Unblocking Dynamic Partial Order Reduction

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Abstract

Existing dynamic partial order reduction (DPOR) algorithms scale poorly on concurrent data structure benchmarks because they visit a huge number of blocked executions due to spinloops. In response, we develop Awamoche, a sound, complete, and strongly optimal DPOR algorithm that avoids exploring any useless blocked executions in programs with await and confirmation-CAS loops. Consequently, it outperforms the state-of-the-art, often by an exponential factor.

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APA

Kokologiannakis, M., Marmanis, I., & Vafeiadis, V. (2023). Unblocking Dynamic Partial Order Reduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13964 LNCS, pp. 230–250). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-37706-8_12

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