Symbiotic scheduling of concurrent GPU kernels for performance and energy optimizations

Abstract

The incorporation of GPUs as co-processors has brought forth significant performance improvements for High-Performance Computing (HPC). Efficient utilization of the GPU resources is thus an important consideration for computer scientists. In order to obtain the required performance while limiting the energy consumption, researchers and vendors alike are seeking to apply traditional CPU approaches into the GPU computing domain. For instance, newer NVIDIA GPUs now support concurrent execution of independent kernels as well as Dynamic Voltage and Frequency Scaling (DVFS). Amidst these new developments, we are faced with new opportunities for efficiently scheduling GPU computational kernels under performance and energy constraints.