[ 4 / 4 ] Application profile is long enough (475.95 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 41.29% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % 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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (41.06%)

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

[ 3 / 4 ] A significant amount of threads are idle (23.73%)

On average, more than 10% of observed threads are idle. Such threads are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 3 / 4 ] CPU activity is below 90% (76.27%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (19.75%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (20.22%)

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.

[ 2 / 4 ] Affinity stability is lower than 90% (64.63%)

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%)

[ 0 / 3 ] Cumulative Outermost/In between loops coverage (20.83%) greater than cumulative innermost loop coverage (20.22%)

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 (273.35 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 36.95% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % 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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (35.51%)

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 130.51% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (65.27%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (16.46%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (18.23%)

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.

[ 2 / 4 ] Affinity stability is lower than 90% (65.29%)

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 (17.28%) lower than cumulative innermost loop coverage (18.23%)

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 (165.65 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 31.43% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % 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 (29.17%)

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 204.54% of observed threads are actually active

[ 2 / 4 ] CPU activity is below 90% (51.15%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (11.98%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (16.50%)

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% (35.96%)

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 (12.67%) lower than cumulative innermost loop coverage (16.50%)

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 (102.45 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 24.23% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % 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 (20.77%)

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 308.26% of observed threads are actually active

[ 1 / 4 ] CPU activity is below 90% (38.55%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (7.08%), representing an hotspot for the application

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (13.15%)

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% (34.67%)

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 (7.62%) lower than cumulative innermost loop coverage (13.15%)

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 (55.45 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 19.50% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.15 % 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 (16.37%)

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 435.04% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (27.21%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (4.78%), representing an hotspot for the application

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (11.21%)

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% (26.24%)

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 (5.16%) lower than cumulative innermost loop coverage (11.21%)

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 (35.48 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 14.01% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 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

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

[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (11.95%)

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 581.65% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (18.19%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 3.00%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (11.09%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (8.98%)

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% (17.53%)

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 (2.97%) lower than cumulative innermost loop coverage (8.98%)

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 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 (28.21 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 9.03% of the time spent in analyzed modules. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.00 % 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 (7.47%)

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 968.44% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (15.14%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 1.57%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (6.90%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (6.24%)

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% (14.18%)

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 (1.23%) lower than cumulative innermost loop coverage (6.24%)

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 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 (32.97 s)

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

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with source/debug info

-g option gives access to debugging informations, such are source locations.

[ 0 / 3 ] Architecture specific options are unknown for some functions (compilation options info are not available)

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

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

Functions without compilation options information cumulate 6.11% of the time spent in analyzed modules. For libmumps_common.so, check that both -g and -grecord-gcc-switches are present. For libdmumps.so, check that both -g and -grecord-gcc-switches are present. Remark: if such options are 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 ] Optimization level is unknown for some functions (compilation options info are not available)

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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.19 % 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 (4.66%)

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 2184.88% of observed threads are actually active

[ 0 / 4 ] CPU activity is below 90% (17.11%)

CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling.

[ 0 / 4 ] Loop profile is flat

No hotspot found in the application (greatest loop coverage is 1.21%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (4.35%)

[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (4.24%)

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% (13.66%)

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 (0.42%) lower than cumulative innermost loop coverage (4.24%)

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)