Performance-Energy Optimizations for Shared Vector Accelerators in Multicores

Abstract

For multicore processors with a private vector coprocessor (VP) per core, VP resources may not be highly utilized due to limited data-level parallelism (DLP) in applications. Also, under low VP utilization static power dominates the total energy consumption. We enhance here our previously proposed VP sharing framework for multicores in order to increase VP utilization while reducing the static energy. We describe two power-gating (PG) techniques to dynamically control the VP's width based on utilization figures. Floating-point results on an FPGA prototype show that the PG techniques reduce the energy needs by 30-35 percent with negligible performance reduction as compared to a multicore with the same amount of hardware resources where, however, each core is attached to a private VP.