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A scalable queue for work distribution on GPUs

Published:10 February 2018Publication History
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Abstract

Harnessing the power of massively parallel devices like the graphics processing unit (GPU) is difficult for algorithms that show dynamic or inhomogeneous workloads. To achieve high performance, such advanced algorithms require scalable, concurrent queues to collect and distribute work. We present a new concurrent work queue, the Broker Queue, a highly efficient, linearizable queue for fine-granular work distribution on the GPU. We evaluate its usability and benefits in contrast to existing queuing algorithms. Our queue is up to one order of magnitude faster than non-blocking queues, and outperforms simpler queue designs that are unfit for fine-granular work distribution.

References

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  1. A scalable queue for work distribution on GPUs

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    • Published in

      cover image ACM SIGPLAN Notices
      ACM SIGPLAN Notices  Volume 53, Issue 1
      PPoPP '18
      January 2018
      426 pages
      ISSN:0362-1340
      EISSN:1558-1160
      DOI:10.1145/3200691
      Issue’s Table of Contents
      • cover image ACM Conferences
        PPoPP '18: Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
        February 2018
        442 pages
        ISBN:9781450349826
        DOI:10.1145/3178487

      Copyright © 2018 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 10 February 2018

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