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exec - 2026-03-17 16:43:20 - MAQAO 2026.0.0

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Strategizer  

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (94.99%)

If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances.

[ 4 / 4 ] Threads activity is good

On average, more than 90.98% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 92.53% of time

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (28.10%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (94.99%)

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 / 4 ] Affinity stability is lower than 90% (88.33%)

Threads are often migrating to other CPU cores/threads. For OpenMP, typically set (OMP_PLACES=cores OMP_PROC_BIND=close) or (OMP_PLACES=threads OMP_PROC_BIND=spread). With OpenMPI + OpenMP, use --bind-to core --map-by node:PE=$OMP_NUM_THREADS --report-bindings. With IntelMPI + OpenMP, set I_MPI_PIN_DOMAIN=omp:compact or I_MPI_PIN_DOMAIN=omp:scatter and use -print-rank-map.

[ 3 / 3 ] Less than 10% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

[ 0 / 3 ] Too many functions do not use all threads

Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (14.02%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.00%) lower than cumulative innermost loop coverage (94.99%)

Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex

[ 2 / 2 ] Less than 10% (0.00%) is spend in BLAS2 operations

BLAS2 calls usually could make a poor cache usage and could benefit from inlining.

[ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions)

Optimizer

Loop IDAnalysisPenalty Score
Loop 20 - exec+Execution Time: 28 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Loop Computation Issues+6
[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] 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
Data Access Issues+0
[SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 0 issues ( = arrays) costing 2 points each0
Loop 22 - exec+Execution Time: 28 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Loop Computation Issues+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
Data Access Issues+0
[SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 0 issues ( = arrays) costing 2 points each0
Loop 16 - exec+Execution Time: 19 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Data Access Issues+0
[SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 0 issues ( = arrays) costing 2 points each0
Loop 18 - exec+Execution Time: 19 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Loop Computation Issues+4
[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
Loop 12 - execExecution Time: 0 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Loop 14 - exec+Execution Time: 0 % - Vectorization Ratio: 100.00 % - Vector Length Use: 50.00 %
Loop Computation Issues+4
[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
Data Access Issues+0
[SA] Inefficient vectorization: more than 10% of the vector loads instructions are unaligned - When allocating arrays, don’t forget to align them. There are 0 issues ( = arrays) costing 2 points each0
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