ComputeDRAM: In-memory compute using off-the-shelf DRAMs

Fei Gao, Georgios Tziantzioulis, David Wentzlaff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In-memory computing has long been promised as a solution to the Memory Wall problem. Recent work has proposed using chargesharing on the bit-lines of a memory in order to compute in-place and with massive parallelism, all without having to move data across the memory bus. Unfortunately, prior work has required modification to RAM designs (e.g. adding multiple row decoders) in order to open multiple rows simultaneously. So far, the competitive and low-margin nature of the DRAM industry has made commercial DRAM manufacturers resist adding any additional logic into DRAM. This paper addresses the need for in-memory computation with little to no change to DRAM designs. It is the first work to demonstrate in-memory computation with off-theshelf, unmodified, commercial, DRAM. This is accomplished by violating the nominal timing specification and activating multiple rows in rapid succession, which happens to leave multiple rows open simultaneously, thereby enabling bit-line charge sharing. We use a constraint-violating command sequence to implement and demonstrate row copy, logical OR, and logical AND in unmodified, commodity, DRAM. Subsequently, we employ these primitives to develop an architecture for arbitrary, massively-parallel, computation. Utilizing a customized DRAM controller in an FPGA and commodity DRAM modules, we characterize this opportunity in hardware for all major DRAM vendors. This work stands as a proof of concept that in-memory computation is possible with unmodified DRAM modules and that there exists a financially feasible way for DRAM manufacturers to support in-memory compute.

Original languageEnglish (US)
Title of host publicationMICRO 2019 - 52nd Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings
PublisherIEEE Computer Society
Pages100-113
Number of pages14
ISBN (Electronic)9781450369381
DOIs
StatePublished - Oct 12 2019
Event52nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2019 - Columbus, United States
Duration: Oct 12 2019Oct 16 2019

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
ISSN (Print)1072-4451

Conference

Conference52nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2019
CountryUnited States
CityColumbus
Period10/12/1910/16/19

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Keywords

  • Bit-serial
  • DRAM
  • In-memory computing
  • Main memory

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  • Cite this

    Gao, F., Tziantzioulis, G., & Wentzlaff, D. (2019). ComputeDRAM: In-memory compute using off-the-shelf DRAMs. In MICRO 2019 - 52nd Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings (pp. 100-113). (Proceedings of the Annual International Symposium on Microarchitecture, MICRO). IEEE Computer Society. https://doi.org/10.1145/3352460.3358260