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[ 4 / 4 ] Application profile is long enough (34.91 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 3 / 3 ] Optimization level option -O2 is used
To have better performances, it is advised to help the compiler by using a proper optimization level (-O2)
[ 3 / 3 ] Helper debug compilation options -g and -fno-omit-frame-pointer are used
-g option gives access to debugging informations, such are source locations and -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling.
[ 3 / 3 ] Architecture specific option -march=native is used
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.34 % 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 (87.21%)
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% (47.89%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (87.07%)
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 (0.14%) lower than cumulative innermost loop coverage (87.07%)
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% (1.06%) 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 (%) |
---|---|---|---|---|---|---|
►745 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 108 | 47.89 | 90.53 | 39.08 |
○ | [SA] Presence of expensive instructions (GATHER/SCATTER) - Use array restructuring. There are 16 issues (= instructions) costing 4 points each. | 64 | ||||
○ | [DA] Ratio time (ORIG)/time (DL1) is greater than 3 (12.76) - Perform blocking. Perform array restructuring. There are 3 issues (= non unit stride or indirect memory access) costing 2 point each, with an additional malus of 13 points due to the ORIG/DL1 ratio. | 19 | ||||
○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 3 issues ( = indirect data accesses) costing 4 point each. | 12 | ||||
○ | [SA] Presence of special instructions executing on a single port (INSERT/EXTRACT, SHUFFLE/PERM, BROADCAST) - Simplify data access and try to get stride 1 access. There are 9 issues (= instructions) costing 1 point each. | 9 | ||||
○ | [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 | ||||
○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.08) - Focus on optimizing data accesses. | 0 | ||||
►805 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 28.15 | 74.47 | 31.38 |
○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 2 issues ( = indirect data accesses) costing 4 point each. | 8 | ||||
►1466 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 14 | 4.2 | 54.55 | 15.91 |
○ | [SA] Presence of indirect accesses - Use array restructuring or gather instructions to lower the cost. There are 2 issues ( = indirect data accesses) costing 4 point each. | 8 | ||||
○ | [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 3 issues ( = data accesses) costing 2 point each. | 6 | ||||
►1683 | miniqmc | Inefficient vectorization. | 46 | 2.04 | 100 | 100 |
○ | [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] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 7 issues ( = arrays) costing 2 points each | 14 | ||||
○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.77) - Focus on optimizing data accesses. | 0 | ||||
►1048 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 88 | 0.76 | 94 | 94.75 |
○ | [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 16 issues (= instructions) costing 4 points each. | 64 | ||||
○ | [SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 8 issues ( = arrays) costing 2 points each | 16 | ||||
○ | [SA] Presence of special instructions executing on a single port (BROADCAST) - Simplify data access and try to get stride 1 access. There are 6 issues (= instructions) costing 1 point each. | 6 | ||||
○ | [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 | ||||
○ | [DA] The ratio FP/LS (floating point / memory accesses) is between 0.8 and 1.2 (0.89) - Both arithmetic and data access have to be optimized simultaneously. | 0 | ||||
►218 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 22 | 0.67 | 87.5 | 63.93 |
○ | [SA] Presence of special instructions executing on a single port (INSERT/EXTRACT, COMPRESS/EXPAND, BLEND/MERGE, SHUFFLE/PERM, BROADCAST) - Simplify data access and try to get stride 1 access. There are 8 issues (= instructions) costing 1 point each. | 8 | ||||
○ | [SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 3 issues ( = arrays) costing 2 points each | 6 | ||||
○ | [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 | ||||
○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The 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 | ||||
○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.20) - Focus on optimizing data accesses. | 0 | ||||
►807 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 16 | 0.5 | 0 | 11.16 |
○ | [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 | ||||
►804 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 1 | 0.38 | 0 | 11.16 |
○ | [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 | ||||
►1918 | miniqmc | Inefficient vectorization. | 2 | 0.35 | 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 | ||||
►512 | miniqmc | Inefficient vectorization. | 15 | 0.31 | 100 | 100 |
○ | [SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 5 issues ( = arrays) costing 2 points each | 10 | ||||
○ | [DA] Ratio time (ORIG)/time (DL1) is greater than 3 (4.46) - Perform blocking. Perform array restructuring. There are 0 issues (= non unit stride or indirect memory access) costing 2 point each, with an additional malus of 5 points due to the ORIG/DL1 ratio. | 5 | ||||
○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.17) - Focus on optimizing data accesses. | 0 |