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On Static Timing Analysis of GPU Kernels

Author Vesa Hirvisalo



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Vesa Hirvisalo

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Vesa Hirvisalo. On Static Timing Analysis of GPU Kernels. In 14th International Workshop on Worst-Case Execution Time Analysis. Open Access Series in Informatics (OASIcs), Volume 39, pp. 43-52, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2014)
https://doi.org/10.4230/OASIcs.WCET.2014.43

Abstract

We study static timing analysis of programs running on GPU accelerators. Such programs follow a data parallel programming model that allows massive parallelism on manycore processors. Data parallel programming and GPUs as accelerators have received wide use during the recent years. The timing analysis of programs running on single core machines is well known and applied also in practice. However for multicore and manycore machines, timing analysis presents a significant but yet not properly solved problem. In this paper, we present static timing analysis of GPU kernels based on a method that we call abstract CTA simulation. Cooperative Thread Arrays (CTA) are the basic execution structure that GPU devices use in their operation that proceeds in thread groups called warps. Abstract CTA simulation is based on static analysis of thread divergence in warps and their abstract scheduling.
Keywords
  • Parallelism
  • WCET

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References

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