Hai-Dang Vu and Sebastien Le Nours and Sebastien Pillement and Ralf Stemmer and Kim Grüttner
26th Asia and South Pacific Design Automation Conference (ASP-DAC) 2021
Fast yet accurate performance and timing prediction of complex parallel data flow applications on multi-processor systems remains a difficult discipline. The reason for it comes from the complexity of the data flow applications and the hardware platform with shared resources, like buses and memories. This combination may lead to complex timing interferences that are difficult to express in pure analytical or classical simulation-based approaches. In this work, we propose a message-level communication model for timing and performance prediction of Synchronous Data Flow (SDF) applications on MPSoCs with shared memories. We compare our work against measurement and TLM simulation-based performance prediction models on two case-studies from the computer vision domain.We show that the accuracy and execution time of our simulation outperforms existing approaches and is suitable for a fast yet accurate design space exploration.
01 / 2021
PETA-MC Probabilistic Energy and Timing Analysis of Data Flow Applications on Multi-Core Processors