Kernel-to-User-Mode Transition-Aware Hardware Scheduling

As thread-level parallelism in applications has continued to expand, so has research in chip multicore processors. More and more applications are becoming multithreaded, which should lead to a growing number of threads executing on a machine. Consequentially, the operating system will require increasingly larger amounts of CPU time to schedule these threads efficiently. Instead of perpetuating the trend of performing more-complex thread scheduling in the OS, the authors propose a scheduling mechanism that can be efficiently implemented in hardware as well. Their approach of identifying multithreaded application bottlenecks such as thread synchronization sections complements the fairness-aware scheduler method. It achieves average speedup of 11.1 and 30 percent (geometric mean) compared to the state-of-the-art Fairness-Aware Scheduler and Linux OS scheduler, respectively, while being 8 percent slower compared to the state-of-the-art bottleneck identification techniques.