| orig_default | gcc_default | armclang_3 | gcc_3 |
|---|---|---|---|
[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics. | [ 3 / 3 ] Host configuration allows retrieval of all necessary metrics. | [ 3 / 3 ] Host configuration allows retrieval of all necessary metrics. | [ 3 / 3 ] Host configuration allows retrieval of all necessary metrics. |
[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info -g option gives access to debugging informations, such are source locations. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info -g option gives access to debugging informations, such are source locations. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info -g option gives access to debugging informations, such are source locations. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info -g option gives access to debugging informations, such are source locations. |
[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present -fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present -fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present -fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling. | [ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present -fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling. |
[ 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 | [ 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 | [ 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 | [ 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 |
[ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used |
[ 3.00 / 3 ] Most of time spent in analyzed modules (99.97%) comes from functions compiled with architecture specialization option -mcpu | [ 3.00 / 3 ] Most of time spent in analyzed modules (99.99%) comes from functions compiled with architecture specialization option -mcpu | [ 3.00 / 3 ] Most of time spent in analyzed modules (99.97%) comes from functions compiled with architecture specialization option -mcpu | [ 3.00 / 3 ] Most of time spent in analyzed modules (99.99%) comes from functions compiled with architecture specialization option -mcpu |
[ 4 / 4 ] Application profile is long enough (87.56 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. | [ 4 / 4 ] Application profile is long enough (80.61 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. | [ 4 / 4 ] Application profile is long enough (84.97 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. | [ 4 / 4 ] Application profile is long enough (79.31 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. |
[ 0 / 0 ] Fastmath not used Consider to add ffast-math to compilation flags (or replace -O3 with -Ofast) to unlock potential extra speedup by relaxing floating-point computation consistency. Warning: floating-point accuracy may be reduced and the compliance to IEEE/ISO rules/specifications for math functions will be relaxed, typically 'errno' will no longer be set after calling some math functions. | [ 0 / 0 ] Fastmath not used Consider to add ffast-math to compilation flags (or replace -O3 with -Ofast) to unlock potential extra speedup by relaxing floating-point computation consistency. Warning: floating-point accuracy may be reduced and the compliance to IEEE/ISO rules/specifications for math functions will be relaxed, typically 'errno' will no longer be set after calling some math functions. | Not available for this run | Not available for this run |
[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. | [ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. | [ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. | [ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. |
| orig_default | gcc_default | armclang_3 | gcc_3 |
|---|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 96.25% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 95.82% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 96.12% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 95.73% of time |
[ 4 / 4 ] Affinity is good (96.51%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (97.39%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (96.36%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (97.31%) Threads are not migrating to CPU cores: probably successfully pinned |
[ 3 / 3 ] Functions mostly use all threads Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (5.79%) | [ 3 / 3 ] Functions mostly use all threads Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (4.50%) | [ 3 / 3 ] Functions mostly use all threads Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (5.67%) | [ 3 / 3 ] Functions mostly use all threads Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (4.51%) |
[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.00%) lower than cumulative innermost loop coverage (92.21%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.04%) lower than cumulative innermost loop coverage (97.13%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.57%) lower than cumulative innermost loop coverage (93.53%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.06%) lower than cumulative innermost loop coverage (97.08%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex |
[ 4 / 4 ] Threads activity is good On average, more than 96.21% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 95.79% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 96.06% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 95.69% of observed threads are actually active |
[ 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% (0.00%) is spend in BLAS2 operations BLAS2 calls usually could make a poor cache usage and could benefit from inlining. | [ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations BLAS2 calls usually could make a poor cache usage and could benefit from inlining. | [ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations BLAS2 calls usually could make a poor cache usage and could benefit from inlining. |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (92.21%) 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 ] Enough time of the experiment time spent in analyzed innermost loops (97.13%) 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 ] Enough time of the experiment time spent in analyzed innermost loops (93.53%) 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 ] Enough time of the experiment time spent in analyzed innermost loops (97.08%) 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. |
[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations It could be more efficient to inline by hand BLAS1 operations | [ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations It could be more efficient to inline by hand BLAS1 operations | [ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations It could be more efficient to inline by hand BLAS1 operations | [ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations It could be more efficient to inline by hand BLAS1 operations |
[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions) |
[ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (6.77%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (7.71%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (6.85%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (7.88%), representing an hotspot for the application |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (92.21%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (97.18%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (94.11%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (97.14%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. |
| Analysis | r0 | r1 | r2 | r3 | |
|---|---|---|---|---|---|
| Loop Computation Issues | Presence of expensive FP instructions | 9 | 9 | 9 | 9 |
| Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 3 | 1 | 2 | 2 | |
| Presence of a large number of scalar integer instructions | 0 | 1 | 10 | 1 | |
| Control Flow Issues | Presence of calls | 0 | 1 | 0 | 0 |
| Presence of 2 to 4 paths | 0 | 1 | 0 | 1 | |
| Data Access Issues | Presence of constant non-unit stride data access | 10 | 10 | 8 | 9 |
| Presence of indirect access | 10 | 3 | 0 | 1 | |
| Vectorization Roadblocks | Presence of calls | 0 | 1 | 0 | 0 |
| Presence of 2 to 4 paths | 0 | 1 | 0 | 1 | |
| Presence of more than 4 paths | 0 | 0 | 2 | 0 | |
| Presence of constant non-unit stride data access | 10 | 10 | 8 | 9 | |
| Presence of indirect access | 10 | 3 | 0 | 1 | |