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LCCG : a locality-centric hardware accelerator for high throughput of concurrent graph processing
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Zhao, Jin, Zhang, Yu, Liao, Xiaofei, He, Ligang, He, Bingsheng, Jin, Hai and Liu, Haikun (2021) LCCG : a locality-centric hardware accelerator for high throughput of concurrent graph processing. In: SC '21: The International Conference for High Performance Computing, Networking, Storage and Analysis, St. Louis Missouri, 14-19 Nov 2021. Published in: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis pp. 1-14. ISBN 9781450384421. doi:10.1145/3458817.3480854
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Official URL: https://doi.org/10.1145/3458817.3480854
Abstract
In modern data centers, massive concurrent graph processing jobs are being processed on large graphs. However, existing hardware/-software solutions suffer from irregular graph traversal and intense resource contention. In this paper, we propose LCCG, a <u>L</u>ocality-<u>C</u>entric programmable accelerator that augments the many-core processor for achieving higher throughput of <u>C</u>oncurrent <u>G</u>raph processing jobs. Specifically, we develop a novel topology-aware execution approach into the accelerator design to regularize the graph traversals for multiple jobs on-the-fly according to the graph topology, which is able to fully consolidate the graph data accesses from concurrent jobs. By reusing the same graph data among more jobs and coalescing the accesses of the vertices' states for these jobs, LCCG can improve the core utilization. We conduct extensive experiments on a simulated 64-core processor. The results show that LCCG improves the throughput of the cutting-edge software system by 11.3~23.9 times with only 0.5% additional area cost. Moreover, LCCG gains the speedups of 4.7~10.3, 5.5~13.2, and 3.8~8.4 times over state-of-the-art hardware graph processing accelerators (namely, HATS, Minnow, and PHI, respectively).
| Item Type: | Conference Item (Paper) | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science > Computer Science | ||||
| SWORD Depositor: | Library Publications Router | ||||
| Journal or Publication Title: | Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis | ||||
| Publisher: | ACM | ||||
| ISBN: | 9781450384421 | ||||
| Official Date: | 14 November 2021 | ||||
| Dates: |
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| Page Range: | pp. 1-14 | ||||
| Article Number: | 45 | ||||
| DOI: | 10.1145/3458817.3480854 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Conference Paper Type: | Paper | ||||
| Title of Event: | SC '21: The International Conference for High Performance Computing, Networking, Storage and Analysis | ||||
| Type of Event: | Conference | ||||
| Location of Event: | St. Louis Missouri | ||||
| Date(s) of Event: | 14-19 Nov 2021 |
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