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[ 4 / 4 ] Application profile is long enough (666.22 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.
[ 0 / 3 ] Compilation of some functions is not optimized for the target processor
-march=x86-64 option is used but it is not specific enough to produce efficient code. Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).
[ 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 (61.32%)
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% (7.09%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (42.44%)
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 (18.88%) lower than cumulative innermost loop coverage (42.44%)
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 (%) |
|---|---|---|---|---|---|---|
| ►3384 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 7.09 | 11.56 | 8.42 |
| ○ | [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 | ||||
| ►3370 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 6.67 | 11.56 | 8.42 |
| ○ | [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 | ||||
| ►3371 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 6.31 | 10.98 | 8.31 |
| ○ | [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 | ||||
| ►3385 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 6.3 | 10.98 | 8.31 |
| ○ | [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 | ||||
| ►1401 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1002 | 6.26 | 31.36 | 12.14 |
| ○ | [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 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►888 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1002 | 5.96 | 30.86 | 12.07 |
| ○ | [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 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►1414 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 22 | 3.57 | 19.42 | 9.89 |
| ○ | [SA] Too many paths (18 paths) - Simplify control structure. There are 18 issues ( = paths) costing 1 point each with a malus of 4 points. | 22 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►1397 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1002 | 3.36 | 23.21 | 10.6 |
| ○ | [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 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►891 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 3.03 | 17.86 | 9.6 |
| ○ | [SA] Too many paths (at least 1000 paths) - Simplify control structure. There are at least 1000 issues ( = paths) costing 1 point. | 1000 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►1403 | picongpu | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 3.03 | 19.15 | 9.81 |
| ○ | [SA] Too many paths (at least 1000 paths) - Simplify control structure. There are at least 1000 issues ( = paths) costing 1 point. | 1000 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 |