Gravity: An Artificial Neural Network Compiler for Embedded Applications

Abstract

This paper introduces the Gravity compiler. Gravity is an open source optimizing Artificial Neural Network (ANN) to ANSI C compiler with two unique design features that make it ideal for use in resource constrained embedded systems: (1) the generated ANSI C code is self-contained and void of any library or platform dependencies and (2) the generated ANSI C code is optimized for maximum performance and minimum memory usage. Moreover, Gravity is constructed as a modern compiler consisting of an intuitive input language, an expressive Intermediate Representation (IR), a mapping to a Fictitious Instruction Set Machine (FISM) and a retargetable backend, making it an ideal research tool for exploring high-performance embedded software strategies in AI and Deep-Learning applications. We validate the efficacy of Gravity by solving the MNIST handwriting digit recognition on an embedded device. We measured a 300x reduction in memory, 2.5x speedup in inference and 33% speedup in training compared to TensorFlow. We also outperformed TVM, by over 2.4x in inference speed.