406 citations · 429 across the 9 of their papers we have counts for
4 papers · 1 filter
Ranking Before Serving: Low-Latency LLM Serving via Pairwise Learning-to-Rank
Yiheng Tao, Yihe Zhang, Matthew Dearing +4
Efficient scheduling of large language model (LLM) inference tasks is critical for achieving low latency and high throughput, a challenge that is becoming increasingly acute with t…
Extracting Practical, Actionable Energy Insights from Supercomputer Telemetry and Logs
Melanie Cornelius, Greg Cross, Shilpika Shilpika +2
As supercomputers grow in size and complexity, power efficiency has become a critical challenge, particularly in understanding GPU power consumption within modern HPC workloads. Th…
Leveraging LLMs to Automate Energy-Aware Refactoring of Parallel Scientific Codes
Matthew T. Dearing, Yiheng Tao, Xingfu Wu +2
Large language models (LLMs) are increasingly used for generating parallel scientific codes, with a primary focus on generating functionally correct code. Recent work has focused o…
Generative AI Uses and Risks for Knowledge Workers in a Science Organization
Kelly B. Wagman, Matthew T. Dearing, Marshini Chetty
Generative AI could enhance scientific discovery by supporting knowledge workers in science organizations. However, the real-world applications and perceived concerns of generative…