Help is available by moving the cursor above any 
symbol or by checking MAQAO website.
[ 4 / 4 ] Application profile is long enough (111.16 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=haswell is used
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.04 % 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 (67.79%)
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% (22.46%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (67.64%)
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 (0.15%) lower than cumulative innermost loop coverage (67.64%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.01%) is spend in Libm/SVML (special functions)
[ 2 / 2 ] Less than 10% (2.23%) 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 (%) |
|---|---|---|---|---|---|---|
| ○559 | libqmcwfs.so | Partial or unexisting vectorization - No issue detected | 0 | 22.46 | 0 | 12.5 |
| ►563 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 17.68 | 27.66 | 17.55 |
| ○ | [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 | ||||
| ○377 | libqmcparticle_omptarget.so | Partial or unexisting vectorization - No issue detected | 0 | 8.52 | 12.24 | 14.03 |
| ►224 | libqmcparticle_omptarget.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 34 | 6.84 | 20 | 15 |
| ○ | [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 | ||||
| ○ | [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 | ||||
| ○445 | libqmcparticle_omptarget.so | Partial or unexisting vectorization - No issue detected | 0 | 1.67 | 73.13 | 39.93 |
| ►398 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 4 | 1.42 | 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 | ||||
| ►504 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1000 | 1.35 | 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 | ||||
| ►565 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 10 | 0.96 | 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 | ||||
| ○562 | libqmcwfs.so | Partial or unexisting vectorization - No issue detected | 0 | 0.9 | 0 | 12.5 |
| ►401 | libqmcwfs.so | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 0.9 | 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 |