Urmish Thakker

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 33

Top Topics

Static Analysis

Text Compression

Top Venues

AIChallengeIoT@SenSys

IEEE Internet Things J.

Publications

Raghu Prabhakar, Ram Sivaramakrishnan, Darshan Gandhi, Yun Du, Mingran Wang, Xiangyu Song, Kejie Zhang, Tianren Gao, Angela Wang, Karen Li, Yongning Sheng, Joshua Brot, Denis Sokolov, Apurv Vivek, Calvin Leung, Arjun Sabnis, Jiayu Bai, Tuowen Zhao, Mark Gottscho, David Jackson, Mark Luttrell, Manish K. Shah, Edison Chen, Kaizhao Liang, Swayambhoo Jain, Urmish Thakker, Dawei Huang, Sumti Jairath, Kevin J. Brown, Kunle Olukotun
SambaNova SN40L: Scaling the AI Memory Wall with Dataflow and Composition of Experts. CoRR (2024)
Zoltan Csaki, Bo Li, Jonathan Li, Qiantong Xu, Pian Pawakapan, Leon Zhang, Yun Du, Hengyu Zhao, Changran Hu, Urmish Thakker
SambaLingo: Teaching Large Language Models New Languages. CoRR (2024)
Venkat Srinivasan, Darshan Gandhi, Urmish Thakker, Raghu Prabhakar
Training Large Language Models Efficiently with Sparsity and Dataflow. CoRR (2023)
Zoltan Csaki, Pian Pawakapan, Urmish Thakker, Qiantong Xu
Efficiently Adapting Pretrained Language Models To New Languages. CoRR (2023)
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini
A Survey on Federated Learning for Resource-Constrained IoT Devices. IEEE Internet Things J. 9 (1) (2022)
Victor Sanh, Albert Webson, Colin Raffel, Stephen Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush
Multitask Prompted Training Enables Zero-Shot Task Generalization. ICLR (2022)
Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Mike Tian-Jian Jiang, Alexander M. Rush
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. CoRR (2022)
Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Dragomir R. Radev, Mike Tian-Jian Jiang, Alexander M. Rush
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. ACL (demo) (2022)
Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M. Rush
Multitask Prompted Training Enables Zero-Shot Task Generalization. CoRR (2021)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Nat Jeffries, Csaba Király, Jeremy Holleman, Pietro Montino, David Kanter, Pete Warden, Danilo Pau, Urmish Thakker, Antonio Torrini, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. NeurIPS Datasets and Benchmarks (2021)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. MLSys (2021)
Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices. CoRR (2021)
Colby R. Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Király, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, Urmish Thakker, Antonio Torrini, Pete Warden, Jay Cordaro, Giuseppe Di Guglielmo, Javier M. Duarte, Stephen Gibellini, Videet Parekh, Honson Tran, Nhan Tran, Wenxu Niu, Xuesong Xu
MLPerf Tiny Benchmark. CoRR (2021)
Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
Doping: A technique for Extreme Compression of LSTM Models using Sparse Structured Additive Matrices. MLSys (2021)
Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu
Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products. ACM J. Emerg. Technol. Comput. Syst. 17 (4) (2021)
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini
Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art. CoRR (2020)
Xueqin Huang, Urmish Thakker, Dibakar Gope, Jesse G. Beu
Pushing the Envelope of Dynamic Spatial Gating technologies. AIChallengeIoT@SenSys (2020)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. CoRR (2020)
Urmish Thakker, Paul N. Whatmough, Matthew Mattina, Jesse G. Beu
Compressing Language Models using Doped Kronecker Products. CoRR (2020)
Ravi Raju, Dibakar Gope, Urmish Thakker, Jesse G. Beu
Understanding the Impact of Dynamic Channel Pruning on Conditionally Parameterized Convolutions. AIChallengeIoT@SenSys (2020)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Rank and run-time aware compression of NLP Applications. CoRR (2020)
Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David A. Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav
Benchmarking TinyML Systems: Challenges and Direction. CoRR (2020)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Rank and run-time aware compression of NLP Applications. SustaiNLP@EMNLP (2020)
Dibakar Gope, Jesse G. Beu, Urmish Thakker, Matthew Mattina
Ternary MobileNets via Per-Layer Hybrid Filter Banks. CVPR Workshops (2020)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina
Compressing RNNs for IoT devices by 15-38x using Kronecker Products. CoRR (2019)
Newsha Ardalani, Urmish Thakker, Aws Albarghouthi, Karu Sankaralingam
A Static Analysis-based Cross-Architecture Performance Prediction Using Machine Learning. CoRR (2019)
Dibakar Gope, Jesse G. Beu, Urmish Thakker, Matthew Mattina
Ternary MobileNets via Per-Layer Hybrid Filter Banks. CoRR (2019)
Jin Tao, Urmish Thakker, Ganesh Dasika, Jesse G. Beu
Skipping RNN State Updates without Retraining the Original Model. SenSys-ML (2019)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Run-Time Efficient RNN Compression for Inference on Edge Devices. EMC2@HPCA/CVPR/ISCA (2019)
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
Pushing the limits of RNN Compression. CoRR (2019)
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
Pushing the limits of RNN Compression. EMC2@NeurIPS (2019)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Run-Time Efficient RNN Compression for Inference on Edge Devices. CoRR (2019)
Urmish Thakker, Ganesh Dasika, Jesse G. Beu, Matthew Mattina
Measuring scheduling efficiency of RNNs for NLP applications. CoRR (2019)