9 citations · 10 across the 11 of their papers we have counts for
4 papers · 1 filter
Frontier: Towards Comprehensive and Accurate LLM Inference Simulation
Yicheng Feng, Xin Tan, Yangtao Deng +3
Modern LLM serving is no longer homogeneous or monolithic. Production systems now combine disaggregated execution, complex parallelism, runtime optimizations, and stateful workload…
OrchestrRL: Dynamic Compute and Network Orchestration for Disaggregated RL
Xin Tan, Yicheng Feng, Yu Zhou +3
Disaggregating the generation and training stages in RL is widely adopted to scale LLM post-training. There are two critical challenges here. First, the generation stage often beco…
DSV: Exploiting Dynamic Sparsity to Accelerate Large-Scale Video DiT Training
Xin Tan, Yuetao Chen, Yimin Jiang +6
Diffusion Transformers (DiTs) have shown remarkable performance in generating high-quality videos. However, the quadratic complexity of 3D full attention remains a bottleneck in sc…
Teola: Towards End-to-End Optimization of LLM-based Applications
Xin Tan, Yimin Jiang, Yitao Yang +1
Large language model (LLM)-based applications consist of both LLM and non-LLM components, each contributing to the end-to-end latency. Despite great efforts to optimize LLM inferen…