Optimization of AI SoC with Compiler-assisted Virtual Design Platform

Abstract

As deep learning keeps evolving dramatically with rapidly increasing complexity, the demand for efficient hardware accelerators has become vital. However, the lack of software/hardware co-development toolchains makes designing AI SoCs (artificial intelligent system-on-chips) considerably challenging. This paper presents a compiler-assisted virtual platform to facilitate the development of AI SoCs from the early design stage. The electronic system-level design platform provides rapid functional verification and performance/energy analysis. Cooperating with the neural network compiler, AI software and hardware can be co-optimized on the proposed virtual design platform. Our Deep Inference Processor is also utilized on the virtual design platform to demonstrate the effectiveness of the architectural evaluation and exploration methodology.