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[ 4 / 4 ] Application profile is long enough (164.51 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 3.00 / 3 ] Optimization level option is correctly 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 ] 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 (52.08%)
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% (18.75%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (51.81%)
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 (0.27%) lower than cumulative innermost loop coverage (51.81%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.01%) 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 (%) |
---|---|---|---|---|---|---|
►1141 | exec | The loop is fully and efficiently vectorized. | 0 | 18.75 | 100 | 100 |
○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
○1183 | exec | Partial or unexisting vectorization - No issue detected | 0 | 11.84 | 0 | 25 |
○3289 | exec | Partial or unexisting vectorization - No issue detected | 0 | 8.86 | 0 | 25 |
○4214 | exec | Partial or unexisting vectorization - No issue detected | 0 | 5.23 | 0 | 25 |
►394 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 1.2 | 0 | 18.95 |
○ | [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 | ||||
►1442 | exec | Inefficient vectorization. | 2 | 0.8 | 100 | 80 |
○ | [SA] Inefficient vectorization: use of shorter than available vector length - Force compiler to use proper vector length. CAUTION: use of 512 bits vectors could be more expensive than 256 bits on some processors. Use intrinsics (costly and not portable). The issue costs 2 points. | 2 | ||||
○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
○3457 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.63 | 65.57 | 77.87 |
○3456 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.6 | 65.57 | 77.87 |
►699 | exec | The loop is fully and efficiently vectorized. | 0 | 0.49 | 100 | 100 |
○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
○1179 | exec | Partial or unexisting vectorization - No issue detected | 0 | 0.48 | 0 | 25 |