A2M: Approximate Algebraic Memory Using Polynomials Rings

Dong Kai Wang, Nam Sung Kim

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

Abstract

Emerging applications today operate on increasingly larger data sets, and as a result, the memory subsystem is prone to be a bottleneck in bandwidth and capacity. Many of these applications store data based on real world phenomena which often have continuity properties and can be approximated by mathematical functions. In this work, we view computer memory abstractly as a set of functions that map each address input to a data output. We propose Approximate Algebraic Memory (A2M), a specialized memory model that uses finite degree polynomials to approximate ranges of memory content with the desired properties. Specifically, A2M uses dedicated hardware to derive and store polynomial coefficients rather than memory data. In error resilient workloads, the benefits of this design is threefold: (1) high ratio memory compression, (2) high bandwidth accesses, and (3) direct computation on memory. We evaluate A2M's potential as an on-chip structure for general-purpose processors, and as a specialized read-only memory for neural network accelerators. Our results show that for CPU workloads, A2M yields minimal error (< 1%) at a fixed compression ratio of 16, and improves performance by 11.3% on average.

Original languageEnglish (US)
Title of host publicationInternational Symposium on Low Power Electronics and Design, ISLPED 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728129549
DOIs
StatePublished - Jul 2019
Event2019 IEEE/ACM International Symposium on Low Power Electronics and Design, ISLPED 2019 - Lausanne, Switzerland
Duration: Jul 29 2019Jul 31 2019

Publication series

NameProceedings of the International Symposium on Low Power Electronics and Design
Volume2019-July
ISSN (Print)1533-4678

Conference

Conference2019 IEEE/ACM International Symposium on Low Power Electronics and Design, ISLPED 2019
CountrySwitzerland
CityLausanne
Period7/29/197/31/19

Keywords

  • Approximate Computing
  • Data Compression
  • Memory Architecture

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'A<sup>2</sup>M: Approximate Algebraic Memory Using Polynomials Rings'. Together they form a unique fingerprint.

Cite this