We propose a high performance hybrid hardware/software solution to race detection that uses minimal hardware support. This hardware extension consists of a single extra instruction, StateChk, that simply returns the coherence state of a cache block without requiring any complex traps to handlers. To leverage this support, we propose a new algorithm for race detection. This detection algorithm uses StateChk to eliminate many expensive operations. We also propose a new execution schedule manipulation heuristic to achieve high coverage rapidly. This approach is capable of detecting virtually all data races detected by a traditional happened-before data race detection approach, but at significantly lower space and performance overhead. © 2011 Springer-Verlag.
CITATION STYLE
Gonzalez-Alberquilla, R., Strauss, K., Ceze, L., & Piñuel, L. (2011). Accelerating data race detection with minimal hardware support. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6852 LNCS, pp. 27–38). https://doi.org/10.1007/978-3-642-23400-2_4
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