ELP2IM: Efficient and Low Power Bitwise Operation Processing in DRAM
Xin Xin, Youtao Zhang, Jun Yang
Abstract
Recently proposed DRAM based memory-centric architectures have demonstrated their great potentials in addressing the memory wall challenge of modern computing systems. Such architectures exploit charge sharing of multiple rows to enable in-memory bitwise operations. However, existing designs rely heavily on reserved rows to implement computation, which introduces high data movement overhead, large operation latency, large energy consumption, and low operation reliability. In this paper, we propose ELP2IM, an efficient and low power processing in-memory architecture, to address the above issues. ELP2IM utilizes two stable states of sense amplifiers in DRAM subarrays so that it can effectively reduce the number of intra-subarray data movements as well as the number of concurrently opened DRAM rows, which exhibits great performance and energy consumption advantages over existing designs. Our experimental results show that the power efficiency of ELP2IM is more than 2X improvement over the state-of-the-art DRAM based memory-centric designs in real application.