Matrix-DSP back-end support based on TVM compilation structure

Abstract

The emergence of deep learning frameworks has greatly facilitated the construction of network models, but it has not solved the problem of network models deployed in different hardware backends. TVM combines hardware-independent optimization and hardware-related optimization decoupling ideas to provide excellent solutions. By analyzing the basic structure of TVM and the basic process of neural network deployment on hardware, TVM has realized the basic support of the independently developed chip Matrix-DSP, which provides a foundation for further exploring the performance of the chip and enriching the application scenarios of the chip.