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http://dx.doi.org/10.9708/jksci.2021.26.09.001

A Tool for On-the-fly Repairing of Atomicity Violation in GPU Program Execution  

Lee, Keonpyo (Dept. of AI Convergence Engineering, Gyeongsang National University)
Lee, Seongjin (Dept. of AI Convergence Engineering, Gyeongsang National University)
Jun, Yong-Kee (Dept. of Aerospace Software Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.26, no.9, 2021 , pp. 1-12 More about this Journal
Abstract
In this paper, we propose a tool called ARCAV (Atomatic Recovery of CUDA Atomicity violation) to automatically repair atomicity violations in GPU (Graphics Processing Unit) program. ARCAV monitors information of every barrier and memory to make actual memory writes occur at the end of the barrier region or to make the program execute barrier region again. Existing methods do not repair atomicity violations but only detect the atomicity violations in GPU programs because GPU programs generally do not support lock and sleep instructions which are necessary for repairing the atomicity violations. Proposed ARCAV is designed for GPU execution model. ARCAV detects and repairs four patterns of atomicity violations which represent real-world cases. Moreover, ARCAV is independent of memory hierarchy and thread configuration. Our experiments show that the performance of ARCAV is stable regardless of the number of threads or blocks. The overhead of ARCAV is evaluated using four real-world kernels, and its slowdown is 2.1x, in average, of native execution time.
Keywords
Concurrent program; GPU program; Concurrency error; Atomicity violation; On-the-fly repairing;
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