1 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
AFD-Ledger: Deployment Provisioning for Attention--FFN Disaggregation
Chengyu Qiu, Xiao Fu, Fengcun Li +6
Attention--Feed-Forward Network (FFN) Disaggregation (AFD) is emerging as a promising architecture for serving Mixture-of-Experts (MoE) language models. While existing AFD systems…
Surviving Partial Rank Failures in Wide Expert-Parallel MoE Inference
Xun Sun, Shaoyuan Chen, Pingchuan Ma +18
Mixture-of-Experts (MoE) serving relies on wide expert parallelism (EP) to aggregate the memory capacity and bandwidth of many GPUs within one inference instance. This efficiency c…
Seer: Online Context Learning for Fast Synchronous LLM Reinforcement Learning
Ruoyu Qin, Weiran He, Weixiao Huang +7
Reinforcement Learning (RL) has emerged as a critical technique for advancing modern Large Language Models (LLMs), yet existing synchronous RL systems face severe performance bottl…
TrEnv-X: Transparently Share Serverless Execution Environments Across Different Functions and Nodes
Jialiang Huang, Teng Ma, Zheng Liu +11
Serverless computing is renowned for its computation elasticity, yet its full potential is often constrained by the requirement for functions to operate within local and dedicated…
Efficient Graph-Based Approximate Nearest Neighbor Search Achieving: Low Latency Without Throughput Loss
Jingjia Luo, Mingxing Zhang, Kang Chen +4
The increase in the dimensionality of neural embedding models has enhanced the accuracy of semantic search capabilities but also amplified the computational demands for Approximate…