Help is available by moving the cursor above any 
symbol or by checking MAQAO website.
[ 4 / 4 ] Application profile is long enough (232.71 s)
To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.
[ 3.00 / 3 ] Optimization level option is correctly used
[ 2.40 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g
-g option gives access to debugging informations, such are source locations. Add -fno-omit-frame-pointer to improve the accuracy of callchains found during the application profiling
[ 3.00 / 3 ] Architecture specific option -xop 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 (1.57%)
If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.
[ 0 / 4 ] Loop profile is flat
No hotspot found in the application (greatest loop coverage is 0.33%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (1.57%)
[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (1.55%)
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 (0.02%) lower than cumulative innermost loop coverage (1.55%)
Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex
[ 2 / 2 ] Less than 10% (0.01%) 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 (%) |
|---|---|---|---|---|---|---|
| ►183 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 0.33 | 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 4 issues ( = data accesses) costing 2 point each. | 8 | ||||
| ►169 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 0.24 | 50 | 28.13 |
| ○ | [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 | ||||
| ►184 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 0.22 | 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 4 issues ( = data accesses) costing 2 point each. | 8 | ||||
| ○186 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - No issue detected | 0 | 0.2 | 0 | 12.5 |
| ►185 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 8 | 0.2 | 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 4 issues ( = data accesses) costing 2 point each. | 8 | ||||
| ►739 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 51 | 0.07 | 85.45 | 41.82 |
| ○ | [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 special instructions executing on a single port (INSERT/EXTRACT, SHUFFLE/PERM, Other_packing) - Simplify data access and try to get stride 1 access. There are 10 issues (= instructions) costing 1 point each. | 10 | ||||
| ○ | [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] 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 | ||||
| ○ | [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 | ||||
| ○ | Warning! There is no dynamic data for this loop. Some checks can not been performed. | 0 | ||||
| ►827 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.06 | 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 | ||||
| ►173 | libqmckl.so.0.0.0 | Inefficient vectorization. | 6 | 0.05 | 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 | ||||
| ►162 | libqmckl.so.0.0.0 | Partial or unexisting vectorization - Use pragma to force vectorization and check potential dependencies between array access. | 2 | 0.04 | 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 | ||||
| ►779 | libqmckl.so.0.0.0 | Inefficient vectorization. | 2 | 0.02 | 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 |