Chaojie Zhang

Senior Research SDE

出版物

表示方法:

- Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation
  
  Amey Agrawal, Haoran Qiu, Junda Chen, Íñigo Goiri, Chaojie Zhang, Rayyan Shahid, Ramachandran Ramjee, Alexey Tumanov, Esha Choukse
  
  September 2025
  
  Publication プロジェクト
- Enabling Sustainable Cloud Computing With Low-Carbon Server Design
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  IEEE Micro | June 2025, 巻45: pp. 19-28
  
  DOI Publication
- TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Esha Choukse, Haoran Qiu, Rodrigo Fonseca, Josep Torrellas, Ricardo Bianchini
  
  ASPLOS | April 2025
  
  Preprint プロジェクト
- DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Josep Torrellas, Esha Choukse
  
  HPCA | March 2025
  
  Preprint プロジェクト
- Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations
  
  Amey Agrawal, Junda Chen, Íñigo Goiri, Ramachandran Ramjee, Chaojie Zhang, Alexey Tumanov, Esha Choukse
  
  ArXiv | September 2024, 巻abs/2409.17264
  
  Preprint プロジェクト
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- Splitwise: Efficient generative LLM inference using phase splitting
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Íñigo Goiri, Saeed Maleki, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication DOI プロジェクト
- Characterizing Power Management Opportunities for LLMs in the Cloud
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ASPLOS | April 2024
  
  Publication プロジェクト
- Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference
  
  Jovan Stojkovic, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Josep Torrellas
  
  EMC2 at ASPLOS | April 2024
  
  Publication プロジェクト
- POLCA: Power Oversubscription in LLM Cloud Providers
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ArXiv | August 2023, 巻abs/2308.12908
  
  Preprint プロジェクト
- Flex: High-Availability Datacenters With Zero Reserved Power
  
  Chaojie Zhang, Alok Kumbhare, Ioannis Manousakis, Deli Zhang, Pulkit Misra, Rod Assis, Kyle Woolcock, Nithish Mahalingam, Brijesh Warrier, David Gauthier, Lalu Kunnath, Steve Solomon, Osvaldo Morales, Marcus Fontoura, Ricardo Bianchini
  
  Proceedings of the International Symposium on Computer Architecture (ISCA) | June 2021
  
  Publication プロジェクト

- Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation
  
  Amey Agrawal, Haoran Qiu, Junda Chen, Íñigo Goiri, Chaojie Zhang, Rayyan Shahid, Ramachandran Ramjee, Alexey Tumanov, Esha Choukse
  
  September 2025
  
  Publication プロジェクト
- Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations
  
  Amey Agrawal, Junda Chen, Íñigo Goiri, Ramachandran Ramjee, Chaojie Zhang, Alexey Tumanov, Esha Choukse
  
  ArXiv | September 2024, 巻abs/2409.17264
  
  Preprint プロジェクト
- Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation
  
  Amey Agrawal, Haoran Qiu, Junda Chen, Íñigo Goiri, Chaojie Zhang, Rayyan Shahid, Ramachandran Ramjee, Alexey Tumanov, Esha Choukse
  
  September 2025
  
  Publication プロジェクト
- Enabling Sustainable Cloud Computing With Low-Carbon Server Design
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  IEEE Micro | June 2025, 巻45: pp. 19-28
  
  DOI Publication
- TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Esha Choukse, Haoran Qiu, Rodrigo Fonseca, Josep Torrellas, Ricardo Bianchini
  
  ASPLOS | April 2025
  
  Preprint プロジェクト
- DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Josep Torrellas, Esha Choukse
  
  HPCA | March 2025
  
  Preprint プロジェクト
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- Splitwise: Efficient generative LLM inference using phase splitting
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Íñigo Goiri, Saeed Maleki, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication DOI プロジェクト
- Characterizing Power Management Opportunities for LLMs in the Cloud
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ASPLOS | April 2024
  
  Publication プロジェクト
- Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference
  
  Jovan Stojkovic, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Josep Torrellas
  
  EMC2 at ASPLOS | April 2024
  
  Publication プロジェクト
- POLCA: Power Oversubscription in LLM Cloud Providers
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ArXiv | August 2023, 巻abs/2308.12908
  
