1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.DC2024★ 1 cited
ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
Yifan Qiao, Shu Anzai, Shan Yu +10
Large language model (LLM) serving demands low latency and high throughput, but high load variability makes it challenging to achieve high GPU utilization. In this paper, we identi…
cs.DC2024
DRust: Language-Guided Distributed Shared Memory with Fine Granularity, Full Transparency, and Ultra Efficiency
Haoran Ma, Yifan Qiao, Shi Liu +7
Despite being a powerful concept, distributed shared memory (DSM) has not been made practical due to the extensive synchronization needed between servers to implement memory cohere…
cs.CL2024★ 1 cited
Measuring Psychological Depth in Language Models
Fabrice Harel-Canada, Hanyu Zhou, Sreya Muppalla +4
Evaluations of creative stories generated by large language models (LLMs) often focus on objective properties of the text, such as its style, coherence, and diversity. While these…