[ 4 / 4 ] Application profile is long enough (644.91 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 3.99 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (7.96%)

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 99.89% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 99.89% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 3.81%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (7.96%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (7.78%)

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.

[ 0 / 4 ] Affinity stability is lower than 90% (10.28%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.18%) lower than cumulative innermost loop coverage (7.78%)

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)

[ 4 / 4 ] Application profile is long enough (382.87 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 3.38 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (7.09%)

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 199.64% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 99.84% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 3.16%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (6.98%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (6.94%)

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.

[ 0 / 4 ] Affinity stability is lower than 90% (25.33%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.16%) lower than cumulative innermost loop coverage (6.94%)

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)

[ 4 / 4 ] Application profile is long enough (235.62 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 2.76 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (6.23%)

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 384.76% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.24% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 2.40%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (6.10%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (6.11%)

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.

[ 1 / 4 ] Affinity stability is lower than 90% (33.32%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.13%) lower than cumulative innermost loop coverage (6.11%)

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)

[ 4 / 4 ] Application profile is long enough (169.32 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 2.04 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (5.39%)

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 721.13% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 90.22% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 1.46%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (5.20%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (5.30%)

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.

[ 1 / 4 ] Affinity stability is lower than 90% (45.46%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.09%) lower than cumulative innermost loop coverage (5.30%)

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)

[ 4 / 4 ] Application profile is long enough (121.47 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 1.40 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (4.08%)

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 1481.89% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 92.71% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.83%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (3.95%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (4.03%)

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% (74.90%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.06%) lower than cumulative innermost loop coverage (4.03%)

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)

[ 4 / 4 ] Application profile is long enough (89.81 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 2.47 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (3.11%)

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 2995.97% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 93.71% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.61%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (2.98%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (3.05%)

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% (80.44%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.06%) lower than cumulative innermost loop coverage (3.05%)

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)

[ 4 / 4 ] Application profile is long enough (82.23 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.52 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (2.44%)

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 6158.66% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.36% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.61%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (2.37%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (2.41%)

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% (85.08%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.03%) lower than cumulative innermost loop coverage (2.41%)

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)

[ 4 / 4 ] Application profile is long enough (93.01 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.23 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (2.11%)

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 12379.05% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.84% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.67%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (2.06%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (2.09%)

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% (84.51%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.02%) lower than cumulative innermost loop coverage (2.09%)

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)

[ 4 / 4 ] Application profile is long enough (98.97 s)

To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds.

[ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 100.00% of the time spent in analyzed modules. Check that -g is present.
Remark: if -g is indeed used, this can also be due to some compiler built-in functions (typically math) or statically linked libraries. This warning can be ignored in that case.

[ 0 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have better performances, it is advised to help the compiler by using a proper optimization level (-O2 of higher). Warning, depending on compilers, faster optimization levels can decrease numeric accuracy.

[ 3 / 3 ] Host configuration allows retrieval of all necessary metrics.

[ 0 / 3 ] Compilation of some functions is not optimized for the target processor

Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ).

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.17 % 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

[ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated.

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (1.90%)

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 16645.52% of observed threads are actually active

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.90% of time

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 0.59%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (1.87%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (1.88%)

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% (83.98%)

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

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of application walltime (0.00%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.02%) lower than cumulative innermost loop coverage (1.88%)

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)