查看文章

Value locality, the recurrence of a previously-seen value, has been the enabler of myriad optimization techniques in traditional processors. Value similarity relaxes the constraint of value locality by allowing values to differ in the lowest significant bits where values are micro-architecturally near. With the end of Dennard Scaling and the turn towards massively parallel accelerators, we revisit value similarity in the context of GPUs. We identify a form of value similarity called intra-warp operand value similarity, which is abundant in GPUs. We present Warp Approximation, which leverages intra-warp operand value similarity to trade off accuracy for energy. Warp Approximation dynamically identifies intra-warp operand value similarity in hardware, and executes a single representative thread on behalf of all the active threads in a warp, thereby producing a representative value with approximate value locality. This …