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exec - 2024-01-23 21:38:34 - MAQAO 2.19.0

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Stylizer  

[ 4 / 4 ] Application profile is long enough (123.58 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 0.05 % 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

Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (43.65%)

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 2.97%), but the twenty hottest loops cumulated coverage is representative enough (29.27% > 20%)

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (35.91%)

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% (20.53%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (7.74%) lower than cumulative innermost loop coverage (35.91%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.83%) is spend in Libm/SVML (special functions)

[ 0 / 2 ] More than 10% (21.61%) 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.

Optimizer

Loop IDModuleAnalysisPenalty ScoreCoverage (%)Vectorization
Ratio (%)
Vector Length
Use (%)
3162execInefficient vectorization.22.9710050
[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
2654execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.122.72012.5
[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 6 issues ( = data accesses) costing 2 point each.12
2653execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.162.31012.5
[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 8 issues ( = data accesses) costing 2 point each.16
3085execInefficient vectorization.22.0710050
[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
3293execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.212.027.6912.98
[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
2563execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.141.6673.520.51
[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
[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
2399execInefficient vectorization.41.5910050
[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
2649execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.121.58012.5
[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
4303execPartial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.141.57011.86
[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
4552execPartial or unexisting vectorization - No issue detected01.3406.25
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