2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
PTXBench: Benchmarking and Adapting LLMs for GPU Kernel Optimization with Architecture-specific PTX
Genghan Zhang, Yixin Dong, Chengze Fan +4
We introduce PTXBench, a benchmark for evaluating and adapting large language models (LLMs) to use architecture-specific PTX for GPU kernel optimization. PTXBench measures function…
Axon: A Synthesizing Superoptimizer for Tensor Programs
Akash Kothari, Shaowei Zhu, Daniel Kroening +1
Writing high performance kernels for AI accelerators requires deep expertise in tiling, instruction selection, data layout, and operator fusion placing a significant burden on prog…
MKEvolve: A Modular Multi-Agent Framework for Kernel Code Generation
Jason Yoo, Rajarshi Saha, Shaowei Zhu +3
Despite rapid progress in LLM-based code generation, writing correct and performant kernels for hardware accelerators remains a key bottleneck in scaling modern ML workloads. We pr…
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
Yile Gu, Zhen Zhang, Shaowei Zhu +4
LLM serving frameworks are quickly evolving with a complex software stack and a vast number of optimizations. The rapid development process can introduce silent errors where output…
A Categorical Basis for Robust Program Analysis
Zachary Kincaid, Shaowei Zhu
Users of program analyses expect that results change predictably in response to changes in their programs, but many analyses fail to provide such robustness. This paper introduces…