Nvidia(US:NVDA) 半导体行业观察·2025-07-06 02:49Core Viewpoint - The article discusses the advancements of the open-source project Zluda, which aims to enable CUDA applications to run on non-Nvidia GPUs, thereby expanding hardware options and reducing vendor lock-in [4][7]. Group 1: Zluda Project Updates - Zluda has made significant progress in achieving CUDA compatibility on AMD, Intel, and other third-party GPUs, allowing users to run CUDA-based applications with near-native performance [4][7]. - The team behind Zluda has doubled in size, now including two full-time developers, which is expected to accelerate the project's development [4]. - Recent updates include improvements to the ROCm/HIP GPU runtime, ensuring reliable operation on both Linux and Windows platforms [5]. Group 2: Performance Enhancements - The performance of executing unmodified CUDA binaries on non-Nvidia GPUs has significantly improved, with the tool now capable of handling complex instructions with full precision [7]. - Zluda has enhanced its logging capabilities to track interactions between code and APIs, capturing previously ignored interactions and intermediate API calls [7]. - The project has made notable progress in supporting llm.c, a pure CUDA test implementation for language models like GPT-2 and GPT-3, with 16 out of 44 functions implemented [7]. Group 3: 32-bit PhysX Support - Zluda has received minor updates related to 32-bit PhysX support, focusing on efficient CUDA log collection to identify potential errors that may also affect 64-bit PhysX code [8]. - Full support for 32-bit PhysX may require significant contributions from third-party developers, indicating a collaborative effort is needed for further advancements [8].