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Nam Sung Kim

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Defensive ML: Defending Architectural Side-channels with Adversarial Obfuscation

Feb 03, 2023
Hyoungwook Nam, Raghavendra Pradyumna Pothukuchi, Bo Li, Nam Sung Kim, Josep Torrellas

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BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling

Mar 26, 2022
Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, Yingyan Lin

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PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication

Mar 20, 2022
Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

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Harmony: Overcoming the hurdles of GPU memory capacity to train massive DNN models on commodity servers

Feb 02, 2022
Youjie Li, Amar Phanishayee, Derek Murray, Jakub Tarnawski, Nam Sung Kim

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Bit-Parallel Vector Composability for Neural Acceleration

Apr 11, 2020
Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh

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Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training

Nov 08, 2018
Youjie Li, Mingchao Yu, Songze Li, Salman Avestimehr, Nam Sung Kim, Alexander Schwing

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GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training

Nov 08, 2018
Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander Schwing, Murali Annavaram, Salman Avestimehr

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GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks

May 10, 2018
Amir Yazdanbakhsh, Hajar Falahati, Philip J. Wolfe, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh

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