Baolin Li

Orcid: 0000-0001-9778-1023

Affiliations:

Northeastern University, Boston, MA, USA

According to our database¹, Baolin Li authored at least 28 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2024

Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference.

[BibT_eX]

[DOI]

CoRR, 2024

EcoLife: Carbon-Aware Serverless Function Scheduling for Sustainable Computing.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2024

Interpretable Analysis of Production GPU Clusters Monitoring Data via Association Rule Mining.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

LLM Inference Serving: Survey of Recent Advances and Opportunities.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2024

Sprout: Green Generative AI with Carbon-Efficient LLM Inference.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Sustainable HPC: Modeling, Characterization, and Implications of Carbon Footprint in Modern HPC Systems.

[BibT_eX]

[DOI]

CoRR, 2023

Green Carbon Footprint for Model Inference Serving via Exploiting Mixed-Quality Models and GPU Partitioning.

[BibT_eX]

[DOI]

CoRR, 2023

Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2023

Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2023

From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Kairos: Building Cost-Efficient Machine Learning Inference Systems with Heterogeneous Cloud Resources.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, 2023

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM Symposium on Cloud Computing, SoCC 2023, 2023

2022

Building Heterogeneous Cloud System for Machine Learning Inference.

[BibT_eX]

[DOI]

CoRR, 2022

Using Multi-Instance GPU for Efficient Operation of Multi-Tenant GPU Clusters.

[BibT_eX]

[DOI]

CoRR, 2022

The MIT Supercloud Workload Classification Challenge.

[BibT_eX]

[DOI]

CoRR, 2022

Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

The MIT Supercloud Workload Classification Challenge.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Characterizing Multi-Instance GPU for Machine Learning Workloads.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

DASH: Scheduling Deep Learning Workloads on Multi-Generational GPU-Accelerated Clusters.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2022

Benchmarking Resource Usage for Efficient Distributed Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE High Performance Extreme Computing Conference, 2022

AI-Enabling Workloads on Large-Scale GPU-Accelerated System: Characterization, Opportunities, and Implications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022

Do Temperature and Humidity Exposures Hurt or Benefit Your SSDs?

[BibT_eX]

[DOI]

Adnan Maruf

Sashri Brahmakshatriya

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

MISO: exploiting multi-instance GPU capability on multi-tenant GPU clusters.

[BibT_eX]

[DOI]

Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

2021

RIBBON: cost-effective and qos-aware deep learning model inference using a diverse pool of cloud computing instances.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2021

The MIT Supercloud Dataset.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

Serving Machine Learning Inference Using Heterogeneous Hardware.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

2020

UREQA: Leveraging Operation-Aware Error Rates for Effective Quantum Circuit Mapping on NISQ-Era Quantum Computers.

[BibT_eX]

[DOI]

Proceedings of the 2020 USENIX Annual Technical Conference, 2020

Experimental evaluation of NISQ quantum computers: error measurement, characterization, and implications.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2020

Baolin Li

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