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DTSTART;TZID=America/Denver:20231114T110000
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UID:submissions.supercomputing.org_SC23_sess155_pap326@linklings.com
SUMMARY:A GPU Algorithm for Detecting Strongly Connected Components
DESCRIPTION:Ghadeer Alabandi (Texas State University); William Sands and G
 eorge Biros (University of Texas, Oden Institute); and Martin Burtscher (T
 exas State University)\n\nDetecting strongly connected components (SCCs) i
 s an important step in various graph computations. The fastest GPU and CPU
  implementations from the literature work well on graphs where most of the
  vertices belong to a single SCC and the vertex degrees follow a power-law
  distribution. However, these algorithms can be slow on the mesh graphs us
 ed in certain radiative transfer simulations, which have a nearly constant
  vertex degree and can have significant variability in the number and size
  of SCCs. We introduce ECL-SCC, an SCC detection algorithm that addresses 
 these shortcomings. Our approach is GPU-friendly and employs innovative te
 chniques such as maximum ID propagation and edge removal. On an A100 GPU, 
 ECL-SCC performs on par with the fastest prior GPU code on power-law graph
 s and outperforms it by 7.8x on mesh graphs. Moreover, ECL-SCC running on 
 the GPU outperforms fast parallel CPU code by three orders of magnitude on
  meshes.\n\nTag: Accelerators, Algorithms, Graph Algorithms and Frameworks
 \n\nRegistration Category: Tech Program Reg Pass\n\nReproducibility Badges
 : Artifact Available, Artifact Functional, Results Reproduced\n\nSession C
 hair: Marco Minutoli (Advanced Micro Devices)\n\n
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