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[ 4 / 4 ] Application profile is long enough (62.95 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 3 / 3 ] Optimization level option -O2 is used
To have better performances, it is advised to help the compiler by using a proper optimization level (-O2)
[ 3 / 3 ] Helper debug compilation options -g and -fno-omit-frame-pointer are used
-g option gives access to debugging informations, such are source locations and -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling.
[ 3 / 3 ] Architecture specific option -mcpu is used
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0 % 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
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (63.47%)
If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.
[ 4 / 4 ] Loop profile is not flat
At least one loop coverage is greater than 4% (29.97%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (63.28%)
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%) is spend in BLAS1 operations
It could be more efficient to inline by hand BLAS1 operations
[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.19%) lower than cumulative innermost loop coverage (63.28%)
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%) is spend in Libm/SVML (special functions)
[ 2 / 2 ] Less than 10% (0%) is spend in BLAS2 operations
BLAS2 calls usually could make a poor cache usage and could benefit from inlining.
| Loop ID | Module | Analysis | Penalty Score | Coverage (%) | Vectorization Ratio (%) | Vector Length Use (%) |
|---|---|---|---|---|---|---|
| ○1213 | exec | Partial or unexisting vectorization - No issue detected | 0 | 29.97 | 35.14 | 33.45 |
| ►755 | exec | The loop is fully and efficiently vectorized. | 0 | 9.85 | 100 | 100 |
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►812 | exec | The loop is fully and efficiently vectorized. | 0 | 7.47 | 100 | 100 |
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ○1205 | exec | Partial or unexisting vectorization - No issue detected | 0 | 6.28 | 35.14 | 33.45 |
| ○1249 | exec | Partial or unexisting vectorization - No issue detected | 0 | 2.07 | 28.95 | 32.24 |
| ○1207 | exec | Partial or unexisting vectorization - No issue detected | 0 | 1.19 | 38.89 | 34.38 |
| ►322 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 0.83 | 0 | 19.17 |
| ○ | [SA] Too many paths (6561 paths) - Simplify control structure. There are 6561 issues ( = paths) costing 1 point, limited to 1000. | 1000 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ○642 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.74 | 0 | 25 |
| ○1242 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.43 | 28.95 | 32.24 |
| ○903 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.41 | 0 | 25 |