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

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

[ 2 / 3 ] Security settings from the host restrict profiling. Some metrics will be missing or incomplete.

Current value for kernel.perf_event_paranoid is 2. If possible, set it to 1 or check with your system administrator which flag can be used to achieve this.

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

[ 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.

[ 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.

[ 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.

[ 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.

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present

-fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling.

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present

-fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling.

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present

-fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling.

[ 3 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations and -fno-omit-frame-pointer is present

-fno-omit-frame-pointer improves the accuracy of callchains found during the application profiling.

[ 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

[ 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

[ 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

[ 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

[ 3 / 3 ] Optimization level option is correctly used

[ 3 / 3 ] Optimization level option is correctly used

[ 3 / 3 ] Optimization level option is correctly used

[ 3 / 3 ] Optimization level option is correctly used

[ 3.00 / 3 ] Most of time spent in analyzed modules (100.00%) comes from functions compiled with architecture specialization option -march=znver5

[ 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 ( -march=(target) ).

[ 3.00 / 3 ] Most of time spent in analyzed modules (100.00%) comes from functions compiled with architecture specialization option -mcpu

[ 3.00 / 3 ] Most of time spent in analyzed modules (99.99%) comes from functions compiled with architecture specialization option -mcpu

[ 4 / 4 ] Application profile is long enough (48.96 s)

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

[ 4 / 4 ] Application profile is long enough (34.76 s)

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

[ 4 / 4 ] Application profile is long enough (55.29 s)

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

[ 4 / 4 ] Application profile is long enough (42.49 s)

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

Not available for this run

[ 0 / 0 ] Fastmath not used

Consider to add ffast-math to compilation flags (or replace -O3 with -Ofast) to unlock potential extra speedup by relaxing floating-point computation consistency. Warning: floating-point accuracy may be reduced and the compliance to IEEE/ISO rules/specifications for math functions will be relaxed, typically 'errno' will no longer be set after calling some math functions.

Not available for this run

Not available for this run

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

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

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

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

[ 3 / 4 ] CPU activity is below 90% (73.48%)

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 ] CPU activity is good

CPU cores are active 91.76% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 94.30% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 95.21% of time

[ 4 / 4 ] Affinity is good (99.18%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.74%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (98.91%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (98.88%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 3 / 3 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of the application profiled time (5.22%)

[ 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 the application profiled time (58.50%). 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 ] Functions mostly use all threads

Functions running on a reduced number of threads (typically sequential code) cover less than 10% of the application profiled time (3.25%)

[ 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 the application profiled time (11.49%). 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 (37.01%) lower than cumulative innermost loop coverage (56.56%)

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

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (35.18%) lower than cumulative innermost loop coverage (35.69%)

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

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (38.49%) lower than cumulative innermost loop coverage (56.92%)

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

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (37.64%) lower than cumulative innermost loop coverage (56.18%)

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

[ 3 / 4 ] A significant amount of threads are idle (26.52%)

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.

[ 4 / 4 ] Threads activity is good

On average, more than 91.76% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 94.30% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 95.21% of observed threads are actually active

[ 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 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 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 BLAS2 operations

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (56.56%)

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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (35.69%)

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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (56.92%)

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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (56.18%)

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% (0.00%) is spend in BLAS1 operations

It could be more efficient to inline by hand BLAS1 operations

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

It could be more efficient to inline by hand BLAS1 operations

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

It could be more efficient to inline by hand BLAS1 operations

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

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

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

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

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (35.73%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (35.15%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (40.77%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (44.14%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (93.57%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (70.87%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (95.41%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (93.82%)

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