Alban Desmaison

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 29

Top Topics

Sparse Linear Systems

Graphics Processing Units

Top Venues

Publications

Dongning Ma, Fan Fred Lin, Alban Desmaison, Joel Coburn, Daniel Moore, Sriram Sankar, Xun Jiao
Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations. ASPLOS (3) (2024)
Jason Ansel, Edward Z. Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, Soumith Chintala
PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. ASPLOS (2) (2024)
Yanli Zhao, Andrew Gu, Rohan Varma, Liang Luo, Chien-Chin Huang, Min Xu, Less Wright, Hamid Shojanazeri, Myle Ott, Sam Shleifer, Alban Desmaison, Can Balioglu, Bernard Nguyen, Geeta Chauhan, Yuchen Hao, Shen Li
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. CoRR (2023)
Yanli Zhao, Andrew Gu, Rohan Varma, Liang Luo, Chien-Chin Huang, Min Xu, Less Wright, Hamid Shojanazeri, Myle Ott, Sam Shleifer, Alban Desmaison, Can Balioglu, Pritam Damania, Bernard Nguyen, Geeta Chauhan, Yuchen Hao, Ajit Mathews, Shen Li
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel. Proc. VLDB Endow. 16 (12) (2023)
Dongning Ma, Xun Jiao, Fan Fred Lin, Mengshi Zhang, Alban Desmaison, Thomas Sellinger, Daniel Moore, Sriram Sankar
Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors. CoRR (2023)
Shen Li, Pritam Damania, Luca Wehrstedt, Rohan Varma, Omkar Salpekar, Pavel Belevich, Howard Huang, Yanli Zhao, Lucas Hosseini, Wanchao Liang, Hongyi Jia, Shihao Xu, Satendra Gera, Alisson G. Azzolini, Guoqiang Jerry Chen, Zachary DeVito, Chaoyang He, Amir Ziashahabi, Alban Desmaison, Edward Z. Yang, Gregory Chanan, Brian Vaughan, Manoj Krishnan, Joseph S. Spisak, Salman Avestimehr, Soumith Chintala
PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. MLSys (2023)
Xun Jiao, Fan Fred Lin, Matt Xiao, Alban Desmaison, Daniel Moore, Sriram Sankar
Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study. RTSS (2023)
Frédéric Magoulès, Abal-Kassim Cheik Ahamed, Alban Desmaison, Jean-Christophe Léchenet, François Mayer, Haifa Ben Salem, Thomas Zhu
Power Consumption Analysis of Parallel Algorithms on GPUs. CoRR (2021)
Abal-Kassim Cheik Ahamed, Alban Desmaison, Frédéric Magoulès
Fast and Green Computing with Graphics Processing Units for solving Sparse Linear Systems. CoRR (2021)
Alessandro De Palma, Rudy Bunel, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition. CoRR (2021)
Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Lagrangian Decomposition for Neural Network Verification. UAI (2020)
Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Lagrangian Decomposition for Neural Network Verification. CoRR (2020)
Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. SIAM J. Imaging Sci. 12 (1) (2019)
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
PyTorch: An Imperative Style, High-Performance Deep Learning Library. CoRR (2019)
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
PyTorch: An Imperative Style, High-Performance Deep Learning Library. NeurIPS (2019)
Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials. CoRR (2018)
N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. CoRR (2017)
Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
Learning to superoptimize programs. ICLR (Poster) (2017)
Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
Efficient Linear Programming for Dense CRFs. CVPR (2017)
Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. NIPS (2017)
Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Continuous Relaxations for Dense CRF. ECCV (2) (2016)
Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
Learning to superoptimize programs. CoRR (2016)
Rudy Bunel, Alban Desmaison, Pushmeet Kohli, Philip H. S. Torr, Pawan Kumar Mudigonda
Adaptive Neural Compilation. CoRR (2016)
Rudy Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr
Adaptive Neural Compilation. NIPS (2016)
N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
Inducing Interpretable Representations with Variational Autoencoders. CoRR (2016)
Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli
Learning to superoptimize programs - Workshop Version. CoRR (2016)
Alban Desmaison, Rudy Bunel, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Continuous Relaxations for Dense CRF. CoRR (2016)
Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, Philip H. S. Torr
Playing Doom with SLAM-Augmented Deep Reinforcement Learning. CoRR (2016)
Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
Efficient Linear Programming for Dense CRFs. CoRR (2016)
Abal-Kassim Cheik Ahamed, Alban Desmaison, Frédéric Magoulès
Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems. HPCC/CSS/ICESS (2014)
Frédéric Magoulès, Abal-Kassim Cheik Ahamed, Alban Desmaison, Jean-Christophe Léchenet, François Mayer, Haifa Ben Salem, Thomas Zhu
Power Consumption Analysis of Parallel Algorithms on GPUs. HPCC/CSS/ICESS (2014)