Load-Triggered Warp Approximation on GPU

Abstract

Value similarity of operands across warps have been exploited to improve energy efficiency of GPUs. Prior work, however, incurs significant overheads to check value similarity for every instruction and does not improve performance as it does not reduce the number of executed instructions. This work proposes Lock 'n Load (LnL) which triggers approximate execution of code regions by only checking similarity of values returned from load instructions and fuses multiple approximated warps into a single warp.