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arXiv · 2305.09130

Auto-Tuning High-Performance Programs Using Model Checking in Promela

Natalia Garanina·Sergey Staroletov·Sergei Gorlatch
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Abstract

The paper combines research approaches that traditionally have been disjoint: 1) model checking as used in formal verification of programs, and 2) auto-tuning as often used in high-performance computing. Auto-tuning frameworks optimize parallel programs by finding the optimal values of the performance-critical parameters -- so-called tuning parameters -- for a particular high-performance architecture and input data size. As there are many parameters influencing program's performance, finding the optimal parameter configuration is a hardly manageable task even for experts. Auto-tuning automates this process, but it is often time-consuming. We apply model checking for accelerating auto-tuning by using a counterexample constructed during the verification of the optimality property of the program. We describe in detail an implementation of our approach for programs written in OpenCL -- the standard for programming modern high-performance architectures -- using the model representation language Promela and the popular SPIN verification tool, and we report experimental results for an application use case.

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Natalia Garanina, Sergey Staroletov, Sergei Gorlatch. 2023-05-16. Auto-Tuning High-Performance Programs Using Model Checking in Promela. https://arxiv.org/abs/2305.09130

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