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DTSTAMP:20211207T054805Z
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UID:submissions.supercomputing.org_SC21_sess151_pap246@linklings.com
SUMMARY:LCCG: A Locality-Centric Hardware Accelerator for High Throughput 
 of Concurrent Graph Processing
DESCRIPTION:Paper\n\nLCCG: A Locality-Centric Hardware Accelerator for Hig
 h Throughput of Concurrent Graph Processing\n\nZhao, Zhang, Liao, He, He..
 .\n\nIn modern data centers, massive concurrent graph processing jobs are 
 being processed on large graphs. However, existing hardware/- software sol
 utions suffer from irregular graph traversal and intense resource contenti
 on. In this paper, we propose LCCG, a Locality-Centric programmable accele
 rator that augments the many-core processor for achieving higher throughpu
 t of Concurrent Graph processing jobs. Specifically, we develop a novel to
 pology-aware execution approach into the accelerator design to regularize 
 the graph traversals for multiple jobs on-the-fly according to the graph t
 opology, which is able to fully consolidate the graph data accesses from c
 oncurrent jobs. By reusing the same graph data among more jobs and coalesc
 ing the accesses of the vertices’ states for these jobs, LCCG can improve 
 the core utilization. We conduct extensive experiments on a simulated 64-c
 ore processor. The results show that LCCG improves the throughput of the c
 utting-edge software system by 11.3-23.9 times with only 0.5% area cost.\n
 \nTag: Reproducibility Badge, Accelerator-based Architectures\n\nRegistrat
 ion Category: Tech Program Reg Pass\n\nReproducibility Badges: Artifact Av
 ailable, Artifact Functional, Results Reproduced
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