[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-5452":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":25,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":29,"readmeContent":30,"aiSummary":31,"trendingCount":16,"starSnapshotCount":16,"syncStatus":32,"lastSyncTime":33,"discoverSource":34},5452,"ZLUDA","vosen\u002FZLUDA","vosen","CUDA on non-NVIDIA GPUs","https:\u002F\u002Fvosen.github.io\u002FZLUDA\u002F",null,"Rust",14276,912,145,150,0,3,17,89,15,43.88,"Apache License 2.0",false,"master",true,[27,28],"cuda","rust","2026-06-12 02:01:10","ZLUDA is a drop-in replacement for CUDA on non-NVIDIA GPUs. ZLUDA allows running unmodified CUDA applications using non-NVIDIA GPUs with near-native performance\n\n\u003Cdiv align=\"center\">\n\n\u003C!-- 80x28 104.75x28  62x28-->\n[\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fquick start-green?style=for-the-badge&logo=readthedocs&logoColor=white\" width=\"267.5\" height=\"56\">](https:\u002F\u002Fzluda.readthedocs.io) [\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white\" width=\"209.5\" height=\"56\">](https:\u002F\u002Fdiscord.gg\u002Fsg6BNzXuc7) [\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fnews-red?style=for-the-badge&logo=book&logoColor=white\" width=\"124\" height=\"56\">](https:\u002F\u002Fvosen.github.io\u002FZLUDA\u002F)\n\n\u003Cdiv\u002F>\n","ZLUDA 是一个能够在非NVIDIA GPU上运行CUDA应用程序的替代方案。它允许用户无需修改代码即可在非NVIDIA GPU上以接近原生的性能执行CUDA应用，主要通过Rust语言实现，确保了高性能与安全性。该项目特别适用于那些希望利用手头已有但并非NVIDIA品牌的GPU资源来进行并行计算任务的研究人员和开发者们。无论是进行深度学习训练、科学模拟还是其他需要大量并行处理能力的工作，ZLUDA都提供了一个灵活且高效的解决方案。",2,"2026-06-11 03:03:26","top_language"]