Ultra-Efficient Content Addressable Memory for Tunable GPU Approximation

In this paper, we describe a resistive configurable associative memory (ReCAM) that enables selective approximation and asymmetric voltage overscaling to manage delivered efficiency. The ReCAM structure matches an input pattern with pre-stored ones by applying an approximate search on selected bit indices (bitline-configurable). To further reduce energy, we explore proper ReCAM sizing, various configurable search operations with low overhead voltage overscaling, and different ReCAM update policies. Experimental result on the AMD Southern Islands GPUs for eight applications shows bitlineconfigurable ReCAM achieve on average to 43.6% energy savings with an acceptable quality loss of 10%.