research-article

A Novel ReRAM-Based Processing-in-Memory Architecture for Graph Traversal

Authors:

H. Howie Huang,

Tao LiAuthors Info & Claims

ACM Transactions on Storage (TOS), Volume 14, Issue 1

Article No.: 9, Pages 1 - 26

https://doi.org/10.1145/3177916

Published: 26 February 2018 Publication History

Abstract

Graph algorithms such as graph traversal have been gaining ever-increasing importance in the era of big data. However, graph processing on traditional architectures issues many random and irregular memory accesses, leading to a huge number of data movements and the consumption of very large amounts of energy. To minimize the waste of memory bandwidth, we investigate utilizing processing-in-memory (PIM), combined with non-volatile metal-oxide resistive random access memory (ReRAM), to improve both computation and I/O performance.

We propose a new ReRAM-based processing-in-memory architecture called RPBFS, in which graph data can be persistently stored and processed in place. We study the problem of graph traversal, and we design an efficient graph traversal algorithm in RPBFS. Benefiting from low data movement overhead and high bank-level parallel computation, RPBFS shows a significant performance improvement compared with both the CPU-based and the GPU-based BFS implementations. On a suite of real-world graphs, our architecture yields a speedup in graph traversal performance of up to 33.8×, and achieves a reduction in energy over conventional systems of up to 142.8×.

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Cited By

Cheng YHuang CJiang HXu XWang F(2024)An efficient SSSP algorithm on time-evolving graphs with prediction of computation resultsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2023.104830186(104830)Online publication date: Apr-2024
https://doi.org/10.1016/j.jpdc.2023.104830
Jiang XShen ZSun SYin PJia ZJu LZhang ZYu D(2023)Runtime Row/Column Activation Pruning for ReRAM-based Processing-in-Memory DNN Accelerators2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323699(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323699
Devic ARai SSivasubramaniam AAkel AEilert SEno JSalapura VZahran MChong FTang L(2022)To PIM or not for emerging general purpose processing in DDR memory systemsProceedings of the 49th Annual International Symposium on Computer Architecture10.1145/3470496.3527431(231-244)Online publication date: 18-Jun-2022
https://dl.acm.org/doi/10.1145/3470496.3527431
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Index Terms

A Novel ReRAM-Based Processing-in-Memory Architecture for Graph Traversal
1. Computer systems organization
  1. Architectures
  2. Embedded and cyber-physical systems
2. Hardware
  1. Emerging technologies

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Published In

cover image ACM Transactions on Storage

ACM Transactions on Storage Volume 14, Issue 1

Special Issue on NVM and Storage

February 2018

237 pages

ISSN:1553-3077

EISSN:1553-3093

DOI:10.1145/3190860

Editor:
Sam H. Noh
Ulsan National Institute of Science and Technology, Ulsan, Korea

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Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 26 February 2018

Accepted: 01 January 2018

Received: 01 November 2017

Published in TOS Volume 14, Issue 1

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National Natural Science Foundation of China
Chongqing High-Tech Research Program
Research Grants Council of the Hong Kong Special Administrative Region, China

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https://doi.org/10.1016/j.jpdc.2023.104830
Jiang XShen ZSun SYin PJia ZJu LZhang ZYu D(2023)Runtime Row/Column Activation Pruning for ReRAM-based Processing-in-Memory DNN Accelerators2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323699(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323699
Devic ARai SSivasubramaniam AAkel AEilert SEno JSalapura VZahran MChong FTang L(2022)To PIM or not for emerging general purpose processing in DDR memory systemsProceedings of the 49th Annual International Symposium on Computer Architecture10.1145/3470496.3527431(231-244)Online publication date: 18-Jun-2022
https://dl.acm.org/doi/10.1145/3470496.3527431
Zhang YJia ZDu HXue RShen ZShao Z(2022)A Practical Highly Paralleled ReRAM-Based DNN Accelerator by Reusing Weight Pattern RepetitionsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.307111641:4(922-935)Online publication date: Apr-2022
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Oliveira GBoroumand AGhose SGomez-Luna JMutlu O(2022)Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI54635.2022.00060(273-278)Online publication date: Jul-2022
https://doi.org/10.1109/ISVLSI54635.2022.00060
Ghasemi SJahannia BFarbeh H(2022)GraphA: An efficient ReRAM-based architecture to accelerate large scale graph processingJournal of Systems Architecture10.1016/j.sysarc.2022.102755133(102755)Online publication date: Dec-2022
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Garzón EYavits LLanuzza MTeman AWebster J(2022)Emerging Memory Structures for VLSI CircuitsWiley Encyclopedia of Electrical and Electronics Engineering10.1002/047134608X.W8438(1-28)Online publication date: 12-May-2022
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Wang FYiu MShao Z(2021)Accelerating Similarity-based Mining Tasks on High-dimensional Data by Processing-in-memory2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00167(1859-1864)Online publication date: Apr-2021
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Chen JLin GChen JWang Y(2021)Towards efficient allocation of graph convolutional networks on hybrid computation-in-memory architectureScience China Information Sciences10.1007/s11432-020-3248-y64:6Online publication date: 10-May-2021
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