Help is available by moving the cursor above any 
symbol or by checking MAQAO website.
[ 4 / 4 ] Application profile is long enough (34.96 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 3 / 3 ] Optimization level option is correctly used
[ 3 / 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 improves the accuracy of callchains found during the application profiling.
[ 3 / 3 ] Architecture specific option -march=znver4 is used
[ 0 / 2 ] Too much execution time spent in category "Others" (37.76 %)
If the category "Others" represents more than 20% of the execution time, it means that the application profile misses a representative part of the application.Examine functions details to properly identify “Others” category components.Rerun after adding most represented library names (e.g. more than 20% of coverage) to external_libraries (the names can be directly provided by ONE View)
[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (0.06%)
If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.
[ 0 / 4 ] Loop profile is flat
No hotspot found in the application (greatest loop coverage is 0.04%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (0.06%)
[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (0.01%)
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
[ 0 / 3 ] Cumulative Outermost/In between loops coverage (0.05%) greater than cumulative innermost loop coverage (0.01%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.05%) is spend in Libm/SVML (special functions)
[ 2 / 2 ] Less than 10% (0.02%) 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 (%) |
|---|---|---|---|---|---|---|
| ►39 | exec | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 23 | 0.04 | 0 | 11.74 |
| ○ | [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 | ||||
| ○ | [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 | ||||
| ○ | [SA] Several paths (3 paths) - Simplify control structure or force the compiler to use masked instructions. There are 3 issues ( = paths) costing 1 point each. | 3 | ||||
| ○ | [SA] Non innermost loop (InBetween) - Collapse loop with innermost ones. This issue costs 2 points. | 2 |