CUDA、cudnn和OnnxRuntime版本对应

NVIDIA - CUDA | onnxruntime

Requirements

Please reference table below for official GPU packages dependencies for the ONNX Runtime inferencing package. Note that ONNX Runtime Training is aligned with PyTorch CUDA versions; refer to the Training tab on onnxruntime.ai for supported versions.

Note: Because of CUDA Minor Version Compatibility, ONNX Runtime built with CUDA 11.8 should be compatible with any CUDA 11.x version. Please reference Nvidia CUDA Minor Version Compatibility.

ONNX Runtime CUDA cuDNN Notes
1.17 12.2 8.9.2.26 (Linux) 8.9.2.26 (Windows) The default CUDA version for ORT 1.17 is CUDA 11.8. To install CUDA 12 package, please look at Install ORT. Due to low demand on Java GPU package, only C++/C# Nuget and Python packages are released with CUDA 12.2
1.15 1.16 1.17 11.8 8.2.4 (Linux) 8.5.0.96 (Windows) Tested with CUDA versions from 11.6 up to 11.8, and cuDNN from 8.2.4 up to 8.7.0
1.14 1.13.1 1.13 11.6 8.2.4 (Linux) 8.5.0.96 (Windows) libcudart 11.4.43 libcufft 10.5.2.100 libcurand 10.2.5.120 libcublasLt 11.6.5.2 libcublas 11.6.5.2 libcudnn 8.2.4
1.12 1.11 11.4 8.2.4 (Linux) 8.2.2.26 (Windows) libcudart 11.4.43 libcufft 10.5.2.100 libcurand 10.2.5.120 libcublasLt 11.6.5.2 libcublas 11.6.5.2 libcudnn 8.2.4
1.10 11.4 8.2.4 (Linux) 8.2.2.26 (Windows) libcudart 11.4.43 libcufft 10.5.2.100 libcurand 10.2.5.120 libcublasLt 11.6.1.51 libcublas 11.6.1.51 libcudnn 8.2.4
1.9 11.4 8.2.4 (Linux) 8.2.2.26 (Windows) libcudart 11.4.43 libcufft 10.5.2.100 libcurand 10.2.5.120 libcublasLt 11.6.1.51 libcublas 11.6.1.51 libcudnn 8.2.4
1.8 11.0.3 8.0.4 (Linux) 8.0.2.39 (Windows) libcudart 11.0.221 libcufft 10.2.1.245 libcurand 10.2.1.245 libcublasLt 11.2.0.252 libcublas 11.2.0.252 libcudnn 8.0.4
1.7 11.0.3 8.0.4 (Linux) 8.0.2.39 (Windows) libcudart 11.0.221 libcufft 10.2.1.245 libcurand 10.2.1.245 libcublasLt 11.2.0.252 libcublas 11.2.0.252 libcudnn 8.0.4
1.5-1.6 10.2 8.0.3 CUDA 11 can be built from source
1.2-1.4 10.1 7.6.5 Requires cublas10-10.2.1.243; cublas 10.1.x will not work
1.0-1.1 10.0 7.6.4 CUDA versions from 9.1 up to 10.1, and cuDNN versions from 7.1 up to 7.4 should also work with Visual Studio 2017

For older versions, please reference the readme and build pages on the release branch.

For Windows, Microsoft C and C++ (MSVC) runtime libraries is also required.

相关推荐
liuyunshengsir12 小时前
从 TVM 到 TileLang:一文读懂深度学习编译器为什么走向 Tile 化
人工智能·深度学习·tvm·tilelang
海天一色y13 小时前
GSPO:重新定义大语言模型的强化学习训练范式
人工智能·机器学习·语言模型
云和数据.ChenGuang13 小时前
fastapi项目拆分实战数据模型
java·服务器·数据库·人工智能·深度学习·fastapi·强化学习
watersink13 小时前
机器学习HMM
人工智能·机器学习
东方小月13 小时前
从零开发一个 Coding Agent(九):实现 Agent 的工具调用闭环
人工智能·前端框架·node.js
Luhui Dev13 小时前
如何在 WorkBuddy 中使用大角几何:从 MCP 接入到 AI 几何作图
人工智能·数学·算法·agent·luhuidev
孙启超13 小时前
【AI应用开发】什么是混合检索(Hybrid Search)?向量检索 + BM25 关键词检索,适用场景与 RRF 融合原理
人工智能·缓存·llm·向量数据库·bm25·向量化·ai应用开发
The moon forgets13 小时前
Qwen团队提出Ego2Robot, 第一人称视频助力具身VLA训练新数据
人工智能·机器学习·音视频
szxinmai主板定制专家14 小时前
基于 RK3588 + Xilinx Kintex-7 FPGA 异构工业主控板设计方案
arm开发·人工智能·嵌入式硬件·fpga开发·zynq