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[ 4 / 4 ] Application profile is long enough (32.71 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 -xHost is used
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.03 % 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 (87.87%)
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% (54.21%), representing an hotspot for the application
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (87.49%)
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 (0.38%) lower than cumulative innermost loop coverage (87.49%)
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% (1.3%) 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 (%) |
|---|---|---|---|---|---|---|
| ►2265 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 54.21 | 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 1 issues ( = data accesses) costing 2 point each. | 2 | ||||
| ►2308 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 28 | 21.6 | 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 14 issues ( = data accesses) costing 2 point each. | 28 | ||||
| ►4527 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 12 | 4.37 | 30 | 16.25 |
| ○ | [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 | ||||
| ►5306 | miniqmc | Inefficient vectorization. | 50 | 2.24 | 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 8 issues ( = arrays) costing 2 points each | 16 | ||||
| ○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is between 0.8 and 1.2 (0.97) - Both arithmetic and data access have to be optimized simultaneously. | 0 | ||||
| ►481 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 17 | 0.65 | 90.83 | 70.99 |
| ○ | [SA] Several paths (4 paths) - Simplify control structure or force the compiler to use masked instructions. There are 4 issues ( = paths) costing 1 point each. | 4 | ||||
| ○ | [SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 1.75 issues ( = arrays) costing 2 points each | 4 | ||||
| ○ | [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] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [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 | ||||
| ○ | [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 special instructions executing on a single port (COMPRESS/EXPAND) - Simplify data access and try to get stride 1 access. There are 1 issues (= instructions) costing 1 point each. | 1 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.65) - Focus on optimizing data accesses. | 0 | ||||
| ►2305 | miniqmc | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 0.53 | 8.33 | 13.54 |
| ○ | [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 | ||||
| ►4516 | miniqmc | Inefficient vectorization. | 50 | 0.37 | 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 8 issues ( = arrays) costing 2 points each | 16 | ||||
| ○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is between 0.8 and 1.2 (1.01) - Both arithmetic and data access have to be optimized simultaneously. | 0 | ||||
| ►4515 | miniqmc | Inefficient vectorization. | 50 | 0.35 | 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 8 issues ( = arrays) costing 2 points each | 16 | ||||
| ○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is between 0.8 and 1.2 (0.96) - Both arithmetic and data access have to be optimized simultaneously. | 0 | ||||
| ►501 | miniqmc | Inefficient vectorization. | 16 | 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 (5.93) - 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 6 points due to the ORIG/DL1 ratio. | 6 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.11) - Focus on optimizing data accesses. | 0 | ||||
| ►4501 | miniqmc | Inefficient vectorization. | 54 | 0.3 | 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 8 issues ( = arrays) costing 2 points each | 16 | ||||
| ○ | [DA] Highly variable Cycle per Iteration across loop instances (2.4540525071757 > 1.5 ) - Loop execution is sensitive to different contexts or/and call chain: try to determine such contexts and use loop specialization. Try FDO/PGO compiler options. This issue costs 4 point. | 4 | ||||
| ○ | [SA] Inefficient vectorization: use of masked instructions - Simplify control structure. The issue costs 2 points. | 2 | ||||
| ○ | [DA] The ratio FP/LS (floating point / memory accesses) is smaller than 0.8 (0.78) - Focus on optimizing data accesses. | 0 |