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ORCIDQuentin Anthony
Quentin G. Anthony – Quentin Gregory Anthony
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2020 – today
- 2025
[j2]Quentin Anthony
, Benjamin Michalowicz, Jacob Hatef, Lang Xu, Mustafa Abduljabbar, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Understanding and Characterizing Communication Characteristics for Distributed Transformer Models. IEEE Micro 45(2): 8-17 (2025)- [i26]Lang Xu, Quentin Anthony, Jacob Hatef, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning. CoRR abs/2501.04266 (2025) - [i25]Alexis Roger, Prateek Humane, Daniel Z. Kaplan, Kshitij Gupta, Qi Sun, George Adamopoulos, Jonathan Siu Chi Lim, Quentin Anthony, Edwin Fennell, Irina Rish:
Robin: a Suite of Multi-Scale Vision-Language Models and the CHIRP Evaluation Benchmark. CoRR abs/2501.09672 (2025) - [i24]Paul Janson, Benjamin Thérien, Quentin Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky:
PyLO: Towards Accessible Learned Optimizers in PyTorch. CoRR abs/2506.10315 (2025) - [i23]Lang Xu, Kaushik Kandadi Suresh, Quentin Anthony, Nawras Alnaasan, Dhabaleswar K. Panda:
Characterizing Communication Patterns in Distributed Large Language Model Inference. CoRR abs/2507.14392 (2025) - 2024
- [j1]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [c28]Lang Xu, Quentin Anthony, Qinghua Zhou, Nawras Alnaasan, Radha Gulhane, Aamir Shafi, Hari Subramoni, Dhabaleswar K. D. K. Panda:
Accelerating Large Language Model Training with Hybrid GPU-based Compression. CCGrid 2024: 196-205 - [c27]Lang Xu, Quentin Anthony, Jacob Hatef, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning. HiPC 2024: 57-67 - [c26]Quentin Anthony, Benjamin Michalowicz, Jacob Hatef, Lang Xu, Mustafa Abdul Jabbar, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Demystifying the Communication Characteristics for Distributed Transformer Models. HOTI 2024: 57-65 - [c25]Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
The Case for Co-Designing Model Architectures with Hardware. ICPP 2024: 84-96 - [c24]Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony:
Comparative Study of Large Language Model Architectures on Frontier. IPDPS 2024: 556-569 - [c23]Jinghan Yao, Quentin Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Exploiting Inter-Layer Expert Affinity for Accelerating Mixture-of-Experts Model Inference. IPDPS 2024: 915-925 - [c22]Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang:
RedPajama: an Open Dataset for Training Large Language Models. NeurIPS 2024 - [c21]Radha Gulhane, Quentin Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Infer-HiRes: Accelerating Inference for High-Resolution Images with Quantization and Distributed Deep Learning. PEARC 2024: 5:1-5:9 - [i22]Jinghan Yao, Quentin Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Exploiting Inter-Layer Expert Affinity for Accelerating Mixture-of-Experts Model Inference. CoRR abs/2401.08383 (2024) - [i21]Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
The Case for Co-Designing Model Architectures with Hardware. CoRR abs/2401.14489 (2024) - [i20]Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony:
Comparative Study of Large Language Model Architectures on Frontier. CoRR abs/2402.00691 (2024) - [i19]Quentin Anthony, Yury Tokpanov, Paolo Glorioso, Beren Millidge:
BlackMamba: Mixture of Experts for State-Space Models. CoRR abs/2402.01771 (2024) - [i18]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR abs/2403.08763 (2024) - [i17]Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Xingjian Du, Teddy Ferdinan, Haowen Hou, Przemyslaw Kazienko, Kranthi Kiran GV, Jan Kocon, Bartlomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanislaw Wozniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu:
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence. CoRR abs/2404.05892 (2024) - [i16]Paolo Glorioso, Quentin Anthony, Yury Tokpanov, James Whittington, Jonathan Pilault, Adam Ibrahim, Beren Millidge:
