Publications

(2023). Accelerating Deep Neural Network guided MCTS using Adaptive Parallelism. In ACM/IA3(SC'23 Workshop).

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(2022). Accelerator Design and Exploration for Deformable Convolution Networks. In IEEE/SiPS.

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(2022). Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. In IEEE/FPL.

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(2022). FPGA Acceleration of Deep Reinforcement Learning Using On-chip Replay Management. In ACM/CF.

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(2021). PPOAccel: A High-Throughput Acceleration Framework for Proximal Policy Optimization. In IEEE/TPDS.

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(2021). FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning Algorithms. In IEEE/FPL.

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(2021). How to Avoid Zero-spacing in Fractionally-Strided Convolution? A Hardware-Algorithm Co-design Methodology. In IEEE/HiPC.

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(2021). Dynamap: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference. In ACM/FPGA.

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(2020). How to Efficiently Train Your AI Agent? Characterizing and Evaluating Reep Reinforcement Learning on Heterogeneous Platforms. In IEEE/HPEC.

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(2020). QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. In IEEE/IPDPSW.

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(2020). Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms. In IEEE/FCCM.

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