CUDA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
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A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
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May 20, 2024 - Python
Windows & Linux automated scripts & docs to improve your UX & productivity (including WSL2, conda, GPU drivers & development tools)
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Install Immich in LXC with optional CUDA support
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Documentation of the spatially explicit biodiversity simulation necsim-rust
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(GPU accelerated) Multi-arch (linux/amd64, linux/arm64/v8) JupyterLab R docker images. Please submit Pull Requests to the GitLab repository. Mirror of
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Spatially explicit biodiversity simulations using a parallel library written in Rust
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A high-throughput and memory-efficient inference and serving engine for LLMs
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(GPU accelerated) Multi-arch (linux/amd64, linux/arm64/v8) R docker images. Please submit Pull Requests to the GitLab repository. Mirror of
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Open Voice OS Status Page
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Molecular dynamics and Monte Carlo soft matter simulation on GPUs.
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cuGraph - RAPIDS Graph Analytics Library
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RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
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May 20, 2024 - Cuda
Created by Nvidia
Released June 23, 2007
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- Website
- developer.nvidia.com/cuda-zone
- Wikipedia
- Wikipedia