Taking Back Control in an Intermediate Representation for GPU Computing
We describe our experiences successfully applying lightweight formal methods to substantially improve and reformulate an important part of Standard Portable Intermediate Representation SPIRV, an industry-standard language for GPU computing.
The formal model that we present has allowed us to (1) identify several ambiguities and needless complexities in the way that structured control flow was defined in the SPIRV specification; (2) interact with the authors of the SPIRV specification to rectify these problems; (3) validate the developer tools and conformance test suites that support the SPIRV language by cross-checking them against our formal model, improving the tools, test suites, and our models in the process; and (4) develop a novel method for fuzzing SPIRV compilers to detect miscompilation bugs that leverages our formal model.
The latest release of the SPIRV specification incorporates the revised set of control-flow definitions that have arisen from our work. Furthermore, our novel compiler-fuzzing technique has led to the discovery of twenty distinct, previously unknown bugs in SPIRV compilers from Google, the Khronos Group, Intel, and Mozilla. Our work showcases the practical impact that formal modelling and analysis techniques can have on the design and implementation of industry-standard programming languages.
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|Taking Back Control in an Intermediate Representation for GPU Computing
Vasileios Klimis Imperial College London, Jack Clark Imperial College London, Alan Baker Google, David Neto Google, John Wickerson Imperial College London, Alastair F. Donaldson Imperial College London; GoogleDOI
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Konstantinos Kallas University of Pennsylvania, Haoran Zhang University of Pennsylvania, Rajeev Alur University of Pennsylvania, Sebastian Angel University of Pennsylvania; Microsoft Research, Vincent Liu University of PennsylvaniaDOI