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BARRACUDA: binary-level analysis of runtime RAces in CUDA programs

Ariel Eizenberg, Yuanfeng Peng, Toma Pigli, William Mansky, Joseph Devietti

Abstract

GPU programming models enable and encourage massively parallel programming with over a million threads, requiring extreme parallelism to achieve good performance. Massive parallelism brings significant correctness challenges by increasing the possibility for bugs as the number of thread interleavings balloons. Conventional dynamic safety analyses struggle to run at this scale.

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