System-level performance analysis of multiprocessor system-on-chips by combining analytical model and execution time variation

As the impact of the communication architecture on performance grows in a Multiprocessor System-on-Chip (MPSoC) design, the need for performance analysis in the early stage in order to consider various communication architectures is also increasing. While a simulation is commonly performed for performance evaluation of an MPSoC, it often suffers from a lengthy run time as well as poor performance coverage due to limited input stimuli or their ad hoc applications. In this paper, we propose a novel system-level performance analysis method to estimate the performance distribution of an MPSoC. Our approach consists of two techniques: (1) analytical model of on-chip crossbar-based communication architectures and (2) enumeration of task-level execution time variations for a target application. The execution time variation of tasks is efficiently captured by a memory access workload model. Thus, the proposed approach leads to better performance coverage for an MPSoC application in a reasonable computation time than the simulation-based approach. The experimental results validate the accuracy, efficiency, and practical usage of the proposed approach.