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[ 0 / 4 ] Application profile is too short (4.43 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.
[ 3.00 / 3 ] Optimization level option is correctly used
[ 2.40 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information
Functions without compilation information (typically not compiled with -g) cumulate 0.00% 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.
[ 3.00 / 3 ] Architecture specific option -xop 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 (83.92%)
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% (51.55%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (79.43%)
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 (4.49%) lower than cumulative innermost loop coverage (79.43%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.86%) 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 (%) |
|---|---|---|---|---|---|---|
| ►214 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 51.55 | 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 | ||||
| ►208 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 22.24 | 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 | ||||
| ►210 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 4 | 1.55 | 20.51 | 15.06 |
| ○ | [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 | ||||
| ►27 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1006 | 1.09 | 16.88 | 14.17 |
| ○ | [SA] Too many paths (53849 paths) - Simplify control structure. There are 53849 issues ( = paths) costing 1 point, limited to 1000. | 1000 | ||||
| ○ | [SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 4 issues (= calls) costing 1 point each. | 4 | ||||
| ○ | [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 | ||||
| ►212 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 1.08 | 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 | ||||
| ►213 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 14 | 0.86 | 21.39 | 15.14 |
| ○ | [SA] Too many paths (8 paths) - Simplify control structure. There are 8 issues ( = paths) costing 1 point each with a malus of 4 points. | 12 | ||||
| ○ | [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 | ||||
| ►201 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 0.83 | 0 | 12.5 |
| ○ | [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 | ||||
| ►29 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 48 | 0.76 | 43.14 | 20.1 |
| ○ | [SA] Too many paths (42 paths) - Simplify control structure. There are 42 issues ( = paths) costing 1 point each with a malus of 4 points. | 46 | ||||
| ○ | [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 | ||||
| ►11 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1006 | 0.69 | 15.7 | 13.55 |
| ○ | [SA] Too many paths (15689 paths) - Simplify control structure. There are 15689 issues ( = paths) costing 1 point, limited to 1000. | 1000 | ||||
| ○ | [SA] Presence of calls - Inline either by compiler or by hand and use SVML for libm calls. There are 4 issues (= calls) costing 1 point each. | 4 | ||||
| ○ | [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 | ||||
| ►203 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.52 | 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 |