Sanmukh Kuppannagari

James C. Wyant Assistant Professor

PPOAccel: A high-throughput acceleration framework for proximal policy optimization


Journal article


Yuan Meng, Sanmukh Kuppannagari, Rajgopal Kannan, Viktor Prasanna
IEEE Transactions on Parallel and Distributed Systems, vol. 33, IEEE, 2021, pp. 2066--2078

Cite

Cite

APA   Click to copy
Meng, Y., Kuppannagari, S., Kannan, R., & Prasanna, V. (2021). PPOAccel: A high-throughput acceleration framework for proximal policy optimization. IEEE Transactions on Parallel and Distributed Systems, 33, 2066–2078.


Chicago/Turabian   Click to copy
Meng, Yuan, Sanmukh Kuppannagari, Rajgopal Kannan, and Viktor Prasanna. “PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization.” IEEE Transactions on Parallel and Distributed Systems 33 (2021): 2066–2078.


MLA   Click to copy
Meng, Yuan, et al. “PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization.” IEEE Transactions on Parallel and Distributed Systems, vol. 33, IEEE, 2021, pp. 2066–78.


BibTeX   Click to copy

@article{meng2021a,
  title = {PPOAccel: A high-throughput acceleration framework for proximal policy optimization},
  year = {2021},
  journal = {IEEE Transactions on Parallel and Distributed Systems},
  pages = {2066--2078},
  publisher = {IEEE},
  volume = {33},
  author = {Meng, Yuan and Kuppannagari, Sanmukh and Kannan, Rajgopal and Prasanna, Viktor}
}


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