G3 ACfL best (O3) | G4 ACfL best (O3) |
---|---|
[ 2.98 / 3 ] Architecture specific option -mcpu is used | [ 2.98 / 3 ] Architecture specific option -mcpu is used |
[ 2.98 / 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. | [ 2.98 / 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. |
[ 2 / 2 ] Application is correctly profiled ("Others" category represents 1.37 % 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 0.64 % 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 |
[ 2.97 / 3 ] Optimization level option is correctly used | [ 2.98 / 3 ] Optimization level option is correctly used |
[ 4 / 4 ] Application profile is long enough (12653.23 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 (7881.70 s) To have good quality measurements, it is advised that the application profiling time is greater than 10 seconds. |
G3 ACfL best (O3) | G4 ACfL best (O3) |
---|---|
[ 4 / 4 ] CPU activity is good CPU cores are active 97.63% of time | [ 4 / 4 ] CPU activity is good CPU cores are active 98.14% of time |
[ 4 / 4 ] Affinity is good (99.97%) Threads are not migrating to CPU cores: probably successfully pinned | [ 4 / 4 ] Affinity is good (99.97%) Threads are not migrating to CPU cores: probably successfully pinned |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed loops (79.07%) 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 (77.96%) 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 (9.46%) lower than cumulative innermost loop coverage (69.61%) 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 (6.54%) lower than cumulative innermost loop coverage (71.42%) 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 97.61% of observed threads are actually active | [ 4 / 4 ] Threads activity is good On average, more than 98.12% 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. |
[ 4 / 4 ] Enough time of the experiment time spent in analyzed innermost loops (69.61%) 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 (71.42%) 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 ] Loop profile is not flat At least one loop coverage is greater than 4% (6.46%), representing an hotspot for the application | [ 4 / 4 ] Loop profile is not flat At least one loop coverage is greater than 4% (5.28%), representing an hotspot for the application |
Analysis | r_1 | r_2 | |
---|---|---|---|
Loop Computation Issues | Less than 10% of the FP ADD/SUB/MUL arithmetic operations are performed using FMA | 9 | 10 |
Presence of a large number of scalar integer instructions | 6 | 6 | |
Control Flow Issues | Non-innermost loop | 2 | 1 |
Data Access Issues | Presence of constant non-unit stride data access | 5 | 4 |
Presence of indirect access | 2 | 2 | |
Vectorization Roadblocks | Presence of more than 4 paths | 4 | 3 |
Non-innermost loop | 2 | 1 | |
Presence of constant non-unit stride data access | 5 | 4 | |
Presence of indirect access | 2 | 2 |