Zamba: A Compact 7B SSM Hybrid Model. CoRR abs/2405.16712 (2024) - [i15]Yury Tokpanov, Beren Millidge, Paolo Glorioso, Jonathan Pilault, Adam Ibrahim, James Whittington, Quentin Anthony:
Zyda: A 1.3T Dataset for Open Language Modeling. CoRR abs/2406.01981 (2024) - [i14]Vasudev Shyam, Jonathan Pilault, Emily Shepperd, Quentin Anthony, Beren Millidge:
Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters. CoRR abs/2408.04093 (2024) - [i13]Quentin Anthony, Benjamin Michalowicz, Jacob Hatef, Lang Xu, Mustafa Abduljabbar, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Demystifying the Communication Characteristics for Distributed Transformer Models. CoRR abs/2408.10197 (2024) - [i12]Lang Xu, Quentin Anthony, Qinghua Zhou, Nawras Alnaasan, Radha Gulhane, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Accelerating Large Language Model Training with Hybrid GPU-based Compression. CoRR abs/2409.02423 (2024) - [i11]Yury Tokpanov, Paolo Glorioso, Quentin Anthony, Beren Millidge:
Zyda-2: a 5 Trillion Token High-Quality Dataset. CoRR abs/2411.06068 (2024) - [i10]Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang:
RedPajama: an Open Dataset for Training Large Language Models. CoRR abs/2411.12372 (2024) - [i9]Paolo Glorioso, Quentin Anthony, Yury Tokpanov, Anna Golubeva, Vasudev Shyam, James Whittington, Jonathan Pilault, Beren Millidge:
The Zamba2 Suite: Technical Report. CoRR abs/2411.15242 (2024) - 2023
- [c20]Quentin Anthony, Lang Xu, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
ScaMP: Scalable Meta-Parallelism for Deep Learning Search. CCGridW 2023: 346-348 - [c19]Quentin Anthony, Lang Xu, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
ScaMP: Scalable Meta-Parallelism for Deep Learning Search. CCGrid 2023: 391-402 - [c18]Alexander Havrilla, Maksym Zhuravinskyi, Duy Phung, Aman Tiwari, Jonathan Tow, Stella Biderman, Quentin Anthony, Louis Castricato:
trlX: A Framework for Large Scale Reinforcement Learning from Human Feedback. EMNLP 2023: 8578-8595 - [c17]Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Stella Biderman, Huanqi Cao, Xin Cheng, Michael Chung, Leon Derczynski, Xingjian Du, Matteo Grella, Kranthi Kiran GV, Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Jiaju Lin, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Guangyu Song, Xiangru Tang, Johan S. Wind, Stanislaw Wozniak, Zhenyuan Zhang, Qinghua Zhou, Jian Zhu, Rui-Jie Zhu:
RWKV: Reinventing RNNs for the Transformer Era. EMNLP (Findings) 2023: 14048-14077 - [c16]Stella Biderman, Hailey Schoelkopf, Quentin Gregory Anthony, Herbie Bradley, Kyle O'Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, Oskar van der Wal:
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. ICML 2023: 2397-2430 - [c15]Qinghua Zhou, Quentin Anthony, Lang Xu, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar K. Panda:
Accelerating Distributed Deep Learning Training with Compression Assisted Allgather and Reduce-Scatter Communication. IPDPS 2023: 134-144 - [c14]Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar K. Panda:
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning. IPDPS 2023: 996-1006 - [c13]Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff:
Emergent and Predictable Memorization in Large Language Models. NeurIPS 2023 - [i8]Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar K. Panda:
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning. CoRR abs/2303.08374 (2023) - [i7]Stella Biderman, Hailey Schoelkopf, Quentin Anthony, Herbie Bradley, Kyle O'Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, Oskar van der Wal:
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. CoRR abs/2304.01373 (2023) - [i6]Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff:
