2 papers
cs.DC2026
UCCL-Zip: Lossless Compression Supercharged GPU Communication
Shuang Ma, Chon Lam Lao, Zhiying Xu +8
The rapid growth of large language models (LLMs) has made GPU communication a critical bottleneck. While prior work reduces communication volume via quantization or lossy compressi…
cs.DC2026
Foundry: Template-Based CUDA Graph Context Materialization for Fast LLM Serving Cold Start
Xueshen Liu, Yongji Wu, Yuncheng Yao +3
Modern LLM service providers increasingly rely on autoscaling and parallelism reconfiguration to respond to rapidly changing workloads, but cold-start latency remains a major bottl…