718 citations · 881 across the 22 of their papers we have counts for
6 papers · 1 filter
CAKE: Compiler-Agent Co-Design for Frontier Kernel Evolution
Zihao Ye, Yingyi Huang, Hongyi Jin +11
GPU kernel agents and GPU programming languages have advanced separately, leaving expert kernels difficult to reproduce. Agents usually treat the compiler as a fixed black box and…
Tabular Numeric Stretch Transformation
Zihao Ye, Juyong Kim, Johnna Sundberg +2
Tabular data presents unique challenges for deep learning due to its heterogeneous nature, where numeric features exhibit diverse distributions, scales, and statistical properties.…
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…
AVO: Agentic Variation Operators for Autonomous Evolutionary Search
Terry Chen, Zhifan Ye, Bing Xu +20
Agentic Variation Operators (AVO) are a new family of evolutionary variation operators that replace the fixed mutation, crossover, and hand-designed heuristics of classical evoluti…
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…
FlashInfer-Bench: Building the Virtuous Cycle for AI-driven LLM Systems
Shanli Xing, Yiyan Zhai, Alexander Jiang +10
Recent advances show that large language models (LLMs) can act as autonomous agents capable of generating GPU kernels, but integrating these AI-generated kernels into real-world in…