| A Survey on Error-Bounded Lossy Compression for Scientific Datasets S Di, J Liu, K Zhao, X Liang, R Underwood, Z Zhang, M Shah, Y Huang, ... arXiv preprint arXiv:2404.02840, 2024 | 9 | 2024 |
| Offline energy-optimal llm serving: Workload-based energy models for llm inference on heterogeneous systems G Wilkins, S Keshav, R Mortier arXiv preprint arXiv:2407.04014, 2024 | 7 | 2024 |
| Hybrid Heterogeneous Clusters Can Lower the Energy Consumption of LLM Inference Workloads G Wilkins, S Keshav, R Mortier Proceedings of the 15th ACM International Conference on Future and …, 2024 | 5 | 2024 |
| FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications G Wilkins, S Di, JC Calhoun, Z Li, K Kim, R Underwood, R Mortier, ... 2024 IEEE 44th International Conference on Distributed Computing Systems …, 2024 | 4* | 2024 |
| Modeling power consumption of lossy compressed i/o for exascale hpc systems G Wilkins, JC Calhoun 2022 IEEE International Parallel and Distributed Processing Symposium …, 2022 | 3 | 2022 |
| Online Workload Allocation and Energy Optimization in Large Language Model Inference Systems G Wilkins | 1 | 2024 |
| Analyzing the energy consumption of synchronous and asynchronous checkpointing strategies G Wilkins, MJ Gossman, B Nicolae, MC Smith, JC Calhoun 2022 IEEE/ACM Third International Symposium on Checkpointing for …, 2022 | 1 | 2022 |
| To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O G Wilkins, S Di, JC Calhoun, R Underwood, F Cappello arXiv preprint arXiv:2410.23497, 2024 | | 2024 |
| Modeling Power Usage for the SZ Lossy Compressor on HPC Systems G WILKINS, J CALHOUN | | 2020 |
Jon CalhounAssociate Professor Clemson University在 clemson.edu 的电子邮件经过验证
