1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.DC2026
Democratizing MoE inference on commodity GPUs with CoMoE
Ruwen Fan, Yuezhi Zu, Minhui Xie +6
Deploying Mixture-of-Experts (MoE) models relies heavily on Expert Parallelism, which generates intense inter-GPU communication. Consequently, state-of-the-art inference systems re…
cs.PF2026
Swarm: Co-Activation Aware KVCache Offloading Across Multiple SSDs
Tuowei Wang, Liyun Chu, Ruwen Fan +1
The key-value (KV) cache has become the dominant contributor to memory consumption in large language model (LLM) inference. Although offloading KVCache from GPU high-bandwidth memo…
cs.LG2024★ 1 cited
Neuralink: Fast LLM Inference on Smartphones with Neuron Co-Activation Linking
Tuowei Wang, Ruwen Fan, Minxing Huang +6
Large Language Models (LLMs) have achieved remarkable success across various domains, yet deploying them on mobile devices remains an arduous challenge due to their extensive compu…