3D-stacked memory-side acceleration: Accelerator and system design

Qi Guo, Nikolaos Alachiotis, Berkin Akin, Fazle Sadi, Guanglin Xu, Tze Meng Low, Larry Pileggi, James C. Hoe, Franz Franchetti

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Specialized hardware acceleration is an effective technique to mitigate the dark silicon problems. A challenge in designing on-chip hardware accelerators for data-intensive applications is how to efficiently transfer data between the memory hierarchy and the accelerators. Although the Processingin-Memory (PIM) technique has the potential to reduce the overhead of data transfers, it is limited by the traditional process technology. Recent process technology advancements such as 3Ddie stacking enable efficient PIM architectures by integrating accelerators to the logic layer of 3D DRAM, thus leading to the concept of the 3D-stacked Memory-Side Accelerator (MSA). In this paper, we initially present the overall architecture of the 3D-stacked MSA, which relies on a configurable array of domain-specific accelerators. Thereafter, we describe a full-system prototype that is built upon a novel software stack and a hybrid evaluation methodology. Experimental results demonstrate that the 3D-stacked MSA achieves up to 179x and 96x better energyefficiency than the Intel Haswell processor for the FFT and matrix transposition algorithms, respectively.
Original languageEnglish
Title of host publication2nd Workshop on Near Data Processing (WONDP) in conjunction with the 47th IEEE/ACM International Symposium on Microarchitecture (MICRO-47)
PublisherIEEE
Number of pages6
Publication statusPublished - 2014
Externally publishedYes
Event2nd Workshop on Near Data Processing, WONDP 2014 - Cambridge, United Kingdom
Duration: 13 Dec 201417 Dec 2014
Conference number: 2

Conference

Conference2nd Workshop on Near Data Processing, WONDP 2014
Abbreviated titleWONPD
Country/TerritoryUnited Kingdom
CityCambridge
Period13/12/1417/12/14

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