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Devesh Tiwari
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Publications
- 2024
- [i22]Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally:
Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale. CoRR abs/2402.18593 (2024) - [i21]Baolin Li, Yankai Jiang, Vijay Gadepally, Devesh Tiwari:
Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference. CoRR abs/2403.12900 (2024) - 2023
- [c98]Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally:
Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale. SoCC 2023: 588-596 - [c94]Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Kairos: Building Cost-Efficient Machine Learning Inference Systems with Heterogeneous Cloud Resources. HPDC 2023: 3-16 - [c92]Siddharth Samsi, Dan Zhao, Joseph McDonald, Baolin Li, Adam Michaleas, Michael Jones, William Bergeron, Jeremy Kepner, Devesh Tiwari, Vijay Gadepally:
From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference. HPEC 2023: 1-9 - [c89]Baolin Li, Rohan Basu Roy, Daniel Wang, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems. SC 2023: 19:1-19:15 - [c88]Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service. SC 2023: 20:1-20:15 - [i20]Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Green Carbon Footprint for Model Inference Serving via Exploiting Mixed-Quality Models and GPU Partitioning. CoRR abs/2304.09781 (2023) - [i19]Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Sustainable HPC: Modeling, Characterization, and Implications of Carbon Footprint in Modern HPC Systems. CoRR abs/2306.13177 (2023) - [i13]Siddharth Samsi, Dan Zhao, Joseph McDonald, Baolin Li, Adam Michaleas, Michael Jones, William Bergeron, Jeremy Kepner, Devesh Tiwari, Vijay Gadepally:
From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference. CoRR abs/2310.03003 (2023) - 2022
- [c82]Baolin Li, Tirthak Patel, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
MISO: exploiting multi-instance GPU capability on multi-tenant GPU clusters. SoCC 2022: 173-189 - [c78]Baolin Li, Rohin Arora, Siddharth Samsi, Tirthak Patel, William Arcand, David Bestor, Chansup Byun, Rohan Basu Roy, Bill Bergeron, John T. Holodnak, Michael Houle, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Peter Michaleas, Joseph McDonald, Lauren Milechin, Julie Mullen, Andrew Prout, Benjamin Price, Albert Reuther, Antonio Rosa, Matthew L. Weiss, Charles Yee, Daniel Edelman, Allan Vanterpool, Anson Cheng, Vijay Gadepally, Devesh Tiwari:
AI-Enabling Workloads on Large-Scale GPU-Accelerated System: Characterization, Opportunities, and Implications. HPCA 2022: 1224-1237 - [c76]Nathan C. Frey, Baolin Li, Joseph McDonald, Dan Zhao, Michael Jones, David Bestor, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
Benchmarking Resource Usage for Efficient Distributed Deep Learning. HPEC 2022: 1-8 - [c75]Baolin Li, Tirthak Patel, Vijay Gadepally, Karen Gettings, Siddharth Samsi, Devesh Tiwari:
DASH: Scheduling Deep Learning Workloads on Multi-Generational GPU-Accelerated Clusters. HPEC 2022: 1-7 - [c74]Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan C. Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, William Bergeron, Chansup Byun, Daniel Edelman, Michael Houle, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
The MIT Supercloud Workload Classification Challenge. IPDPS Workshops 2022: 708-714 - [c73]Baolin Li, Vijay Gadepally, Siddharth Samsi, Devesh Tiwari:
Characterizing Multi-Instance GPU for Machine Learning Workloads. IPDPS Workshops 2022: 724-731 - [c71]Joseph McDonald, Baolin Li, Nathan C. Frey, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models. NAACL-HLT (Findings) 2022: 1962-1970 - [c70]Rohan Basu Roy, Tirthak Patel, Vijay Gadepally, Devesh Tiwari:
Mashup: making serverless computing useful for HPC workflows via hybrid execution. PPoPP 2022: 46-60 - [i12]Nathan C. Frey, Baolin Li, Joseph McDonald, Dan Zhao, Michael Jones, David Bestor, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
Benchmarking Resource Usage for Efficient Distributed Deep Learning. CoRR abs/2201.12423 (2022) - [i11]Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan C. Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, Chansup Byun, Daniel Edelman, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
The MIT Supercloud Workload Classification Challenge. CoRR abs/2204.05839 (2022) - [i10]Joseph McDonald, Baolin Li, Nathan C. Frey, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models. CoRR abs/2205.09646 (2022) - [i9]Baolin Li, Tirthak Patel, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Using Multi-Instance GPU for Efficient Operation of Multi-Tenant GPU Clusters. CoRR abs/2207.11428 (2022) - [i8]Baolin Li, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally, Karen Gettings, Devesh Tiwari:
RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances. CoRR abs/2207.11434 (2022) - [i7]Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari:
Building Heterogeneous Cloud System for Machine Learning Inference. CoRR abs/2210.05889 (2022) - 2021
- [c64]Baolin Li, Vijay Gadepally, Siddharth Samsi, Mark S. Veillette, Devesh Tiwari:
Serving Machine Learning Inference Using Heterogeneous Hardware. HPEC 2021: 1-8 - [c63]Siddharth Samsi, Matthew L. Weiss, David Bestor, Baolin Li, Michael Jones, Albert Reuther, Daniel Edelman, William Arcand, Chansup Byun, John Holodnack, Matthew Hubbell, Jeremy Kepner, Anna Klein, Joseph McDonald, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Charles Yee, Benjamin Price, Andrew Prout, Antonio Rosa, Allan Vanterpool, Lindsey McEvoy, Anson Cheng, Devesh Tiwari, Vijay Gadepally:
The MIT Supercloud Dataset. HPEC 2021: 1-8 - [c60]Rohan Basu Roy, Tirthak Patel, Vijay Gadepally, Devesh Tiwari:
Bliss: auto-tuning complex applications using a pool of diverse lightweight learning models. PLDI 2021: 1280-1295 - [c59]Baolin Li, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally, Karen Gettings, Devesh Tiwari:
RIBBON: cost-effective and qos-aware deep learning model inference using a diverse pool of cloud computing instances. SC 2021: 24 - [i4]Siddharth Samsi, Matthew L. Weiss, David Bestor, Baolin Li, Michael Jones, Albert Reuther, Daniel Edelman, William Arcand, Chansup Byun, John Holodnack, Matthew Hubbell, Jeremy Kepner, Anna Klein, Joseph McDonald, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Charles Yee, Benjamin Price, Andrew Prout, Antonio Rosa, Allan Vanterpool, Lindsey McEvoy, Anson Cheng, Devesh Tiwari, Vijay Gadepally:
The MIT Supercloud Dataset. CoRR abs/2108.02037 (2021)
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