配置ubuntu17.1+CUDA9.2的caffe环境，CUDA sample编译完成，执行到./deviceQuery时报错:CUDA driver version is insufficient

Also easy solution is to download some old version of cuda sdk, according to current driver version. 3.0 3.1 are good too. I forgor to mention that I did install the toolkit, and it went without problems. I'll try some old drivers, I guess! Thanks. EDIT: Hm, maybe a stupid question, but where can I find old versions of cuda SDK?

I already had some cudaRuntime Error 35 driver version insufficient · Learn. 2018年10月15日 cat /proc/driver/nvidia/version看了一下服务器的显卡驱动，发现版本比较低，是 352.39，只能安装CUDA7.5，而我装的是8.0的cuda。 CUDA driver version is insufficient for CUDA runtime version. 2019-08-08 21:17 375 查看. [code]conda install -c anaconda tensorflow-gpu [code]conda install -c  I can read before close, "Error: Cuda driver version is insufficient for cuda runtime version" I don't understand. I have install CUDA 9.1 and  Mar 24, 2020 CUDA Device Query (Runtime API) version (CUDART static linking). cudaGetDeviceCount returned 35.

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Note that you don’t need a local CUDA toolkit installation, as the conda binaries and pip wheels will ship with their CUDA (cudnn, NCCL, etc.) runtimes. Yeah every time encountering “CUDA driver version is insufficient for CUDA runtime version” I have to reinstall CUDA, just want to double check and confirm it is the case ResidentMario December 29, 2020, 8:31pm #10 -> CUDA driver version is insufficient for CUDA runtime version But this error is misleading, by selecting back the Performance Mode (NVIDIA GPU) with nvidia-settings utility the problem disappears. In my case I had not a driver version problem but I simply need to re-enable the Nvidia GPU. So I have sufficient confident to believe the "CUDA driver version is insufficient for CUDA runtime version" error is related to cutorch and not cuda. Probably some bug or checksum error in cutorch. CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device (s) CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 35 -> CUDA driver version is insufficient for CUDA runtime version Result = FAIL The text was updated successfully, but these errors were encountered: -> CUDA driver version is insufficient for CUDA runtime version Result = FAIL The text was updated successfully, but these errors were encountered: Running a CUDA container requires a machine with at least one CUDA-capable GPU and a driver compatible with the CUDA toolkit version you are using. mforde84 closed this on Aug 24, 2018 nicolefinnie commented on Oct 13, 2018 @mforde84 @tensorflowbutler CUDA driver version is insufficient for CUDA runtime version.

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CUDA driver version is insufficient for CUDA runtime version. I have no idea how to solve this problem. Also, I don’t want to run the code directly on my system, I want to run in on docker. Source: StackOverflow

2018年10月15日 cat /proc/driver/nvidia/version看了一下服务器的显卡驱动，发现版本比较低，是 352.39，只能安装CUDA7.5，而我装的是8.0的cuda。 CUDA driver version is insufficient for CUDA runtime version. 2019-08-08 21:17 375 查看. [code]conda install -c anaconda tensorflow-gpu [code]conda install -c  I can read before close, "Error: Cuda driver version is insufficient for cuda runtime version" I don't understand.

CUDA driver version is insufficient for CUDA runtime version 简单的讲, cuda驱动版本和cuda库的版本不一致. 常见错误场景: cuda驱动最高支持cuda90的库, 如果用cuda91的库, 会出现这种情况 两种解决思路: 升级cuda驱动 降低cuda91库为cuda90 建议选择第二种解决方案.

CUDA driver version is insufficient for CUDA runtime version 简单的讲, cuda驱动版本和cuda库的版本不一致. 常见错误场景: cuda 驱动最高支持 cuda 90的库, 如果用 cuda 91的库, 会出现这种情况 两种 解决 思路: 升级 cuda 驱动 降低 cuda 91库为 cuda 90 建议选择第二种 解决 方案. Dual GPU -> Intel Iris Pro and NVIDIA GeForce GT 750M (CUDA compatible) Python Build from source. I could follow the instructions without any problems.

You can find the required NVIDIA driver for each CUDA version here in Table1. Note that you don’t need a local CUDA toolkit installation, as the conda binaries and pip wheels will ship with their CUDA (cudnn, NCCL, etc.) runtimes. Yeah every time encountering “CUDA driver version is insufficient for CUDA runtime version” I have to reinstall CUDA, just want to double check and confirm it is the case ResidentMario December 29, 2020, 8:31pm #10 -> CUDA driver version is insufficient for CUDA runtime version But this error is misleading, by selecting back the Performance Mode (NVIDIA GPU) with nvidia-settings utility the problem disappears. In my case I had not a driver version problem but I simply need to re-enable the Nvidia GPU. So I have sufficient confident to believe the "CUDA driver version is insufficient for CUDA runtime version" error is related to cutorch and not cuda.
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From: David Hardy (dhardy_at_ks 解决CUDA driver version is insufficient for CUDA runtime version 2018-10-15 15:42 − ###问题 在服务器上安装mxne的GPU版本 ```bash sudo pip install mxnet-cu80==1.2.1 ``` 然后在gpu上创建数据 ```python import mxnet as mx mx.nd.array([0], ctx = mx.gpu()) ``` 发 Also easy solution is to download some old version of cuda sdk, according to current driver version. 3.0 3.1 are good too. I forgor to mention that I did install the toolkit, and it went without problems. I'll try some old drivers, I guess! Thanks.

2020-02-01 2020-02-29 kernel launch failure : CUDA driver version is insufficient for CUDA runtime version." While trying to run an example source code. Also happens for the function cutilSafeCall.
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(thomasASUS): CUDA driver version is insufficient for CUDA runtime version Hi again, I managed to install the latest NVIDIA drivers (NVIDIA-Linux-x86_64-304.51)

首先看linux中GPU的驱动版本 $ nvidia-smi 可以看到驱动版本是396.44。 2. 查看cuda运行版本 查看cuda 版本： $ cat CUDA DeviceQuery (Runtime API) version (CUDART static linking) cudaGet Device Count returned 35 CUDA driver version is insufficient for CUDA runtime version. При использовании команды lspci -v, grep -i я получаю. Ask questions CUDA driver version is insufficient for CUDA runtime version.

+-----+ | NVIDIA-SMI 375.88 Driver Version: 375.88 | |-----+-----+-----+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr.

Posted 7/11/15 5:06 PM, 4 messages CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 35 -> CUDA driver version is insufficient for CUDA runtime version Result = FAIL On using the lspci -v | grep -i command I get : linux系统中，利用docker容器跑pytorch程序时遇到的问题。 CUDA driver version is insufficient for CUDA runtime version. CUDA驱动版本与运行版本不匹配。 1. 首先看linux中GPU的驱动版本 $ nvidia-smi 可以看到驱动版本是396.44。 2. 查看cuda运行版本 查看cuda 版本： $ cat CUDA DeviceQuery (Runtime API) version (CUDART static linking) cudaGet Device Count returned 35 CUDA driver version is insufficient for CUDA runtime version.

answer 1 This was fixed by building OpenCV with 1.3 compute capability. Dont let Cmake choose it automatically. CUDA Status: CUDA driver version is insufficient for CUDA runtime version.