The metric value is low, which may signal a poor logical CPU cores utilization caused by load imbalance, threading runtime overhead, contended synchronization, or thread/process underutilization. Explore sub-metrics to estimate the efficiency of MPI and OpenMP parallelism or run the Locks and Waits analysis to identify parallel bottlenecks for other parallel runtimes.
| Sync Object | Wait Time with poor CPU Utilization | (% from Object Wait Time)(%) | Wait Count |
|---|---|---|---|
| Condition Variable 0x0d43fa13 | 8.230s | 53.4% | 1 |
| Condition Variable 0xd9e74274 | 7.754s | 51.9% | 1 |
| Futex 0x251f10cb | 5.921s | 99.1% | 52 |
| Condition Variable 0x17c7c503 | 1.256s | 100.0% | 439 |
| Futex | 0.472s | 100.0% | 4 |
| [Others] | 1.065s | 94.4% | 585 |
| Function | Module | Spin and Overhead Time | (% from CPU Time)(%) |
|---|---|---|---|
| __sched_yield | libc.so.6 | 0.230s | 0.2% |
| _PyFunction_Vectorcall | python3.9 | 0.018s | 0.0% |
| method_vectorcall | python3.9 | 0.018s | 0.0% |