In-DRAM near-data approximate acceleration for GPUs

Amir Yazdanbakhsh, Choungki Song, Jacob Sacks, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh, Nam Sung Kim

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

Abstract

GPUs are bottlenecked by the off-chip communication bandwidth and its energy cost; hence near-data acceleration is particularly attractive for GPUs. Integrating the accelerators withinDRAMcan mitigate these bottlenecks and additionally expose them to the higher internal bandwidth of DRAM. However, such an integration is challenging, as it requires low-overhead accelerators while supporting a diverse set of applications. To enable the integration, this work leverages the approximability of GPU applications and utilizes the neural transformation, which converts diverse regions of code mainly to Multiply-Accumulate (MAC). Furthermore, to preserve the SIMT execution model of GPUs, we also propose a novel approximateMAC unit with a significantly smaller area overhead. As such, this work introduces AXRAM-a novel DRAM architecture-that integrates several approximate MAC units. AXRAM offers this integration without increasing the memory column pitch or modifying the internal architecture of the DRAM banks. Our results with 10 GPGPU benchmarks show that, on average, AXRAM provides 2.6× speedup and 13.3× energy reduction over a baseline GPU with no acceleration. These benefits are achieved while reducing the overall DRAM system power by 26% with an area cost of merely 2.1%.

Original languageEnglish (US)
Title of host publicationProceedings - 27th International Conference on Parallel Architectures and Compilation Techniques, PACT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450359863
DOIs
StatePublished - Nov 1 2018
Event27th International Conference on Parallel Architectures and Compilation Techniques, PACT 2018 - Limassol, Cyprus
Duration: Nov 1 2018Nov 4 2018

Publication series

NameParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
ISSN (Print)1089-795X

Conference

Conference27th International Conference on Parallel Architectures and Compilation Techniques, PACT 2018
CountryCyprus
CityLimassol
Period11/1/1811/4/18

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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