options

Stylizer

engine_NEON1M11-0001_o2_m26_ifx_full/engine_NEON1M11-0001_o2_m26_ifort_full

[ 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) ).

[ 2.09 / 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) ).

[ 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.

[ 2.09 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information

Functions without compilation information (typically not compiled with -g) cumulate 30.32% 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.

[ 2 / 2 ] Application is correctly profiled ("Others" category represents 0.20 % 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 0.19 % 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

[ 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.

[ 2.10 / 3 ] Some functions are compiled with a low optimization level (O0 or O1)

To have good 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.

[ 4 / 4 ] Application profile is long enough (2050.76 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 (3579.74 s)

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

Strategizer

engine_NEON1M11-0001_o2_m26_ifx_full/engine_NEON1M11-0001_o2_m26_ifort_full

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (9.49%), representing an hotspot for the application

[ 4 / 4 ] Loop profile is not flat

At least one loop coverage is greater than 4% (9.19%), representing an hotspot for the application

[ 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 (80.95%)

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 (80.04%)

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% (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 ] Enough time of the experiment time spent in analyzed loops (85.37%)

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

[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (83.31%)

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

[ 3 / 3 ] Cumulative Outermost/In between loops coverage (4.41%) lower than cumulative innermost loop coverage (80.95%)

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 (3.27%) lower than cumulative innermost loop coverage (80.04%)

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

Optimizer

Analysisr_1r_2
Loop Computation IssuesPresence of expensive FP instructions11
Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA56
Large loop body over microp cache size10
Presence of a large number of scalar integer instructions23
Bottleneck in the front-end10
Control Flow IssuesPresence of calls21
Presence of 2 to 4 paths21
Presence of more than 4 paths01
Non-innermost loop10
Data Access IssuesPresence of constant non-unit stride data access22
Presence of indirect access22
More than 10% of the vector loads instructions are unaligned30
Presence of expensive instructions: scatter/gather01
Presence of special instructions executing on a single port30
More than 20% of the loads are accessing the stack34
Vectorization RoadblocksPresence of calls21
Presence of 2 to 4 paths21
Presence of more than 4 paths22
Non-innermost loop10
Presence of constant non-unit stride data access22
Presence of indirect access22
Inefficient VectorizationPresence of expensive instructions: scatter/gather01
Presence of special instructions executing on a single port30
Use of masked instructions10
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