Optimization of static data race detection algorithm based on out-of-order parallel SystemC simulation with array element granularity

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.