From the 1 of 28 linked papers with an AI index.
10 papers · 1 filter
EasyBalance: Cross-Layer Load Balancing in Distributed MoE Inference
Yize Wu, Ke Gao, Ling Li +1
Load Balancing has emerged as a critical problem in expert-parallel distributed inference of Mixture-of-Experts (MoE) models. As routing distributions are typically skewed across e…
TuneAgent: Agentic Operating System Kernel Tuning with Reinforcement Learning
Hongyu Lin, Yuchen Li, Haoran Luo +4
Linux kernel tuning is essential for optimizing operating system (OS) performance, yet remains challenging due to the complex kernel space, sparse performance feedback, and strong…
Stable-LoRA: Stabilizing Feature Learning of Low-Rank Adaptation
Yize Wu, Ke Gao, Ling Li +1
Low-Rank Adaptation (LoRA) is a widely adopted parameter-efficient method for fine-tuning Large Langauge Models. It updates the weight matrix as , where is the ori…
ECCO: Evidence-Driven Causal Reasoning for Compiler Optimization
Haolin Pan, Lianghong Huang, Jinyuan Dong +2
Compiler auto-tuning faces a dichotomy between traditional black-box search methods, which lack semantic guidance, and recent Large Language Model (LLM) approaches, which often suf…
EasySpec: Layer-Parallel Speculative Decoding for Efficient Multi-GPU Utilization
Yize Wu, Ke Gao, Ling Li +1
Speculative decoding is an effective and lossless method for Large Language Model (LLM) inference acceleration. It employs a smaller model to generate a draft token sequence, which…
Exploring the Feasibility of End-to-End Large Language Model as a Compiler
Hongbin Zhang, Shihao Gao, Yang Liu +3
In recent years, end-to-end Large Language Model (LLM) technology has shown substantial advantages across various domains. As critical system software and infrastructure, compilers…