1 citations · 1 across the 4 of their papers we have counts for
4 papers
Event Tensor: A Unified Abstraction for Compiling Dynamic Megakernel
Hongyi Jin, Bohan Hou, Guanjie Wang +18
Modern GPU workloads, especially large language model (LLM) inference, suffer from kernel launch overheads and coarse synchronization that limit inter-kernel parallelism. Recent me…
Axe: A Simple Unified Layout Abstraction for Machine Learning Compilers
Bohan Hou, Hongyi Jin, Guanjie Wang +7
Scaling modern deep learning workloads demands coordinated placement of data and compute across device meshes, memory hierarchies, and heterogeneous accelerators. We present Axe La…
XGrammar-2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs
Linzhang Li, Yixin Dong, Guanjie Wang +3
Modern LLM agents increasingly rely on dynamic structured generation, such as tool calling and response protocols. Unlike traditional structured generation with static structures,…
Justitia: Fair and Efficient Scheduling of Task-parallel LLM Agents with Selective Pampering
Mingyan Yang, Guanjie Wang, Manqi Luo +6
LLM agents, which often comprise parallel inference tasks, are commonly adopted to solve real-world problems. When serving such task-parallel LLM agents in shared GPU servers, the…