Selected Publications

Full list of publications here.
Baolin Li, Yankai Jiang, Vijay Gadepally, Devesh Tiwari (2024). Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference. In EMNLP ‘24.
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Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari (2024). Interpretable Analysis of Production GPU Clusters Monitoring Data via Association Rule Mining. In IPDPS ‘24.
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Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari (2023). Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service. In SC ‘23.
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Baolin Li, Rohan Basu Roy, Daniel Wang, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari (2023). Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems. In SC ‘23.
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Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally (2023). Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale. In SoCC ‘23.
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Baolin Li, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari (2023). Kairos: Building Cost-Efficient Machine Learning Inference Systems with Heterogeneous Cloud Resources. In HPDC ‘23.
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Baolin Li, Tirthak Patel, Siddharth Samsi, Vijay Gadepally, Devesh Tiwari (2022). MISO: Exploiting Multi-Instance GPU Capability on Multi-Tenant GPU Clusters. In SoCC ‘22.
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Baolin Li, Rohin Arora, Siddharth Samsi, Tirthak Patel, Rohan Basu Roy, Vijay Gadepally, Devesh Tiwari, Et Al. (2022). AI-Enabling Workloads on Large-Scale GPU-Accelerated System: Characterization, Opportunities, and Implications. In HPCA ‘22.
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Joseph McDonald, Baolin Li, Nathan Frey, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi (2022). Great Power, Great Respobsibility: Recommendations for Reducing Energy for Training Language Models. In NAACL ‘22 Findings.
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Baolin Li, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally, Karen Gettings, Devesh Tiwari (2021). RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances. In SC ‘21.
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