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[ 0 / 4 ] Application profile is too short (1.37 s)
If the overall application profiling time is less than 10 seconds, many of the measurements at function or loop level will very likely be under the measurement quality threshold (0,1 seconds). Rerun to increase runtime duration: for example use a larger dataset or include a repetition loop.
[ 0 / 3 ] Optimization level option not used
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 ] No compilation options found for the main module
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 1.1 % 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 (92.00%)
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% (52.75%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (92.00%)
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 (92%)
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% (1.1%) 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 (%) |
---|---|---|---|---|---|---|
►167 | libqmcparticle.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 4 | 52.75 | 0.9 | 12.33 |
○ | [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 | ||||
○ | [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 | ||||
►557 | libqmcwfs.so | Inefficient vectorization. | 10 | 14.65 | 100 | 100 |
○ | [DA] Ratio time (ORIG)/time (DL1) is greater than 3 (9.64) - Perform blocking. Perform array restructuring. There are 0 issues (= non unit stride or indirect memory access) costing 2 point each, with an additional malus of 10 points due to the ORIG/DL1 ratio. | 10 | ||||
○ | [DA] Low iteration count (12 < 30) - Perform full unroll. Use compiler pragmas. Use PGO/FDO compiler options. Force compiler to use masked instructions. | 0 | ||||
►561 | libqmcwfs.so | Inefficient vectorization. | 8 | 8.79 | 100 | 100 |
○ | [DA] Ratio time (ORIG)/time (DL1) is greater than 3 (5.30) - Perform blocking. Perform array restructuring. There are 1 issues (= non unit stride or indirect memory access) costing 2 point each, with an additional malus of 6 points due to the ORIG/DL1 ratio. | 8 | ||||
►373 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 4 | 2.2 | 0 | 12.5 |
○ | [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 2 issues ( = data accesses) costing 2 point each. | 4 | ||||
►339 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 2.2 | 0 | 10 |
○ | [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 | ||||
○61 | libqmcwfs.so | Partial or unexisting vectorization - No issue detected | 0 | 1.83 | 0 | 12.5 |
►563 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 10 | 1.47 | 11.11 | 13.89 |
○ | [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 5 issues ( = data accesses) costing 2 point each. | 10 | ||||
►340 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 1.1 | 0 | 12.5 |
○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 2 issues ( = indirect data accesses) costing 4 point each. | 8 | ||||
►376 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 12 | 1.1 | 0 | 12.5 |
○ | [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 | ||||
►369 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 1.1 | 0 | 9.38 |
○ | [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 |