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Experiment Quality

gccarmclang

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

[ 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.

[ 2.40 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations but -fno-omit-frame-pointer is missing

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

[ 2.40 / 3 ] Most of time spent in analyzed modules comes from functions with compilation options informations but -fno-omit-frame-pointer is missing

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

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.05 % 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 0.10 % 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 ] Architecture specific option -mcpu is used

[ 3 / 3 ] Architecture specific option -mcpu is used

[ 4 / 4 ] Application profile is long enough (10.34 s)

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

[ 0 / 4 ] Application profile is too short (9.95 s)

If the overall application profiling time is less than 10 seconds, many of the measurements at function or loop level will very likely be under the measurement quality threshold (0,1 seconds). Rerun to increase runtime duration: for example use a larger dataset or include a repetition loop.

[ 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.

[ 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.

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

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

Code Quality

gccarmclang

[ 4 / 4 ] CPU activity is good

CPU cores are active 99.95% of time

[ 4 / 4 ] CPU activity is good

CPU cores are active 99.98% of time

[ 4 / 4 ] Affinity is good (99.90%)

Threads are not migrating to CPU cores: probably successfully pinned

[ 4 / 4 ] Affinity is good (99.93%)

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 (0.00%)

[ 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 (1.40%) lower than cumulative innermost loop coverage (89.26%)

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 (9.35%) lower than cumulative innermost loop coverage (88.34%)

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 99.95% of observed threads are actually active

[ 4 / 4 ] Threads activity is good

On average, more than 99.98% 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.

[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (89.26%)

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 (88.34%)

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

[ 2 / 2 ] Less than 10% (8.71%) is spend in Libm/SVML (special functions)

[ 2 / 2 ] Less than 10% (0.35%) is spend in Libm/SVML (special functions)

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (34.69%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (34.99%), representing an hotspot for the application

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (90.66%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (97.69%)

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

Loops Overview

Analysisr0r1
Loop Computation IssuesPresence of expensive FP instructions12
Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA40
Presence of a large number of scalar integer instructions45
Control Flow IssuesPresence of calls21
Presence of 2 to 4 paths11
Presence of more than 4 paths10
Non-innermost loop15
Data Access IssuesPresence of constant non-unit stride data access75
Presence of indirect access10
Vectorization RoadblocksPresence of calls21
Presence of 2 to 4 paths11
Presence of more than 4 paths14
Non-innermost loop15
Presence of constant non-unit stride data access75
Presence of indirect access10
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