| gcc o2 | gcc o3 | clang o2 | clang o3 |
|---|---|---|---|
[ 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. |
[ 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. | [ 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. |
[ 0 / 3 ] Compilation of some functions is not optimized for the target processor -march=x86-64 option is used but it is not specific enough to produce efficient code. Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ). | [ 0 / 3 ] Compilation of some functions is not optimized for the target processor -march=x86-64 option is used but it is not specific enough to produce efficient code. Architecture specific options are needed to produce efficient code for a specific processor ( -x(target) or -ax(target) ). | [ 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) ). | [ 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) ). |
[ 2.99 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g and -fno-omit-frame-pointer -g option gives access to debugging informations, such are source locations. -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling. | [ 3.00 / 3 ] Most of time spent in analyzed modules comes from functions compiled with -g and -fno-omit-frame-pointer -g option gives access to debugging informations, such are source locations. -fno-omit-frame-pointer improve the accuracy of callchains found during the application profiling. | [ 0 / 3 ] Most of time spent in analyzed modules comes from functions without compilation information Functions without compilation information (typically not compiled with -g and -grecord-gcc-switches) cumulate 100.00% of the time spent in analyzed modules. Check that -g and -grecord-gcc-switches are present. Remark: if -g and -grecord-gcc-switches 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 ] Most of time spent in analyzed modules comes from functions without compilation information Functions without compilation information (typically not compiled with -g and -grecord-gcc-switches) cumulate 100.00% of the time spent in analyzed modules. Check that -g and -grecord-gcc-switches are present. Remark: if -g and -grecord-gcc-switches 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. |
[ 4 / 4 ] Application profile is long enough (51.14 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 (50.23 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 (54.40 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 (53.63 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. |
[ 0 / 2 ] Too much execution time spent in category "Others" (44.83 %) If the category "Others" represents more than 20% of the execution time, it means that the application profile misses a representative part of the application. Examine functions details to properly identify “Others” category components. Rerun after adding most represented library names (e.g. more than 20% of coverage) to external_libraries (the names can be directly provided by ONE View) | [ 0 / 2 ] Too much execution time spent in category "Others" (45.57 %) If the category "Others" represents more than 20% of the execution time, it means that the application profile misses a representative part of the application. Examine functions details to properly identify “Others” category components. Rerun after adding most represented library names (e.g. more than 20% of coverage) to external_libraries (the names can be directly provided by ONE View) | [ 0 / 2 ] Too much execution time spent in category "Others" (43.29 %) If the category "Others" represents more than 20% of the execution time, it means that the application profile misses a representative part of the application. Examine functions details to properly identify “Others” category components. Rerun after adding most represented library names (e.g. more than 20% of coverage) to external_libraries (the names can be directly provided by ONE View) | [ 0 / 2 ] Too much execution time spent in category "Others" (42.48 %) If the category "Others" represents more than 20% of the execution time, it means that the application profile misses a representative part of the application. Examine functions details to properly identify “Others” category components. Rerun after adding most represented library names (e.g. more than 20% of coverage) to external_libraries (the names can be directly provided by ONE View) |
[ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used | [ 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. | [ 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. |
[ 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. |
| gcc o2 | gcc o3 | clang o2 | clang o3 |
|---|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 95.18% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 92.32% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 97.54% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 97.09% of time |
[ 4 / 4 ] Affinity is good (99.92%) 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 | [ 4 / 4 ] Affinity is good (99.91%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.92%) Threads are not migrating to CPU cores: probably successfully pinned |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (31.22%) 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 (30.54%) 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 (32.44%) 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 (33.34%) 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 (2.27%) lower than cumulative innermost loop coverage (28.95%) 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 (4.85%) lower than cumulative innermost loop coverage (25.70%) 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 (0.58%) lower than cumulative innermost loop coverage (31.86%) 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 (0.72%) lower than cumulative innermost loop coverage (32.62%) 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 95.18% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 92.32% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 97.54% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 97.09% 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 (28.95%) 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 (25.70%) 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 (31.86%) 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 (32.62%) 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% (0.66%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.70%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.88%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (1.11%) is spend in Libm/SVML (special functions) |
[ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (19.42%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (19.14%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (21.69%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (21.57%), representing an hotspot for the application |
| Analysis | r_1 | r_2 | r_3 | r_4 | |
|---|---|---|---|---|---|
| Loop Computation Issues | Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 1 | 2 | 1 | 1 |
| Presence of a large number of scalar integer instructions | 4 | 4 | 3 | 3 | |
| Control Flow Issues | Presence of calls | 4 | 4 | 4 | 4 |
| Presence of 2 to 4 paths | 2 | 2 | 2 | 3 | |
| Presence of more than 4 paths | 6 | 3 | 6 | 5 | |
| Non-innermost loop | 2 | 5 | 1 | 1 | |
| Data Access Issues | Presence of constant non-unit stride data access | 3 | 3 | 3 | 4 |
| More than 10% of the vector loads instructions are unaligned | 0 | 1 | 0 | 0 | |
| Presence of special instructions executing on a single port | 2 | 2 | 0 | 0 | |
| More than 20% of the loads are accessing the stack | 2 | 2 | 2 | 2 | |
| Vectorization Roadblocks | Presence of calls | 4 | 4 | 4 | 4 |
| Presence of 2 to 4 paths | 2 | 2 | 2 | 3 | |
| Presence of more than 4 paths | 6 | 5 | 6 | 5 | |
| Non-innermost loop | 2 | 5 | 1 | 1 | |
| Presence of constant non-unit stride data access | 3 | 3 | 3 | 4 | |
| Inefficient Vectorization | Presence of special instructions executing on a single port | 2 | 2 | 0 | 0 |