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#cuda

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🌘 GitHub - tripplyons/cuda-fractal-renderer:在 CUDA 中快速渲染碎形圖
➤ 善用 GPU 平行運算,瞬息生成萬千碎形世界
github.com/tripplyons/cuda-fra
此 GitHub 專案 `tripplyons/cuda-fractal-renderer` 旨在利用 NVIDIA 的 CUDA 平臺,實現碎形圖的快速平行渲染。專案以 Python 和 CUDA C/C++ 為主要程式語言,透過 GPU 加速大幅提升運算效能。使用者可透過簡單的指令安裝依賴並執行程式,並藉由 `--seed` 參數調整碎形樣式或使用 `--grid-size` 參數一次渲染多個碎形,最終成果將輸出為 `output.png` 圖像。此專案具備清晰的設置指南與易於上手的操作流程,並採用 MIT 授權。
+ 「對於需要高效能碎形生成的研究者或視覺藝術家而言,這是一個極具價值的開源工具。易於安裝與操作,且成果令人驚艷。」
+ 「很
#開源專案 #碎形渲染 #GPU運算 #CUDA #Python

Quickly render fractals in CUDA. Contribute to tripplyons/cuda-fractal-renderer development by creating an account on GitHub.
GitHubGitHub - tripplyons/cuda-fractal-renderer: Quickly render fractals in CUDAQuickly render fractals in CUDA. Contribute to tripplyons/cuda-fractal-renderer development by creating an account on GitHub.

The Nvidia RTX A2000 6GB is not the best by far, it lacks VRAM. But computing wise and in term of fair use, with patience, @70W it is a really good deal. It is silent, small, and it works on older computers (no need to change the PSU). I think great for machine learning rather than generative AI, it supports #CUDA (it is for working e.g not gaming).

NB: non sponsored review

In a surprise move, NVIDIA is bringing CUDA to RISC-V CPUs 💥
Announced at RISC-V Summit China , this allows RISC-V processors to run CUDA drivers + logic, with NVIDIA GPUs handling compute tasks ⚙️
Enables open CPU + proprietary GPU AI systems—big for edge, HPC & China’s chipmakers 🇨🇳

A potential shift in global AI infrastructure 🌐

@itsfoss

news.itsfoss.com/nvidia-cuda-r

It's FOSS News · In a Surprise Move, NVIDIA Brings CUDA to RISC-V ProcessorsA surprise collaboration, I must say.

#NVIDIA Bringing #CUDA To #RISCV
NVIDIA's drivers and CUDA software stack are predominantly supported on x86_64 and AArch64 systems but in the past was supported on IBM POWER. This week at the RISC-V Summit China event, NVIDIA's Frans Sijstermans announced that CUDA will be coming to RISC-V.
#AMD for their part with the upstream #opensource #AMDKFD kernel compute driver can already build on RISC-V and the #ROCm user-space components can also be built on RISC-V.
phoronix.com/news/NVIDIA-CUDA-

www.phoronix.comNVIDIA Bringing CUDA To RISC-VNVIDIA announced this week that they are bringing their CUDA software to RISC-V processors.

🌕 [WIP] CUDA 後端
➤ MLX 框架 CUDA 後端開發進度更新
github.com/ml-explore/mlx/pull
此為一個正在開發中的 Pull Request,旨在為 MLX 框架添加 CUDA 後端支持。目前初步可用,已可運行教程範例。開發者建議使用 CMake 構建和測試,並提供了一些相關指令。此專案旨在利用 CUDA 的統一記憶體及 NVIDIA 硬體的廣泛應用,提升開發者體驗,可在 Mac 上本地開發並部署至超級電腦。目前僅在 Ubuntu 22.04 與 CUDA 11.6 環境下測試過。同時,開發者也歡迎社羣貢獻,特別是 ROCm 支持。
+ 真的很期待這個功能,能在 Mac 上開發,然後部署到更強大的硬體上,對研究來說非常方便!
+ 贊同頻繁合併的建議,這樣更容易維護和測試,也能更快地發現問題。
#開源專案 #機器學習 #CUDA #MLX #GitHub

GitHub[WIP] CUDA backend by zcbenz · Pull Request #1983 · ml-explore/mlxBy zcbenz