| orig_default | icx_default | gcc_default | aocc_10 | icx_10 | gcc_9 |
|---|---|---|---|---|---|
[ 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. |
[ 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 | Not available for this run | Not available for this run | Not available for this run |
[ 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) ). | Not available for this run | Not available for this run | [ 3.00 / 3 ] Architecture specific option -march=znver5 is used | [ 3.00 / 3 ] Architecture specific option -axCORE is used | [ 3.00 / 3 ] Architecture specific option -march=znver5 is used |
[ 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. | Not available for this run | Not available for this run | [ 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. | [ 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. | [ 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. |
[ 4 / 4 ] Application profile is long enough (15.91 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 (22.49 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 (11.03 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 (15.87 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 (21.03 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 (13.00 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 0.00 % 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 | [ 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 | [ 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. | [ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used | [ 3 / 3 ] Optimization level option is correctly used |
[ 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. | [ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. | [ 1 / 1 ] Lstopo present. The Topology lstopo report will be generated. |
| orig_default | icx_default | gcc_default | aocc_10 | icx_10 | gcc_9 |
|---|---|---|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 98.79% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 98.90% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 90.54% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 98.83% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 98.86% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 91.83% of time |
[ 4 / 4 ] Affinity is good (99.67%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.77%) 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 | [ 4 / 4 ] Affinity is good (99.65%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.76%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.54%) Threads are not migrating to CPU cores: probably successfully pinned |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (89.24%) 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 (89.58%) 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 (92.73%) 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 (87.79%) 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 (93.76%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. |
[ 0 / 3 ] Cumulative Outermost/In between loops coverage (59.77%) greater than cumulative innermost loop coverage (29.46%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (83.72%) greater than cumulative innermost loop coverage (5.86%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (49.15%) greater than cumulative innermost loop coverage (43.58%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (51.74%) greater than cumulative innermost loop coverage (36.10%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (80.97%) greater than cumulative innermost loop coverage (6.82%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex | [ 0 / 3 ] Cumulative Outermost/In between loops coverage (82.24%) greater than cumulative innermost loop coverage (11.52%) 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 95.99% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 96.83% of observed threads are actually active | [ 3 / 4 ] A significant amount of threads are idle (12.93%) 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 95.88% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 96.74% of observed threads are actually active | [ 3 / 4 ] A significant amount of threads are idle (11.15%) 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. |
[ 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 (29.46%) 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. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (5.86%) 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 (43.58%) 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 (36.10%) 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. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (6.82%) 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. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (11.52%) 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% (0.00%) 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) | [ 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% (59.58%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (83.55%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (48.91%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (51.59%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (80.84%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (81.54%), representing an hotspot for the application |
| Analysis | r_1 | r_2 | r_3 | r_4 | r_5 | r_6 | |
|---|---|---|---|---|---|---|---|
| Loop Computation Issues | Presence of expensive FP instructions | 1 | 1 | 2 | 1 | 1 | 2 |
| Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 8 | 5 | 9 | 0 | 7 | 0 | |
| Presence of a large number of scalar integer instructions | 3 | 3 | 3 | 1 | 3 | 1 | |
| Low iteration count | 1 | 0 | 0 | 0 | 0 | 0 | |
| Control Flow Issues | Presence of 2 to 4 paths | 3 | 3 | 4 | 2 | 1 | 1 |
| Presence of more than 4 paths | 2 | 2 | 0 | 0 | 4 | 4 | |
| Non-innermost loop | 5 | 5 | 4 | 4 | 5 | 5 | |
| Low iteration count | 1 | 0 | 0 | 0 | 0 | 0 | |
| Data Access Issues | Presence of constant non-unit stride data access | 5 | 2 | 6 | 6 | 2 | 1 |
| Presence of indirect access | 2 | 2 | 1 | 2 | 2 | 0 | |
| More than 10% of the vector loads instructions are unaligned | 1 | 3 | 3 | 0 | 0 | 0 | |
| Presence of special instructions executing on a single port | 3 | 3 | 3 | 0 | 0 | 0 | |
| More than 20% of the loads are accessing the stack | 6 | 6 | 3 | 3 | 6 | 2 | |
| Vectorization Roadblocks | Presence of 2 to 4 paths | 3 | 3 | 4 | 2 | 1 | 1 |
| Presence of more than 4 paths | 2 | 2 | 0 | 0 | 4 | 4 | |
| Non-innermost loop | 5 | 5 | 4 | 4 | 5 | 5 | |
| Presence of constant non-unit stride data access | 5 | 2 | 6 | 6 | 2 | 1 | |
| Presence of indirect access | 2 | 2 | 1 | 2 | 2 | 0 | |
| Inefficient Vectorization | Presence of special instructions executing on a single port | 3 | 3 | 3 | 0 | 0 | 0 |