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A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning
[article]
2019
arXiv
pre-print
We introduce Deep500: the first customizable benchmarking infrastructure that enables fair comparison of the plethora of deep learning frameworks, algorithms, libraries, and techniques. The key idea behind Deep500 is its modular design, where deep learning is factorized into four distinct levels: operators, network processing, training, and distributed training. Our evaluation illustrates that Deep500 is customizable (enables combining and benchmarking different deep learning codes) and fair
arXiv:1901.10183v2
fatcat:egohwkvmavdehorgxtmj2rc6t4