Data mining MPSoC simulation traces to identify concurrent memory access patterns

Due to a growing need for flexibility, massively parallel Multiprocessor SoC (MPSoC) architectures are currently being developed. This leads to the need for parallel software, but poses the problem of the efficient deployment of the software on these architectures. To address this problem, the execution of the parallel program with software traces enabled on the platform and the visualization of these traces to detect irregular timing behavior is the rule. This is error prone as it relies on software logs and human analysis, and requires an existing platform. To overcome these issues and automate the process, we propose the conjoint use of a virtual platform logging at hardware level the memory accesses and of a data-mining approach to automatically report unexpected instructions timings, and the context of occurrence of these instructions. We demonstrate the approach on a multiprocessor platform running a video decoding application.