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[ 4 / 4 ] Application profile is long enough (127.77 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 0.07 % 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 (42.39%)
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
No hotspot found in the application (greatest loop coverage is 3.51%), but the twenty hottest loops cumulated coverage is representative enough (28.08% > 20%)
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (34.10%)
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.
[ 0 / 3 ] More than 10% (20.04%) is spend in BLAS1 operations
It could be more efficient to inline by hand BLAS1 operations
[ 3 / 3 ] Cumulative Outermost/In between loops coverage (8.29%) lower than cumulative innermost loop coverage (34.1%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.79%) is spend in Libm/SVML (special functions)
[ 0 / 2 ] More than 10% (21.14%) is spend in BLAS2 operations
BLAS2 calls usually make a poor cache usage. Try blocking. Such calls should probably benefit from inlining. Such inlining will have to be hand made.
| Loop ID | Module | Analysis | Penalty Score | Coverage (%) | Vectorization Ratio (%) | Vector Length Use (%) |
|---|---|---|---|---|---|---|
| ►2687 | exec | Inefficient vectorization. | 93 | 3.51 | 100 | 43.27 |
| ○ | [SA] Presence of expensive instructions (GATHER/SCATTER) - Use array restructuring. There are 20 issues (= instructions) costing 4 points each. | 80 | ||||
| ○ | [DA] Low iteration count (4 < 10) - Perform full unroll. Use compiler pragmas. Use PGO/FDO compiler options. Force compiler to use masked instructions. This issue costs 5 points. | 5 | ||||
| ○ | [SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points. | 4 | ||||
| ○ | [SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points. | 2 | ||||
| ○ | [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 | ||||
| ►3224 | exec | Inefficient vectorization. | 2 | 2.87 | 100 | 50 |
| ○ | [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 | ||||
| ►3140 | exec | Inefficient vectorization. | 2 | 2.01 | 100 | 50 |
| ○ | [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 | ||||
| ►3357 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 21 | 1.97 | 7.14 | 12.95 |
| ○ | [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 10 issues ( = data accesses) costing 2 point each. | 20 | ||||
| ○ | [SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 1 issues (= calls) costing 1 point each. | 1 | ||||
| ►2686 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 10 | 1.96 | 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 5 issues ( = data accesses) costing 2 point each. | 10 | ||||
| ►4419 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 360 | 1.86 | 90.2 | 41.5 |
| ○ | [SA] Presence of special instructions executing on a single port (INSERT/EXTRACT, SHUFFLE/PERM, BROADCAST) - Simplify data access and try to get stride 1 access. There are 135 issues (= instructions) costing 1 point each. | 135 | ||||
| ○ | [SA] Presence of expensive instructions (GATHER/SCATTER) - Use array restructuring. There are 32 issues (= instructions) costing 4 points each. | 128 | ||||
| ○ | [SA] Large loop body: over microp cache size - Perform loop splitting or reduce unrolling. There are 38 issues (= chunks of 50 instructions) costing 2 point each. | 76 | ||||
| ○ | [SA] Too many paths (5 paths) - Simplify control structure. There are 5 issues ( = paths) costing 1 point each with a malus of 4 points. | 9 | ||||
| ○ | [SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points. | 4 | ||||
| ○ | [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 | ||||
| ○ | [SA] Bottleneck in the front end - If loop size is very small (rare occurrences), perform unroll and jam. If loop size is large, perform loop splitting. This issue costs 2 points. | 2 | ||||
| ○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points. | 2 | ||||
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ○ | Warning! Some static analysis are missing because the loop has too many paths. Use a higher value for --maximal_path_number option. | 0 | ||||
| ►2680 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 10 | 1.54 | 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 5 issues ( = data accesses) costing 2 point each. | 10 | ||||
| ►2424 | exec | Inefficient vectorization. | 4 | 1.53 | 100 | 50 |
| ○ | [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 | ||||
| ○ | [SA] Presence of a large number of scalar integer instructions - Simplify loop structure, perform loop splitting or perform unroll and jam. This issue costs 2 points. | 2 | ||||
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►2572 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 12 | 1.3 | 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 4 issues ( = data accesses) costing 2 point each. | 8 | ||||
| ○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 1 issues ( = indirect data accesses) costing 4 point each. | 4 | ||||
| ○4629 | exec | Partial or unexisting vectorization - No issue detected | 0 | 1.26 | 0 | 6.25 |