Yuan Meng

IEEE Trans. Parallel Distributed Syst., June, 2023

A Software-Hardware Co-Optimized Toolkit for Deep Reinforcement Learning on Heterogeneous Platforms.

[BibT_eX]

[DOI]

CoRR, 2023

Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism.

[BibT_eX]

[DOI]

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Accelerating Multi-Agent DDPG on CPU-FPGA Heterogeneous Platform.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

A Framework for Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform via on-chip Dynamic Tree Management.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2023

Characterizing Speed Performance of Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 12th International Conference on Data Science, 2023

2022

PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Parallel Distributed Syst., 2022

Accelerator Design and Exploration for Deformable Convolution Networks.

[BibT_eX]

[DOI]

Hongjiang Men

Proceedings of the IEEE Workshop on Signal Processing Systems, 2022

End to End Framework for CNN Acceleration on FPGAs with Dynamic Algorithm Mapping.

[BibT_eX]

[DOI]

Haomei Liu

Sanmukh Rao Kuppannagari

Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, 2022

Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications, 2022

Accelerating Deformable Convolution Networks.

[BibT_eX]

[DOI]

Hongjiang Men

Proceedings of the 30th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2022

FPGA acceleration of deep reinforcement learning using on-chip replay management.

[BibT_eX]

[DOI]

Chi Zhang

Proceedings of the CF '22: 19th ACM International Conference on Computing Frontiers, Turin, Italy, May 17, 2022

2021

How to Avoid Zero-Spacing in Fractionally-Strided Convolution? A Hardware-Algorithm Co-Design Methodology.

[BibT_eX]

[DOI]

Proceedings of the 28th IEEE International Conference on High Performance Computing, 2021

FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning Algorithms.

[BibT_eX]

[DOI]

Nathaniel Peura

Proceedings of the 31st International Conference on Field-Programmable Logic and Applications, 2021

DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference.

[BibT_eX]

[DOI]

Proceedings of the FPGA '21: The 2021 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, Virtual Event, USA, February 28, 2021

2020

How to Efficiently Train Your AI Agent? Characterizing and Evaluating Deep Reinforcement Learning on Heterogeneous Platforms.

[BibT_eX]

[DOI]

Yang Yang

Proceedings of the 2020 IEEE High Performance Extreme Computing Conference, 2020

QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators.

[BibT_eX]

[DOI]

Rachit Rajat

Ajitesh Srivastava

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms.

[BibT_eX]

[DOI]