns about:
1. Bias and accuracy: LLMs can perpetuate biases and inaccuracies present in the training data, potentially leading to misleading or harmful outputs.
2. Job displacement: As LLMs automate tasks, they may displace human workers, particularly in industries where repetitive or routine tasks are prevalent.
3. Security and control: LLMs can be
Your experiment path is /home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14
To display your profiling results:
############################################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
############################################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Functions | Per-node | maqao lprof -df -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Functions | Per-process | maqao lprof -df -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Functions | Per-thread | maqao lprof -df -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Loops | Cluster-wide | maqao lprof -dl xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Loops | Per-node | maqao lprof -dl -dn xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Loops | Per-process | maqao lprof -dl -dp xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/home/eoseret/Tools/QaaS/qaas_runs/ip-172-31-47-249.ec2.internal/175-768-9528/llama.cpp/run/oneview_runs/multicore/armclang_3/oneview_results_1757691803/tools/lprof_npsu_run_14 #
############################################################################################################################################################################################################################################
