GaaS-X: Graph Analytics Accelerator Supporting Sparse Data Representation using Crossbar Architectures

Nagadastagiri Challapalle, Sahithi Rampalli, Linghao Song, Nandhini Chandramoorthy, Karthik Swaminathan, John Sampson, Yiran Chen, Vijaykrishnan Narayanan

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

Abstract

Graph analytics applications are ubiquitous in this era of a connected world. These applications have very low compute to byte-transferred ratios and exhibit poor locality, which limits their computational efficiency on general purpose computing systems. Conventional hardware accelerators employ custom dataflow and memory hierarchy organization to overcome these challenges. Processing-in-memory (PIM) accelerators leverage massively parallel compute capable memory arrays to perform the in-situ operations on graph data or employ custom compute elements near the memory to leverage larger internal bandwidths. In this work, we present GaaS-X, a graph analytics accelerator that inherently supports the sparse graph data representations using an in-situ compute-enabled crossbar memory architectures. We alleviate the overheads of redundant writes, sparse to dense conversions, and redundant computations on the invalid edges that are present in the state of the art crossbar-based PIM accelerators. GaaS-X achieves 7.7 × and 2.4 × performance and 22 × and 5.7 ×, energy savings, respectively, over two state-of-the-art crossbar accelerators and offers orders of magnitude improvements over GPU and CPU solutions.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture, ISCA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages433-445
Number of pages13
ISBN (Electronic)9781728146614
DOIs
StatePublished - May 2020
Event47th ACM/IEEE Annual International Symposium on Computer Architecture, ISCA 2020 - Virtual, Online, Spain
Duration: May 30 2020Jun 3 2020

Publication series

NameProceedings - International Symposium on Computer Architecture
Volume2020-May
ISSN (Print)1063-6897

Conference

Conference47th ACM/IEEE Annual International Symposium on Computer Architecture, ISCA 2020
CountrySpain
CityVirtual, Online
Period5/30/206/3/20

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

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