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Volume 18, No. 6
GPEmu: A GPU Emulator for Faster and Cheaper Prototyping and Evaluation of Deep Learning System Research
Authors:
Meng Wang, Gus Waldspurger, Naufal Ananda, Yuyang Huang, Kemas Wiharja, John Bent, Swaminathan Sundararaman, Vijay Chidambaram, Haryadi Gunawi
Abstract
Deep learning (DL) system research is often impeded by the limited availability and expensive costs of GPUs. In this paper, we introduce GPEmu, a GPU emulator for faster and cheaper prototyping and evaluation of deep learning system research without using real GPUs. GPEmu comes with four novel features: time emulation, memory emulation, distributed system support, and sharing support. We support over 30 DL models and 6 GPU models, the largest scale to date. We demonstrate the power of GPEmu by successfully reproducing the main results of nine recent publications and easily prototyping three new micro-optimizations.
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