Jonathan Koomey

According to our database, Jonathan Koomey authored at least 6 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation.

Alex C. Newkirk, Jared Fernandez, Jonathan Koomey, Imran Latif, Emma Strubell, Arman Shehabi, Constantine Samaras

CoRR, June, 2025

Generalizable Machine Learning Models for Predicting Data Center Server Power, Efficiency, and Throughput.

Nuoa Lei, Arman Shehabi, Jun Lu, Zhi Cao, Jonathan Koomey, Sarah Smith, Eric R. Masanet

CoRR, March, 2025

Single-Node Power Demand During AI Training: Measurements on an 8-GPU NVIDIA H100 System.

Imran Latif, Alex C. Newkirk, Matthew R. Carbone, Arslan Munir, Yuewei Lin, Jonathan Koomey, Xi Yu, Zhihua Dong

IEEE Access, 2025

2024

Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node.

Imran Latif, Alex C. Newkirk, Matthew R. Carbone, Arslan Munir, Yuewei Lin, Jonathan Koomey, Xi Yu, Zhiuha Dong

CoRR, 2024

2022

Exploring the black box: Applying macro decomposition tools for scenario comparisons.

Jonathan Koomey, Zachary Schmidt, Karl Hausker, Dan Lashof

Environ. Model. Softw., 2022

2019

Inside the Black Box: Understanding key drivers of global emission scenarios.

Jonathan Koomey, Zachary Schmidt, Holmes Hummel, John Weyant

Environ. Model. Softw., 2019