An ESL(electronic system level)virtual platform for convolution accelerator design and verification

Abstract

In recent years Deep Neural Networks (DNNs) have been successfully applied to many computer visions However DNN needs to face a lot of data movements and computational complexities in the calculation process so it will be a huge challenge for power consumption and performance In this paper we propose an ESL virtual platform based on MDFI (Micro Darknet for Inference) for convolution accelerator design and verification In order to quickly develop accelerators and perform verification in the early stages of development we assume that the data for each layer of the model can be loaded into the memory on the accelerator at a time and compared with the Raspberry Pi3 The result shows that the execution time of the ESL virtual platform is about 2 3x faster than the Raspberry Pi3

Date of Award	2019
Original language	English
Supervisor	Chung-Ho Chen (Supervisor)