  Preprint プロジェクト
- Flex: High-Availability Datacenters With Zero Reserved Power
  
  Chaojie Zhang, Alok Kumbhare, Ioannis Manousakis, Deli Zhang, Pulkit Misra, Rod Assis, Kyle Woolcock, Nithish Mahalingam, Brijesh Warrier, David Gauthier, Lalu Kunnath, Steve Solomon, Osvaldo Morales, Marcus Fontoura, Ricardo Bianchini
  
  Proceedings of the International Symposium on Computer Architecture (ISCA) | June 2021
  
  Publication プロジェクト

- Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation
  
  Amey Agrawal, Haoran Qiu, Junda Chen, Íñigo Goiri, Chaojie Zhang, Rayyan Shahid, Ramachandran Ramjee, Alexey Tumanov, Esha Choukse
  
  September 2025
  
  Publication プロジェクト
- Enabling Sustainable Cloud Computing With Low-Carbon Server Design
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  IEEE Micro | June 2025, 巻45: pp. 19-28
  
  DOI Publication
- Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations
  
  Amey Agrawal, Junda Chen, Íñigo Goiri, Ramachandran Ramjee, Chaojie Zhang, Alexey Tumanov, Esha Choukse
  
  ArXiv | September 2024, 巻abs/2409.17264
  
  Preprint プロジェクト
- POLCA: Power Oversubscription in LLM Cloud Providers
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ArXiv | August 2023, 巻abs/2308.12908
  
  Preprint プロジェクト
- TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Esha Choukse, Haoran Qiu, Rodrigo Fonseca, Josep Torrellas, Ricardo Bianchini
  
  ASPLOS | April 2025
  
  Preprint プロジェクト
- DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
  
  Jovan Stojkovic, Chaojie Zhang, Íñigo Goiri, Josep Torrellas, Esha Choukse
  
  HPCA | March 2025
  
  Preprint プロジェクト
- Designing Cloud Servers for Lower Carbon
  
  Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
  
  ISCA | June 2024
  
  Publication
- Splitwise: Efficient generative LLM inference using phase splitting
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Íñigo Goiri, Saeed Maleki, Ricardo Bianchini
  
  ISCA | June 2024
  
  Publication DOI プロジェクト
- Characterizing Power Management Opportunities for LLMs in the Cloud
  
  Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Brijesh Warrier, Nithish Mahalingam, Ricardo Bianchini
  
  ASPLOS | April 2024
  
  Publication プロジェクト
- Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference
  
  Jovan Stojkovic, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Josep Torrellas
  
  EMC2 at ASPLOS | April 2024
  
  Publication プロジェクト
- Flex: High-Availability Datacenters With Zero Reserved Power
  
  Chaojie Zhang, Alok Kumbhare, Ioannis Manousakis, Deli Zhang, Pulkit Misra, Rod Assis, Kyle Woolcock, Nithish Mahalingam, Brijesh Warrier, David Gauthier, Lalu Kunnath, Steve Solomon, Osvaldo Morales, Marcus Fontoura, Ricardo Bianchini
  
  Proceedings of the International Symposium on Computer Architecture (ISCA) | June 2021
  
  Publication プロジェクト

Chaojie Zhang

出版物

Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation

Enabling Sustainable Cloud Computing With Low-Carbon Server Design

TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms

DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations

Designing Cloud Servers for Lower Carbon

Splitwise: Efficient generative LLM inference using phase splitting

Characterizing Power Management Opportunities for LLMs in the Cloud

Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

POLCA: Power Oversubscription in LLM Cloud Providers

Flex: High-Availability Datacenters With Zero Reserved Power

Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation

Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations

Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation

Enabling Sustainable Cloud Computing With Low-Carbon Server Design

TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms

DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

Designing Cloud Servers for Lower Carbon

Splitwise: Efficient generative LLM inference using phase splitting

Characterizing Power Management Opportunities for LLMs in the Cloud

Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

POLCA: Power Oversubscription in LLM Cloud Providers

Flex: High-Availability Datacenters With Zero Reserved Power

Medha: Efficient LLM Inference on Multi-Million Context Lengths Without Approximation

Enabling Sustainable Cloud Computing With Low-Carbon Server Design

Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations

POLCA: Power Oversubscription in LLM Cloud Providers

TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms

DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

Designing Cloud Servers for Lower Carbon

Splitwise: Efficient generative LLM inference using phase splitting

Characterizing Power Management Opportunities for LLMs in the Cloud

Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Flex: High-Availability Datacenters With Zero Reserved Power