Designing RISC-V Instruction Set Extensions for Artificial Neural Networks: An LLVM Compiler-Driven Perspective

The demand for Artificial Intelligence (AI) based solutions is exponentially increasing in all application fields, including low-power devices on the edge. However, due to their limited computational capabilities, these devices, which run Central Processing Units (CPUs) tailored to embedded applicat...

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Autori principali:	Karthikeyan Kalyanasundaram Balasubramanian, Mirco Di Salvo, Walter Rocchia, Sergio Decherchi, Marco Crepaldi
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2024-01-01
Serie:	IEEE Access
Soggetti:	RISC-V AI RISC-V custom instructions extensions LLVM instruction set architecture hardware-software co-design
Accesso online:	https://ieeexplore.ieee.org/document/10501937/
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