22 citations · 33 across the 11 of their papers we have counts for
4 papers · 1 filter
RRTO: A High-Performance Transparent Offloading System for Model Inference in Mobile Edge Computing
Zekai Sun, Xiuxian Guan, Zheng Lin +8
Deploying Machine Learning (ML) applications on resource-constrained mobile devices remains challenging due to limited computational resources and poor platform compatibility. Whil…
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Mingzhe Du, Luu Anh Tuan, Yue Liu +6
Large Language Models (LLMs) generate functionally correct solutions but often fall short in code efficiency, a critical bottleneck for real-world deployment. In this paper, we int…
EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of LLM-Generated Code
Yuhao Qing, Boyu Zhu, Mingzhe Du +9
Existing code generation benchmarks primarily evaluate functional correctness, with limited focus on code efficiency and often restricted to a single language like Python. To addre…
Themis: Efficient Sparse Model Training Through Fully Sharded Sparse Data Parallelism
Yuhao Qing, Guichao Zhu, Lintian Lei +9
Mixture-of-Experts (MoE) scales large language models cost-effectively, but expert-parallel training suffers severe straggler effects from skewed expert loads. Current systems freq…