Setup of an Experimental Framework for Performance Modeling and Prediction of Embedded Multicore AI Architectures
Quentin Dariol · elib (German Aerospace Center) · 2022
Evaluation of performance for complex applications such as Artificial Intelligence (AI) algorithms and more specifically neural networks on Multi-Processor Systems on a Chip (MPSoC) is tedious. Finding an optimized partitioning of the application while predicting accurately the latency induced by communication bus congestion, is hard using traditional analysis methods. This document presents a performance prediction worklow based on SystemC simulation models for timing prediction of neural networks on MPSoC.