@inproceedings{66bdfca49d8c451faefbf24de2d09cf7,
title = "DMazeRunner: Optimizing Convolutions on Dataflow Accelerators",
abstract = "Convolution neural networks (CNNs) can be efficiently executed on dataflow accelerators. However, the vast space of executing convolutions on computational and memory resources of accelerators makes difficult for programmers to automatically and efficiently accelerate the convolutions and for architects to achieve efficient accelerator designs. We propose dMazeRunner framework, which allows users to optimize execution methods for accelerating convolution and matrix multiplication on a given architecture and to explore dataflow accelerator designs for efficiently executing CNN models. dMazeRunner determines efficient dataflows tailored for CNN layers and achieves efficient execution methods for CNN models within several seconds.",
keywords = "Hardware accelerators, deep learning, design space exploration, energy-efficiency, mapping",
author = "Shail Dave and Aviral Shrivastava and Youngbin Kim and Sasikanth Avancha and Kyoungwoo Lee",
note = "Funding Information: This research was partially supported by funding from NSF grant CCF 1723476 - NSF/Intel joint research center for Computer Assisted Programming for Heterogeneous Architectures (CAPA), and from grants NRF-2015M3C4A7065522 and 2014-3-00035, funded by MSIT. Any opinions, findings, and conclusions presented in this material are those of the authors and do not necessarily reflect the views of their employers or the sponsoring agencies. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 ; Conference date: 04-05-2020 Through 08-05-2020",
year = "2020",
month = may,
doi = "10.1109/ICASSP40776.2020.9054275",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1544--1548",
booktitle = "2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings",
}