A Hardware–Software Blueprint for Flexible Deep Learning Specialization
arXiv: Learning(2019)
Abstract
This article describes the Versatile Tensor Accelerator (VTA), a programmable DL architecture designed to be extensible in the face of evolving workloads. VTA achieves “flexible specialization” via a parameterizable architecture, two-level Instruction Set Architecture (ISA), and a Just in Time (JIT) compiler.
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Key words
Machine learning,Computer architecture,Runtime,Task analysis,Computational modeling,Deep learning
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