| aocc_10 | gcc_9 | icx_10 |
|---|---|---|
[ 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. |
[ 3.00 / 3 ] Architecture specific option -march=znver is used | [ 3.00 / 3 ] Architecture specific option -march=znver is used | [ 3.00 / 3 ] Architecture specific option -axCORE is used |
[ 3.00 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g and -fno-omit-frame-pointer -g option gives access to debugging informations, such are source locations. -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling. | [ 3.00 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g and -fno-omit-frame-pointer -g option gives access to debugging informations, such are source locations. -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling. | [ 3.00 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g and -fno-omit-frame-pointer -g option gives access to debugging informations, such are source locations. -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling. |
[ 4 / 4 ] Application profile is long enough (18.29 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 (14.96 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 (24.21 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. |
[ 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 |
[ 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. |
| aocc_10 | gcc_9 | icx_10 |
|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 99.49% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 96.31% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 99.67% of time |
[ 4 / 4 ] Affinity is good (99.75%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.21%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.78%) Threads are not migrating to CPU cores: probably successfully pinned |
[ 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 (10.12%). 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 ] Functions mostly use all threads Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (8.88%) | [ 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 (6.39%) |
[ 0 / 3 ] Cumulative Outermost/In between loops coverage (57.60%) greater than cumulative innermost loop coverage (33.87%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (85.49%) greater than cumulative innermost loop coverage (9.48%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (87.93%) greater than cumulative innermost loop coverage (5.77%) 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 97.20% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 93.62% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 97.95% 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. |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (33.87%) 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. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (9.48%) 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. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (5.77%) 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 |
[ 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% (57.45%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (84.87%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (87.82%), representing an hotspot for the application |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (91.47%) 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 (94.96%) 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 (93.71%) 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 | |
|---|---|---|---|---|
| Loop Computation Issues | Presence of expensive FP instructions | 1 | 2 | 1 |
| Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 0 | 0 | 6 | |
| Presence of a large number of scalar integer instructions | 1 | 1 | 2 | |
| Control Flow Issues | Presence of 2 to 4 paths | 2 | 1 | 1 |
| Presence of more than 4 paths | 0 | 4 | 3 | |
| Non-innermost loop | 2 | 5 | 4 | |
| Data Access Issues | Presence of constant non-unit stride data access | 4 | 1 | 2 |
| Presence of indirect access | 4 | 0 | 2 | |
| More than 20% of the loads are accessing the stack | 3 | 2 | 5 | |
| Vectorization Roadblocks | Presence of 2 to 4 paths | 2 | 1 | 1 |
| Presence of more than 4 paths | 0 | 4 | 3 | |
| Non-innermost loop | 2 | 5 | 4 | |
| Presence of constant non-unit stride data access | 4 | 1 | 2 | |
| Presence of indirect access | 4 | 0 | 2 | |