Help is available by moving the cursor above any 
symbol or by checking MAQAO website.
[ 4 / 4 ] Application profile is long enough (202.96 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.
[ 3.00 / 3 ] Architecture specific option -march=znver4 is used
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 1.46 % 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 (47.42%)
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% (27.82%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (47.10%)
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.
[ 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 (0.32%) lower than cumulative innermost loop coverage (47.1%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.03%) 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 (%) |
|---|---|---|---|---|---|---|
| ►830 | exec | The loop is fully and efficiently vectorized. | 0 | 27.82 | 100 | 100 |
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►895 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 7.56 | 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 1 issues ( = data accesses) costing 2 point each. | 2 | ||||
| ○2748 | exec | Partial or unexisting vectorization - No issue detected | 0 | 5.41 | 12 | 14 |
| ►2304 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 30 | 1.51 | 27.27 | 15.91 |
| ○ | [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 15 issues ( = data accesses) costing 2 point each. | 30 | ||||
| ►351 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 1.25 | 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 | ||||
| ►985 | exec | The loop is fully and efficiently vectorized. | 0 | 0.39 | 100 | 100 |
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►899 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 10 | 0.39 | 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 | ||||
| ►582 | exec | The loop is fully and efficiently vectorized. | 0 | 0.31 | 100 | 100 |
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►990 | exec | Inefficient vectorization. | 24 | 0.31 | 100 | 100 |
| ○ | [SA] Presence of special instructions executing on a single port (SHUFFLE/PERM) - Simplify data access and try to get stride 1 access. There are 24 issues (= instructions) costing 1 point each. | 24 | ||||
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►894 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 36 | 0.26 | 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 18 issues ( = data accesses) costing 2 point each. | 36 |