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[ 4 / 4 ] Application profile is long enough (58.79 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)
To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.
[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information
Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present. Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.
[ 0 / 3 ] Compilation of some functions is not optimized for the target processor
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 (93.86%)
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% (6.21%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (93.86%)
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 (0.00%) lower than cumulative innermost loop coverage (93.86%)
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 (%) |
|---|---|---|---|---|---|---|
| ►194 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 160 | 6.21 | 36.27 | 21.89 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 37 issues ( = indirect data accesses) costing 4 point each. | 148 | ||||
| ○ | [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 6 issues ( = data accesses) costing 2 point each. | 12 | ||||
| ►153 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 114 | 5.23 | 36.36 | 21.85 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 28 issues ( = indirect data accesses) costing 4 point each. | 112 | ||||
| ○ | [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 | ||||
| ►161 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 44 | 5.18 | 36.84 | 31.58 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 11 issues ( = indirect data accesses) costing 4 point each. | 44 | ||||
| ►182 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 162 | 5.15 | 30.77 | 20.09 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 37 issues ( = indirect data accesses) costing 4 point each. | 148 | ||||
| ○ | [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 7 issues ( = data accesses) costing 2 point each. | 14 | ||||
| ►335 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 106 | 4.21 | 41.28 | 33.43 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 26 issues ( = indirect data accesses) costing 4 point each. | 104 | ||||
| ○ | [SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each. | 2 | ||||
| ►293 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 106 | 4.14 | 40.72 | 32.79 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 26 issues ( = indirect data accesses) costing 4 point each. | 104 | ||||
| ○ | [SA] Several paths (2 paths) - Simplify control structure or force the compiler to use masked instructions. There are 2 issues ( = paths) costing 1 point each. | 2 | ||||
| ►164 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 60 | 4.07 | 36.22 | 21.75 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 15 issues ( = indirect data accesses) costing 4 point each. | 60 | ||||
| ►342 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 64 | 4.07 | 35.58 | 21.27 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 16 issues ( = indirect data accesses) costing 4 point each. | 64 | ||||
| ►308 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 64 | 4.07 | 34.95 | 21 |
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 16 issues ( = indirect data accesses) costing 4 point each. | 64 | ||||
| ►295 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 20 | 3.36 | 47.47 | 35.2 |
| ○ | [SA] Too many paths (16 paths) - Simplify control structure. There are 16 issues ( = paths) costing 1 point each with a malus of 4 points. | 20 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 |