Timezone: »
Bandwidth efficient deep learning by model compression
Song Han
Fri Dec 07 06:30 AM -- 06:50 AM (PST) @
n the post-ImageNet era, computer vision and machine learning researchers are solving more complicated AI problems using larger datasets driving the demand for more computation. However, we are in the post-Moore’s Law world where the amount of computation per unit cost and power is no longer increasing at its historic rate. This mismatch between supply and demand for computation highlights the need for co-designing efficient algorithms and hardware. In this talk, I will talk about bandwidth efficient deep learning by model compression, together with efficient hardware architecture support, saving memory bandwidth, networking bandwidth, and engineer bandwidth.
Author Information
Song Han (MIT)
More from the Same Authors
-
2022 : SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models »
Song Han -
2022 Poster: Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models »
Muyang Li · Ji Lin · Chenlin Meng · Stefano Ermon · Song Han · Jun-Yan Zhu -
2022 Poster: On-Device Training Under 256KB Memory »
Ji Lin · Ligeng Zhu · Wei-Ming Chen · Wei-Chen Wang · Chuang Gan · Song Han -
2021 Poster: Memory-efficient Patch-based Inference for Tiny Deep Learning »
Ji Lin · Wei-Ming Chen · Han Cai · Chuang Gan · Song Han -
2021 Poster: Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning »
Ligeng Zhu · Hongzhou Lin · Yao Lu · Yujun Lin · Song Han -
2020 Poster: MCUNet: Tiny Deep Learning on IoT Devices »
Ji Lin · Wei-Ming Chen · Yujun Lin · john cohn · Chuang Gan · Song Han -
2020 Spotlight: MCUNet: Tiny Deep Learning on IoT Devices »
Ji Lin · Wei-Ming Chen · Yujun Lin · john cohn · Chuang Gan · Song Han -
2020 Poster: Differentiable Augmentation for Data-Efficient GAN Training »
Shengyu Zhao · Zhijian Liu · Ji Lin · Jun-Yan Zhu · Song Han -
2020 Poster: TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning »
Han Cai · Chuang Gan · Ligeng Zhu · Song Han -
2019 : Hardware-aware Neural Architecture Design for Small and Fast Models: from 2D to 3D »
Song Han -
2019 Poster: Park: An Open Platform for Learning-Augmented Computer Systems »
Hongzi Mao · Parimarjan Negi · Akshay Narayan · Hanrui Wang · Jiacheng Yang · Haonan Wang · Ryan Marcus · Ravichandra Addanki · Mehrdad Khani Shirkoohi · Songtao He · Vikram Nathan · Frank Cangialosi · Shaileshh Venkatakrishnan · Wei-Hung Weng · Song Han · Tim Kraska · Dr.Mohammad Alizadeh -
2019 Poster: Deep Leakage from Gradients »
Ligeng Zhu · Zhijian Liu · Song Han -
2019 Poster: Point-Voxel CNN for Efficient 3D Deep Learning »
Zhijian Liu · Haotian Tang · Yujun Lin · Song Han -
2019 Spotlight: Point-Voxel CNN for Efficient 3D Deep Learning »
Zhijian Liu · Haotian Tang · Yujun Lin · Song Han -
2018 : Panel disucssion »
Max Welling · Tim Genewein · Edwin Park · Song Han -
2018 : Prof. Song Han »
Song Han