Rong-Guey Chang, Tam-Van Hoang*
Computer Systems Science and Engineering, Vol.46, No.1, pp. 999-1019, 2023, DOI:10.32604/csse.2023.034672
Abstract The diversity of software and hardware forces programmers to spend a great deal of time optimizing their source code, which often requires specific treatment for each platform. The problem becomes critical on embedded devices, where computational and memory resources are strictly constrained. Compilers play an essential role in deploying source code on a target device through the backend. In this work, a novel backend for the Open Neural Network Compiler (ONNC) is proposed, which exploits machine learning to optimize code for the ARM Cortex-M device. The backend requires minimal changes to Open Neural Network Exchange (ONNX) models. Several novel optimization… More >
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