Termination Analysis for GPU Kernels
Department of Computing, Imperial College London, London, United Kingdom
Science of Computer Programming, 2017
@article{ketema2017termination,
title={Termination analysis for GPU kernels},
author={Ketema, Jeroen and Donaldson, Alastair F},
journal={Science of Computer Programming},
year={2017},
publisher={Elsevier}
}
We describe a thread-modular technique for proving termination of massively parallel GPU kernels. The technique reduces the termination problem for these kernels to a sequential termination problem by abstracting the shared state, and as such allows us to leverage termination analysis techniques for sequential programs. An implementation in KITTeL is able to show termination of 94% of 604 kernels collected from various sources.
July 19, 2017 by hgpu
