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bench_jastrow - 2024-02-12 13:27:34 - MAQAO 2.19.0

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▼Stylizer  

[ 4 / 4 ] Application profile is long enough (40.39 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 2.64 / 3 ] Optimization level option is correctly used

[ 2.64 / 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.

[ 2.64 / 3 ] Architecture specific option -march=native 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

▼Strategizer  

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (13.28%)

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% (7.60%), representing an hotspot for the application

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (12.70%)

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 (0.58%) lower than cumulative innermost loop coverage (12.7%)

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%) 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.

▼Optimizer

Loop IDModuleAnalysisPenalty ScoreCoverage (%)Vectorization
Ratio (%)
Vector Length
Use (%)
►292libqmckl.so.0.0.0Inefficient vectorization.67.610050
○[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
○[SA] More than 20% of the loads are accessing the stack - Perform loop splitting to decrease pressure on registers. This issue costs 2 points.2
○Warning! There is no dynamic data for this loop. Some checks can not been performed.0
►259libqmckl.so.0.0.0Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.81.845018.75
○[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
►1059libqmckl.so.0.0.0Inefficient vectorization.20.5410050
○[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
►958libqmckl.so.0.0.0Inefficient vectorization.520.5110046.67
○[SA] Presence of expensive FP instructions - Perform hoisting, change algorithm, use SVML or proper numerical library or perform value profiling (count the number of distinct input values). There are 8 issues (= instructions) costing 4 points each.32
○[SA] Presence of expensive instructions (GATHER/SCATTER) - Use array restructuring. There are 4 issues (= instructions) costing 4 points each.16
○[SA] More than 20% of the loads are accessing the stack - Perform loop splitting to decrease pressure on registers. This issue costs 2 points.2
○[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
►36bench_jastrowInefficient vectorization.20.4710050
○[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
►268libqmckl.so.0.0.0Inefficient vectorization.60.4210050
○[SA] Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA - Reorganize arithmetic expressions to exhibit potential for FMA. This issue costs 4 points.4
○[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
►229libqmckl.so.0.0.0Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access.1120.3620.7915.41
○[SA] Too many paths (106 paths) - Simplify control structure. There are 106 issues ( = paths) costing 1 point each with a malus of 4 points.110
○[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
►263libqmckl.so.0.0.0Inefficient vectorization.20.1710050
○[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
►1139libqmckl.so.0.0.0Inefficient vectorization.20.1610050
○[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
►1101libqmckl.so.0.0.0Inefficient vectorization.20.1510050
○[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
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