Multi-granularity sampling for simulating concurrent heterogeneous applications

TL;DR: An approach that uses the sampling technique to speed up the design flow of Multiprocessor System-on-Chip (MPSoC) systems and shows that the simulation of concurrent heterogeneous applications can be accelerated by a factor of up to 60x, while maintaining an average performance estimation error lower than 5%.

Abstract: Detailed or cycle-accurate/bit-accurate (CABA) simulation is a critical phase in the design flow of embedded systems However, with increasing system complexity, full detailed simulation is prohibitively slower than the hardware being simulated In this paper, we present an approach that uses the sampling technique to speed up the design flow of Multiprocessor System-on-Chip (MPSoC) systems Based on the dynamic behavior of the applications running concurrently, our method dynamically chooses between multiple granularities of the sampling phase The similarities of the execution phases for all possible granularities are first analyzed, then transitions between phase overlaps are discretized To facilitate the detection of repetitions, one phase, with an appropriate granularity, is chosen per process Unlike most other proposals, the associated performance is usually accurate enough not to need repeated resampling The use of checkpointing in conjunction with our approach is simplified because the amount of the needed disk space is significantly reduced Experimental results show that the simulation of concurrent heterogeneous applications can be accelerated by a factor of up to 60x, while maintaining an average performance estimation error lower than 5%