Grant Wilkins

According to our database, Grant Wilkins authored at least 10 papers between 2022 and 2026.

Collaborative distances:

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

2026

EasyRider: Mitigating Power Transients in Datacenter-Scale Training Workloads.

Dillon Jensen, Obidike Nnorom Jr., Grant Wilkins, Hugo Budd, Ram Rajagopal, Juan Rivas-Davila, Philip Levis

CoRR, April, 2026

From Servers to Sites: Compositional Power Trace Generation of LLM Inference for Infrastructure Planning.

Grant Wilkins, Fiodar Kazhamiaka, Ram Rajagopal

CoRR, March, 2026

2025

A Survey on Error-Bounded Lossy Compression for Scientific Datasets.

Sheng Di, Jinyang Liu, Kai Zhao, Xin Liang, Robert Underwood, Zhaorui Zhang, Milan Shah, Yafan Huang, Jiajun Huang, Xiaodong Yu, Congrong Ren, Hanqi Guo, Grant Wilkins, Dingwen Tao, Jiannan Tian, Sian Jin, Zizhe Jian, Daoce Wang, Md Hasanur Rahman, Boyuan Zhang, Shihui Song, Jon Calhoun, Guanpeng Li, Kazutomo Yoshii, Khalid Ayedh Alharthi, Franck Cappello

ACM Comput. Surv., November, 2025

To Compress or Not to Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O.

Grant Wilkins, Sheng Di, Jon C. Calhoun, Robert Underwood, Franck Cappello

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2025

2024

Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems.

Grant Wilkins, Srinivasan Keshav, Richard Mortier

CoRR, 2024

A Survey on Error-Bounded Lossy Compression for Scientific Datasets.

Sheng Di, Jinyang Liu, Kai Zhao, Xin Liang, Robert Underwood, Zhaorui Zhang, Milan Shah, Yafan Huang, Jiajun Huang, Xiaodong Yu, Congrong Ren, Hanqi Guo, Grant Wilkins, Dingwen Tao, Jiannan Tian, Sian Jin, Zizhe Jian, Daoce Wang, Md Hasanur Rahman, Boyuan Zhang, Jon C. Calhoun, Guanpeng Li, Kazutomo Yoshii, Khalid Ayedh Alharthi, Franck Cappello

CoRR, 2024

FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications.

Grant Wilkins, Sheng Di, Jon C. Calhoun, Zilinghan Li, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello

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

Hybrid Heterogeneous Clusters Can Lower the Energy Consumption of LLM Inference Workloads.

Grant Wilkins, Srinivasan Keshav, Richard Mortier

Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 2024

2023

Efficient Communication in Federated Learning Using Floating-Point Lossy Compression.

Grant Wilkins, Sheng Di, Jon C. Calhoun, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello

CoRR, 2023

2022

Modeling Power Consumption of Lossy Compressed I/O for Exascale HPC Systems.

Grant Wilkins, Jon C. Calhoun

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