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exec - 2025-11-25 18:58:09 - MAQAO 2025.1.3

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Stylizer  

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 4 / 4 ] Application profile is long enough (13.59 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 2 / 3 ] Security settings from the host restrict profiling. Some metrics will be missing or incomplete.

Current value for kernel.perf_event_paranoid is 2. If possible, set it to 1 or check with your system administrator which flag can be used to achieve this.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % of the execution time)

To have a representative profiling, it is advised that the category "Others" represents less than 20% of the execution time in order to analyze as much as possible of the user code

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

Strategizer  

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (0.75%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 3 / 4 ] A significant amount of threads are idle (20.17%)

On average, more than 10% of observed threads are idle. Such threads are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 3 / 4 ] CPU activity is below 90% (84.14%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.25%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (0.75%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (0.69%)

If the time spent in analyzed innermost loops is less than 15%, standard innermost loop optimizations such as vectorisation will have a limited impact on application performances.

[ 4 / 4 ] Affinity is good (98.68%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (12.87%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.06%) lower than cumulative innermost loop coverage (0.69%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.04%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 2447 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 56.25 % - Vector Length Use: 68.36 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Data Access Issues+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Vectorization Roadblocks+4
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 2 issues ( = data accesses) costing 2 point each.4
Loop 2450 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 10.53 % - Vector Length Use: 49.34 %
Data Access Issues+8
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 4 issues ( = data accesses) costing 2 point each.8
Vectorization Roadblocks+8
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 4 issues ( = data accesses) costing 2 point each.8
Loop 1565 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 0.00 % - Vector Length Use: 26.34 %
Loop Computation Issues+8
[SA] Presence of expensive FP instructions - Perform hoisting, change algorithm, use SVML or proper numerical library or perform value profiling (count the number of distinct input values). There are 1 issues (= instructions) costing 4 points each.4
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
Control Flow Issues+1
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
Data Access Issues+2
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 1 issues ( = data accesses) costing 2 point each.2
Vectorization Roadblocks+3
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 1 issues ( = data accesses) costing 2 point each.2
Loop 1015 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 68.18 % - Vector Length Use: 82.24 %
Loop Computation Issues+4
[SA] Presence of expensive FP instructions - Perform hoisting, change algorithm, use SVML or proper numerical library or perform value profiling (count the number of distinct input values). There are 1 issues (= instructions) costing 4 points each.4
Loop 1892 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 17.17 % - Vector Length Use: 53.87 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+3
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Vectorization Roadblocks+1003
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
[SA] Too many paths (at least 1000 paths) - Simplify control structure. There are at least 1000 issues ( = paths) costing 1 point.1000
[SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 1398 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 96.97 % - Vector Length Use: 98.48 %
Loop Computation Issues+4
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
Loop 1895 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 16.49 % - Vector Length Use: 50.02 %
Loop Computation Issues+2
[SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points.2
Control Flow Issues+3
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
[SA] Non innermost loop (Outermost) - Collapse loop with innermost ones. This issue costs 2 points.2
Vectorization Roadblocks+1003
[SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each.1
[SA] Too many paths (at least 1000 paths) - Simplify control structure. There are at least 1000 issues ( = paths) costing 1 point.1000
[SA] Non innermost loop (Outermost) - Collapse loop with innermost ones. This issue costs 2 points.2
Loop 434 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 0.00 % - Vector Length Use: 25.00 %
Loop Computation Issues+4
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
Data Access Issues+6
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 3 issues ( = data accesses) costing 2 point each.6
Vectorization Roadblocks+6
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 3 issues ( = data accesses) costing 2 point each.6
Loop 1007 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 100.00 % - Vector Length Use: 100.00 %
Data Access Issues+28
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 14 issues ( = data accesses) costing 2 point each.28
Vectorization Roadblocks+28
[SA] Presence of constant non unit stride data access - Use array restructuring, perform loop interchange or use gather instructions to lower a bit the cost. There are 14 issues ( = data accesses) costing 2 point each.28
Loop 0 - libggml-cpu.so+Execution Time: 0 % - Vectorization Ratio: 92.50 % - Vector Length Use: 98.75 %
Loop Computation Issues+4
[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
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