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[ 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
[ 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.
Loop ID | Module | Analysis | Penalty Score | Coverage (%) | Vectorization Ratio (%) | Vector Length Use (%) |
---|---|---|---|---|---|---|
►292 | libqmckl.so.0.0.0 | Inefficient vectorization. | 6 | 7.6 | 100 | 50 |
○ | [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 | ||||
►259 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 1.84 | 50 | 18.75 |
○ | [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 | ||||
►1059 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.54 | 100 | 50 |
○ | [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 | ||||
►958 | libqmckl.so.0.0.0 | Inefficient vectorization. | 52 | 0.51 | 100 | 46.67 |
○ | [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 | ||||
►36 | bench_jastrow | Inefficient vectorization. | 2 | 0.47 | 100 | 50 |
○ | [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 | ||||
►268 | libqmckl.so.0.0.0 | Inefficient vectorization. | 6 | 0.42 | 100 | 50 |
○ | [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 | ||||
►229 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 112 | 0.36 | 20.79 | 15.41 |
○ | [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 | ||||
►263 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.17 | 100 | 50 |
○ | [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 | ||||
►1139 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.16 | 100 | 50 |
○ | [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 | ||||
►1101 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.15 | 100 | 50 |
○ | [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 |