Efficient scheduling of recursive control flow on GPUs

  • Authors:
  • Xin Huo;Sriram Krishnamoorthy;Gagan Agrawal

  • Affiliations:
  • The Ohio State University, Columbus, OH, USA;Pacific Northwest National Laboratory, Richland, WA, USA;The Ohio State University, Columbus, OH, USA

  • Venue:
  • Proceedings of the 27th international ACM conference on International conference on supercomputing
  • Year:
  • 2013

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Abstract

Graphics processing units (GPUs) have rapidly emerged as a very significant player in high performance computing. Single instruction multiple thread (SIMT) pipelines are typically used in GPUs to exploit parallelism and maximize performance. Although support for unstructured control flow has been included in GPUs, efficiently managing thread divergence for arbitrary parallel programs remains a critical challenge. In this paper, we focus on the problem of supporting recursion in modern GPUs. We design and comparatively evaluate various algorithms to manage thread divergence encountered in recursive programs. The results improve upon traditional post-dominator based reconvergence mechanisms designed to handle thread divergence due to control flow within a procedure.