| Skylake ICPX Ofast AoS (base) | Skylake ICPX Ofast SoA | Skylake ICPX Ofast Manual Unroll | Skylake ICPX Ofast Manual Unroll + SoA |
|---|---|---|---|
[ 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. |
[ 3.00 / 3 ] Architecture specific option -x Host is used | [ 3 / 3 ] Architecture specific option -x Host is used | [ 3 / 3 ] Architecture specific option -x Host is used | [ 3.00 / 3 ] Architecture specific option -x Host 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. | [ 3 / 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 / 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 improves 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 (104.67 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 (98.80 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 (28.13 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 (28.11 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 |
[ 3 / 3 ] Optimization level option is correctly used | [ 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. |
| Skylake ICPX Ofast AoS (base) | Skylake ICPX Ofast SoA | Skylake ICPX Ofast Manual Unroll | Skylake ICPX Ofast Manual Unroll + SoA |
|---|---|---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 96.72% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 96.53% of time | [ 3 / 4 ] CPU activity is below 90% (87.83%) CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling. | [ 3 / 4 ] CPU activity is below 90% (87.83%) CPU cores are idle more than 10% of time. Threads supposed to run on these cores are probably IO/sync waiting. Some hints: use faster filesystems to read/write data, improve parallel load balancing and/or scheduling. |
[ 4 / 4 ] Affinity is good (96.64%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (96.35%) Threads are not migrating to CPU cores: probably successfully pinned | [ 3 / 4 ] Affinity stability is lower than 90% (87.18%) Threads are often migrating to other CPU cores/threads. For OpenMP, typically set (OMP_PLACES=cores OMP_PROC_BIND=close) or (OMP_PLACES=threads OMP_PROC_BIND=spread). With OpenMPI + OpenMP, use --bind-to core --map-by node:PE=$OMP_NUM_THREADS --report-bindings. With IntelMPI + OpenMP, set I_MPI_PIN_DOMAIN=omp:compact or I_MPI_PIN_DOMAIN=omp:scatter and use -print-rank-map. | [ 3 / 4 ] Affinity stability is lower than 90% (87.17%) Threads are often migrating to other CPU cores/threads. For OpenMP, typically set (OMP_PLACES=cores OMP_PROC_BIND=close) or (OMP_PLACES=threads OMP_PROC_BIND=spread). With OpenMPI + OpenMP, use --bind-to core --map-by node:PE=$OMP_NUM_THREADS --report-bindings. With IntelMPI + OpenMP, set I_MPI_PIN_DOMAIN=omp:compact or I_MPI_PIN_DOMAIN=omp:scatter and use -print-rank-map. |
[ 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 (0.02%) | [ 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 (0.01%) | [ 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 (0.04%) | [ 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 (0.04%) |
[ 3 / 3 ] Cumulative Outermost/In between loops coverage (0.66%) lower than cumulative innermost loop coverage (81.22%) 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 (3.57%) lower than cumulative innermost loop coverage (96.26%) 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 (8.63%) lower than cumulative innermost loop coverage (90.77%) 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 (8.73%) lower than cumulative innermost loop coverage (90.71%) 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 (47.11%) 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 (49.13%) 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. | [ 0 / 4 ] A significant amount of threads are idle (78.92%) 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. | [ 0 / 4 ] A significant amount of threads are idle (78.90%) 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. |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (81.22%) 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 (96.26%) 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 (90.77%) 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 (90.71%) 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. |
[ 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) |
[ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (79.19%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (90.46%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (80.25%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (79.60%), representing an hotspot for the application |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (81.88%) 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 (99.83%) 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 (99.40%) 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 (99.44%) 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 | 2 | 1 | 1 | 1 |
| Presence of a large number of scalar integer instructions | 2 | 1 | 2 | 2 | |
| Low iteration count | 0 | 0 | 1 | 1 | |
| Control Flow Issues | Presence of 2 to 4 paths | 0 | 1 | 0 | 0 |
| Presence of more than 4 paths | 2 | 0 | 0 | 0 | |
| Non-innermost loop | 1 | 1 | 1 | 1 | |
| Low iteration count | 0 | 0 | 1 | 1 | |
| Data Access Issues | Presence of constant non-unit stride data access | 0 | 1 | 0 | 0 |
| Presence of indirect access | 1 | 1 | 1 | 1 | |
| Presence of expensive instructions: scatter/gather | 0 | 0 | 1 | 1 | |
| Presence of special instructions executing on a single port | 1 | 2 | 2 | 2 | |
| More than 20% of the loads are accessing the stack | 0 | 1 | 0 | 0 | |
| Vectorization Roadblocks | Presence of 2 to 4 paths | 0 | 1 | 0 | 0 |
| Presence of more than 4 paths | 2 | 0 | 0 | 0 | |
| Non-innermost loop | 1 | 1 | 1 | 1 | |
| Presence of constant non-unit stride data access | 0 | 1 | 0 | 0 | |
| Presence of indirect access | 1 | 1 | 1 | 1 | |
| Inefficient Vectorization | Presence of expensive instructions: scatter/gather | 0 | 0 | 1 | 1 |
| Presence of special instructions executing on a single port | 1 | 2 | 2 | 2 | |
| Use of masked instructions | 0 | 0 | 1 | 1 | |