Verifying GPU Kernels by Test Amplification
University of California, San Diego
34th ACM Conference on Programming Language Design and Implementation (PLDI 2012), 2012
@article{agarwal2012verifying,
title={Verifying GPU Kernels by Test Amplification},
author={Agarwal, A.L.M.G.Y. and Lerner, R.G.R.J.S.},
year={2012}
}
We present a novel technique for verifying properties of data parallel GPU programs via test amplification. The key insight behind our work is that we can use the technique of static information flow to amplify the result of a single test execution over the set of all inputs and interleavings that affect the property being verified. We empirically demonstrate the effectiveness of test amplification for verifying race-freedom and determinism over a large number of standard GPU kernels, by showing that the result of verifying a single dynamic execution can be amplified over the massive space of possible data inputs and thread interleavings.
April 12, 2012 by hgpu
