| orig_default | icx_default | aocc_9 | icx_5 |
|---|---|---|---|
[ 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 (12.03 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 (11.71 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 (11.71 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 (12.52 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 |
[ 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. |
[ 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 | aocc_9 | icx_5 |
|---|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 95.60% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 95.45% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 95.48% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 95.67% of time |
[ 4 / 4 ] Affinity is good (99.24%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.17%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.23%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.18%) 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 (6.15%) | [ 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 (4.53%) | [ 0 / 3 ] Too many functions do not use all threads Functions running on a reduced number of threads (typically sequential code) cover at least 10% of application walltime (34.21%). Check both "Max Inclusive Time Over Threads" and "Nb Threads" in Functions or Loops tabs and consider parallelizing sequential regions or improving parallelization of regions running on a reduced number of threads | [ 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 (4.14%) |
[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.04%) lower than cumulative innermost loop coverage (0.71%) 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 (0.07%) lower than cumulative innermost loop coverage (0.75%) 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 (0.19%) lower than cumulative innermost loop coverage (0.72%) 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 (0.03%) lower than cumulative innermost loop coverage (2.51%) Having cumulative Outermost/In between loops coverage greater than cumulative innermost loop coverage will make loop optimization more complex |
[ 2 / 4 ] A significant amount of threads are idle (39.07%) 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 / 4 ] A significant amount of threads are idle (41.56%) 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 / 4 ] A significant amount of threads are idle (37.17%) 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 / 4 ] A significant amount of threads are idle (42.05%) 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. |
[ 0 / 4 ] Too little time of the experiment time spent in analyzed innermost loops (0.71%) 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 (0.75%) 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 (0.72%) 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 (2.51%) 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% (0.10%) 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% (0.07%) is spend in Libm/SVML (special functions) | [ 2 / 2 ] Less than 10% (0.00%) is spend in Libm/SVML (special functions) |
[ 0 / 4 ] Loop profile is flat No hotspot found in the application (greatest loop coverage is 0.44%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (0.74%) | [ 0 / 4 ] Loop profile is flat No hotspot found in the application (greatest loop coverage is 0.46%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (0.81%) | [ 0 / 4 ] Loop profile is flat No hotspot found in the application (greatest loop coverage is 0.42%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (0.91%) | [ 0 / 4 ] Loop profile is flat No hotspot found in the application (greatest loop coverage is 1.06%), and the twenty hottest loops cumulated coverage is lower than 20% of the application profiled time (2.54%) |
[ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (0.75%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (0.82%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (0.92%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. | [ 0 / 4 ] Too little time of the experiment time spent in analyzed loops (2.54%) If the time spent in analyzed loops is less than 30%, standard loop optimizations will have a limited impact on application performances. |
| Analysis | r0 | r1 | r2 | r3 | |
|---|---|---|---|---|---|
| Loop Computation Issues | Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 0 | 0 | 0 | 3 |
| Presence of a large number of scalar integer instructions | 0 | 0 | 1 | 1 | |
| Control Flow Issues | Non-innermost loop | 0 | 0 | 1 | 0 |
| Data Access Issues | Presence of constant non-unit stride data access | 0 | 0 | 1 | 0 |
| Presence of indirect access | 0 | 0 | 1 | 3 | |
| Presence of special instructions executing on a single port | 0 | 0 | 1 | 1 | |
| More than 20% of the loads are accessing the stack | 0 | 0 | 1 | 0 | |
| Vectorization Roadblocks | Non-innermost loop | 0 | 0 | 1 | 0 |
| Presence of constant non-unit stride data access | 0 | 0 | 1 | 0 | |
| Presence of indirect access | 0 | 0 | 1 | 3 | |
| Inefficient Vectorization | Presence of special instructions executing on a single port | 0 | 0 | 1 | 1 |