Adaptive, Efficient, Parallel Execution Of Parallel Programs

Future multicore processors will be heterogeneous, be increasingly less reliable, and operate in dynamically changing operating conditions. Such environments will result in a constantly varying pool of hardware resources which can greatly complicate the task of efficiently exposing a program's parallelism onto these resources. Coupled with this uncertainty is the diverse set of efficiency metrics that users may desire. This paper proposes Varuna, a system that dynamically, continuously, rapidly and transparently adapts a program's parallelism to best match the instantaneous capabilities of the hardware resources while satisfying different efficiency metrics. Varuna is applicable to both multithreaded and task-based programs and can be seamlessly inserted between the program and the operating system without needing to change the source code of either.We demonstrate Varuna's effectiveness in diverse execution environments using unaltered C/C++ parallel programs from various benchmark suites. Regardless of the execution environment, Varuna always outperformed the state-of-the-art approaches for the efficiency metrics considered.