Emergent and Predictable Memorization in Large Language Models. CoRR abs/2304.11158 (2023) - [i5]Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Huanqi Cao, Xin Cheng, Michael Chung, Matteo Grella, Kranthi Kiran G. V., Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Xiangru Tang, Bolun Wang, Johan S. Wind, Stanislaw Wozniak, Ruichong Zhang, Zhenyuan Zhang, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu:
RWKV: Reinventing RNNs for the Transformer Era. CoRR abs/2305.13048 (2023) - [i4]Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort:
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR abs/2308.04014 (2023) - 2022
- [c12]Qinghua Zhou, Quentin Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Accelerating Broadcast Communication with GPU Compression for Deep Learning Workloads. HIPC 2022: 22-31 - [c11]Chen-Chun Chen, Kawthar Shafie Khorassani, Quentin G. Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Highly Efficient Alltoall and Alltoallv Communication Algorithms for GPU Systems. IPDPS Workshops 2022: 24-33 - [c10]Qinghua Zhou, Pouya Kousha, Quentin Anthony, Kawthar Shafie Khorassani, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Accelerating MPI All-to-All Communication with Online Compression on Modern GPU Clusters. ISC 2022: 3-25 - [c9]Arpan Jain, Aamir Shafi, Quentin Anthony, Pouya Kousha, Hari Subramoni, Dhabaleswar K. Panda:
Hy-Fi: Hybrid Five-Dimensional Parallel DNN Training on High-Performance GPU Clusters. ISC 2022: 109-130 - [i3]Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, Michael Pieler, USVSN Sai Prashanth, Shivanshu Purohit, Laria Reynolds, Jonathan Tow, Ben Wang, Samuel Weinbach:
GPT-NeoX-20B: An Open-Source Autoregressive Language Model. CoRR abs/2204.06745 (2022) - 2021
- [c8]Kawthar Shafie Khorassani, Ching-Hsiang Chu, Quentin G. Anthony, Hari Subramoni, Dhabaleswar K. Panda:
Adaptive and Hierarchical Large Message All-to-all Communication Algorithms for Large-scale Dense GPU Systems. CCGRID 2021: 113-122 - [c7]Quentin Anthony, Lang Xu, Hari Subramoni, Dhabaleswar K. D. K. Panda:
Scaling Single-Image Super-Resolution Training on Modern HPC Clusters: Early Experiences. IPDPS Workshops 2021: 923-932 - [c6]Quentin Anthony, Donglai Dai:
Evaluating Multi-Level Checkpointing for Distributed Deep Neural Network Training. SC (Workshops) 2021: 60-67 - [i2]Pouya Kousha, Quentin Anthony, Hari Subramoni, Dhabaleswar K. Panda:
Cross-layer Visualization and Profiling of Network and I/O Communication for HPC Clusters. CoRR abs/2109.08329 (2021) - 2020
- [c5]Quentin Anthony, Ammar Ahmad Awan, Arpan Jain, Hari Subramoni, Dhabaleswar K. D. K. Panda:
Efficient Training of Semantic Image Segmentation on Summit using Horovod and MVAPICH2-GDR. IPDPS Workshops 2020: 1015-1023 - [c4]Seyedeh Mahdieh Ghazimirsaeed, Quentin Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. D. K. Panda:
Accelerating GPU-based Machine Learning in Python using MPI Library: A Case Study with MVAPICH2-GDR. MLHPC/AI4S@SC 2020: 17-28 - [c3]Arpan Jain, Ammar Ahmad Awan, Asmaa M. Aljuhani, Jahanzeb Maqbool Hashmi, Quentin G. Anthony, Hari Subramoni, Dhabaleswar K. Panda, Raghu Machiraju, Anil Parwani:
GEMS: GPU-enabled memory-aware model-parallelism system for distributed DNN training. SC 2020: 45 - [c2]Ammar Ahmad Awan, Arpan Jain, Quentin Anthony, Hari Subramoni, Dhabaleswar K. Panda:
HyPar-Flow: Exploiting MPI and Keras for Scalable Hybrid-Parallel DNN Training with TensorFlow. ISC 2020: 83-103
2010 – 2019
- 2019
- [c1]Arpan Jain, Ammar Ahmad Awan, Quentin Anthony, Hari Subramoni, Dhabaleswar K. Panda:
Performance Characterization of DNN Training using TensorFlow and PyTorch on Modern Clusters. CLUSTER 2019: 1-11 - [i1]Ammar Ahmad Awan, Arpan Jain, Quentin Anthony, Hari Subramoni, Dhabaleswar K. Panda:
HyPar-Flow: Exploiting MPI and Keras for Scalable Hybrid-Parallel DNN Training using TensorFlow. CoRR abs/1911.05146 (2019)
Coauthor Index
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