In-Memory Processing to Support Search-Based and Bitwise Computation

Abstract: In this paper, we design a Multi-Purpose In-Memory Processing (MPIM) system, which can be used as main memory and for processing. MPIM consists of multiple crossbar memories with the capability of efficient in-memory computations. Instead of transferring the large dataset to the processors, MPIM provides two important in-memory processing capabilities: i) data searching for the nearest neighbor ii) bitwise operations including OR, AND and XOR with small analog sense amplifiers.

Bio: Mohsen Imani is a PhD candidate in the Department of Computer Science and Engineering at the University of California, San Diego. He is a member of System Energy Efficiency Lab (SeeLab) and also a leader in several ongoing projects in area of embedded systems and emerging computing. His research interest is brain-inspired computing, approximate computing and computer architecture.