K-Search
K-Search has a backend for Apple Silicon’s MLX framework K-Search uses Gemini 3.5 Pro Preview to reason about GPU kernel optimizations and generate candidate kernels Shiyi Cao is the developer of K-Search K-Search was evaluated on CUDA kernels from FlashInfer K-Search was compared against OpenEvolve K-Search was compared against ShinkaEvolve K-Search achieves a 0.97× speedup over the native MLX Attention kernel on Apple Silicon K-Search achieves a 20× prefill speedup over the community mlx‑lm implementation on the Mamba SSM kernel K-Search optimizes CUDA kernels by using existing CUDA kernel knowledge as a starting point Dr. Marily Nika is affiliated with AI Product Academy OpenAI produced a proof of Stein's restriction conjecture· Graphiti 生成的实体摘要
关系变化
按生效时间- OpenAIPRODUCED PROOF FORK-Search
OpenAI produced a proof of Stein's restriction conjecture
- Microsoft ThinkingBoxAFFILIATED WITHK-Search
Dr. Marily Nika is affiliated with AI Product Academy
- K-SearchEVALUATED ONFlashInfer
K-Search was evaluated on CUDA kernels from FlashInfer
- K-SearchCOMPARED WITHShinkaEvolve
K-Search was compared against ShinkaEvolve
- K-SearchOPTIMIZESCUDA
K-Search optimizes CUDA kernels by using existing CUDA kernel knowledge as a starting point
- K-SearchACHIEVES SPEEDUP OVERMLX-lm implementation
K-Search achieves a 20× prefill speedup over the community mlx‑lm implementation on the Mamba SSM kernel
- K-SearchHAS BACKEND FORMLX
K-Search has a backend for Apple Silicon’s MLX framework
- K-SearchCOMPARED WITHOpenEvolve
K-Search was compared against OpenEvolve
- K-SearchACHIEVES SPEEDUP OVERMLX Attention kernel
K-Search achieves a 0.97× speedup over the native MLX Attention kernel on Apple Silicon
- Shiyi CaoDEVELOPER OFK-Search
Shiyi Cao is the developer of K-Search
- K-SearchUSESNVIDIA Omniverse libraries
K-Search uses Gemini 3.5 Pro Preview to reason about GPU kernel optimizations and generate candidate kernels
关系是 Graphiti 从报道中提取的事实陈述，不是原文引述；失效时间表示后来的报道显示这条关系已不成立。