Yuan Meng

26 papers A 3B 3C 1Misc 3Journal 8Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
An Acceleration Framework for Deep Reinforcement Learning Using Heterogeneous Systems.
IEEE Trans. Parallel Distributed Syst.
Yuan Meng, Mahesh A. Iyer, Viktor K. Prasanna
2024 B conf
A Heterogeneous Acceleration System for Attention-Based Multi-Agent Reinforcement Learning.
FPL
Samuel Wiggins, Yuan Meng, Mahesh A. Iyer, Viktor K. Prasanna
2024 — conf
PEARL: Enabling Portable, Productive, and High-Performance Deep Reinforcement Learning using Heterogeneous Platforms.
CF
Yuan Meng, Michael Kinsner, Deshanand P. Singh, Mahesh A. Iyer, Viktor K. Prasanna
2023 J jnl
A Framework for Mapping DRL Algorithms With Prioritized Replay Buffer Onto Heterogeneous Platforms.
IEEE Trans. Parallel Distributed Syst.
Chi Zhang, Yuan Meng, Viktor K. Prasanna
2023 A conf
A Framework for Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform via on-chip Dynamic Tree Management.
FPGA
Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2023 J jnl
A Software-Hardware Co-Optimized Toolkit for Deep Reinforcement Learning on Heterogeneous Platforms.
CoRR
Yuan Meng, Michael Kinsner, Deshanand P. Singh, Mahesh A. Iyer, Viktor K. Prasanna
2023 — conf
Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism.
SC Workshops
Yuan Meng, Qian Wang, Tianxin Zu, Viktor K. Prasanna
2023 J jnl
Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism.
CoRR
Yuan Meng, Qian Wang, Tianxin Zu, Viktor K. Prasanna
2023 — conf
Accelerating Multi-Agent DDPG on CPU-FPGA Heterogeneous Platform.
HPEC
Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2023 C conf
Characterizing Speed Performance of Multi-Agent Reinforcement Learning.
DATA
Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2023 J jnl
Characterizing Speed Performance of Multi-Agent Reinforcement Learning.
CoRR
Samuel Wiggins, Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2022 Misc conf
Accelerating Deformable Convolution Networks.
FCCM
Yuan Meng, Hongjiang Men, Viktor K. Prasanna
2022 B conf
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform.
FPL
Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2022 J jnl
Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform.
CoRR
Yuan Meng, Rajgopal Kannan, Viktor K. Prasanna
2022 — conf
Accelerator Design and Exploration for Deformable Convolution Networks.
SiPS
Yuan Meng, Hongjiang Men, Viktor K. Prasanna
2022 — conf
End to End Framework for CNN Acceleration on FPGAs with Dynamic Algorithm Mapping.
IC3
Haomei Liu, Yuan Meng, Sanmukh Rao Kuppannagari, Viktor K. Prasanna
2022 — conf
FPGA acceleration of deep reinforcement learning using on-chip replay management.
CF
Yuan Meng, Chi Zhang, Viktor K. Prasanna
2022 J jnl
PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization.
IEEE Trans. Parallel Distributed Syst.
Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna
2021 A conf
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference.
FPGA
Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna
2021 B conf
FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning Algorithms.
FPL
Nathaniel Peura, Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna
2021 Misc conf
How to Avoid Zero-Spacing in Fractionally-Strided Convolution? A Hardware-Algorithm Co-Design Methodology.
HiPC
Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna
2020 Misc conf
Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms.
FCCM
Yuan Meng, Sanmukh R. Kuppannagari, Viktor K. Prasanna
2020 J jnl
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference.
CoRR
Yuan Meng, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna
2020 — conf
How to Efficiently Train Your AI Agent? Characterizing and Evaluating Deep Reinforcement Learning on Heterogeneous Platforms.
HPEC
Yuan Meng, Yang Yang, Sanmukh R. Kuppannagari, Rajgopal Kannan, Viktor K. Prasanna
2020 A conf
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators.
FPGA
Rachit Rajat, Yuan Meng, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Viktor K. Prasanna, Rajgopal Kannan
2020 — conf
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators.
IPDPS Workshops
Yuan Meng, Sanmukh R. Kuppannagari, Rachit Rajat, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna