options

Stylizer

orig_defaultgcc_defaultaocc_defaulticx_10gcc_4aocc_6

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

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

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

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

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

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

[ 4 / 4 ] Application profile is long enough (28.27 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 (27.95 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 (28.23 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 (28.28 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 (27.81 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 (28.06 s)

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

[ 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 0.02 % 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 0.01 % 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 0.01 % 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 0.01 % 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 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 9 ] Compilation options are not available

Compilation options are an important optimization leverage but ONE-View is not able to analyze them.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

[ 0 / 1 ] Lstopo was not found on the host (either not installed or not loaded). The Topology lstopo report will not be generated.

Strategizer

orig_defaultgcc_defaultaocc_defaulticx_10gcc_4aocc_6

[ 4 / 4 ] CPU activity is good

CPU cores are active 97.68% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.93% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 98.08% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 97.65% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 96.89% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 97.96% of time

[ 4 / 4 ] Affinity is good (99.47%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.07%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.58%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.48%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.10%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.46%)

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 application walltime (4.97%)

[ 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 (5.56%)

[ 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 (5.58%)

[ 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 (5.44%)

[ 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 (5.52%)

[ 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 (5.20%)

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.13%) lower than cumulative innermost loop coverage (86.07%)

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 (0.42%) lower than cumulative innermost loop coverage (87.42%)

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 (0.49%) lower than cumulative innermost loop coverage (86.02%)

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 (0.38%) lower than cumulative innermost loop coverage (86.02%)

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 (0.20%) lower than cumulative innermost loop coverage (87.73%)

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 (0.49%) lower than cumulative innermost loop coverage (86.37%)

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

[ 4 / 4 ] Threads activity is good

On average, more than 95.21% 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 95.80% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 95.26% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 94.32% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 95.19% 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.

[ 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 (86.07%)

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 (87.42%)

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 (86.02%)

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 (86.02%)

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 (87.73%)

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 (86.37%)

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

[ 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% (0.24%) is spend in Libm/SVML (special functions)

[ 2 / 2 ] Less than 10% (0.25%) 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% (0.20%) is spend in Libm/SVML (special functions)

[ 2 / 2 ] Less than 10% (0.23%) is spend in Libm/SVML (special functions)

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (84.98%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (86.35%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (84.92%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (84.90%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (86.79%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (85.25%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (86.21%)

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 (87.84%)

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 (86.51%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (86.39%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (87.94%)

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 (86.86%)

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

Optimizer

Analysisr0r1r2r3r4r5
Loop Computation IssuesPresence of expensive FP instructions111110
Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA001000
Control Flow IssuesPresence of 2 to 4 paths100100
Presence of more than 4 paths011010
Data Access IssuesPresence of constant non-unit stride data access010010
Presence of indirect access010010
More than 10% of the vector loads instructions are unaligned111110
Presence of special instructions executing on a single port121120
Vectorization RoadblocksPresence of 2 to 4 paths100100
Presence of more than 4 paths011010
Presence of constant non-unit stride data access010010
Presence of indirect access010010
Inefficient VectorizationPresence of special instructions executing on a single port121120
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