Benoit Steiner

32 papers A* 9A 1B 1Journal 18Unranked 3
YearRankTypeTitle / Venue / Authors
2023 A* conf
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction.
ICML
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian
2023 J jnl
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction.
CoRR
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh Leather, Yuandong Tian
2023 B conf
Local Branching Relaxation Heuristics for Integer Linear Programs.
CPAIOR
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
2023 A* conf
MODeL: Memory Optimizations for Deep Learning.
ICML
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn, James Hegarty
2023 J jnl
Measuring Faithfulness in Chain-of-Thought Reasoning.
CoRR
Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamile Lukosiute, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, Ethan Perez
2023 A* conf
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning.
ICML
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
2023 J jnl
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning.
CoRR
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
2023 J jnl
Studying Large Language Model Generalization with Influence Functions.
CoRR
Roger B. Grosse, Juhan Bae, Cem Anil, Nelson Elhage, Alex Tamkin, Amirhossein Tajdini, Benoit Steiner, Dustin Li, Esin Durmus, Ethan Perez, Evan Hubinger, Kamile Lukosiute, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, Samuel R. Bowman
2023 A* conf
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems.
ICML
Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
2022 — conf
A graph neural network-based performance model for deep learning applications.
MAPS@PLDI
Shikhar Singh, James Hegarty, Hugh Leather, Benoit Steiner
2022 A conf
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research.
CGO
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
2022 A* conf
Flashlight: Enabling Innovation in Tools for Machine Learning.
ICML
Jacob D. Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Y. Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, Benoit Steiner, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert
2022 J jnl
Flashlight: Enabling Innovation in Tools for Machine Learning.
CoRR
Jacob Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Y. Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, Benoit Steiner, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert
2022 J jnl
Local Branching Relaxation Heuristics for Integer Linear Programs.
CoRR
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
2022 J jnl
LoopStack: a Lightweight Tensor Algebra Compiler Stack.
CoRR
Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski
2022 J jnl
OLLA: Decreasing the Memory Usage of Neural Networks by Optimizing the Lifetime and Location of Arrays.
CoRR
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn, James Hegarty
2022 J jnl
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems.
CoRR
Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
2021 J jnl
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research.
CoRR
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
2021 A* conf
Learning Space Partitions for Path Planning.
NeurIPS
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
2021 J jnl
Learning Space Partitions for Path Planning.
CoRR
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
2021 J jnl
Using Graph Neural Networks to model the performance of Deep Neural Networks.
CoRR
Shikhar Singh, Benoit Steiner, James Hegarty, Hugh Leather
2021 — conf
Value Learning for Throughput Optimization of Deep Learning Workloads.
MLSys
Benoit Steiner, Chris Cummins, Horace He, Hugh Leather
2020 J jnl
Value Function Based Performance Optimization of Deep Learning Workloads.
CoRR
Benoit Steiner, Chris Cummins, Horace He, Hugh Leather
2019 J jnl
Learning to optimize halide with tree search and random programs.
ACM Trans. Graph.
Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley
2019 A* conf
PyTorch: An Imperative Style, High-Performance Deep Learning Library.
NeurIPS
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
2019 J jnl
PyTorch: An Imperative Style, High-Performance Deep Learning Library.
CoRR
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
2018 — conf
A Hierarchical Model for Device Placement.
ICLR (Poster)
Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean
2017 A* conf
Device Placement Optimization with Reinforcement Learning.
ICML
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean
2017 J jnl
Device Placement Optimization with Reinforcement Learning.
CoRR
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean
2016 A* conf
TensorFlow: A System for Large-Scale Machine Learning.
OSDI
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng
2016 J jnl
TensorFlow: A system for large-scale machine learning.
CoRR
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang
2016 J jnl
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.
CoRR
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng