Paper
31 May 2023 Optimization of static data race detection algorithm based on out-of-order parallel SystemC simulation with array element granularity
Nie Sun, Zhengqiu Yang, Jiapeng Xiu, Chen Liu
Author Affiliations +
Proceedings Volume 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023); 127043O (2023) https://doi.org/10.1117/12.2680021
Event: 8th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2023), 2023, Hangzhou, China
Abstract
The IEEE SystemC standard is widely used in Electronic System-Level design, and this high-level abstraction enables more efficient architectural analysis, design, and redesign. Although it often runs on multi-core processors, SystemC itself is written to execute sequentially and cannot use multi-core resources. Based on Out-of-Order PDES for SystemC, this paper provides a more fine-grained data race detection algorithm, which provides more accurate conflict detection results without losing extra time in compilation. The experimental results show that the accuracy of data race detection based on array element granularity is better than that of field granularity detection, meanwhile it can effectively improve the execution efficiency of the program.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nie Sun, Zhengqiu Yang, Jiapeng Xiu, and Chen Liu "Optimization of static data race detection algorithm based on out-of-order parallel SystemC simulation with array element granularity", Proc. SPIE 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023), 127043O (31 May 2023); https://doi.org/10.1117/12.2680021
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KEYWORDS
Detection and tracking algorithms

Design and modelling

Computer simulations

Analytical research

Systems modeling

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