Why does my GPU say CUDA Driver failed?

I can run new Cuda programs on both GPUs. But when I use cuda-gdb to debug people, I get an error that your Cuda driver could not be initialized. When I run the program with cuda-gdb, cudaGetDeviceCount usually shows that I only have one GPU.

What is the CUDA error runtimeerror ( 3 )?

Error: RuntimeError: CUDA error: initialization error. I created any class inherited from Torch.utils.data.Dataset to render my own dataset. In this class, I am doing sample preprocessing on this particular GPU.

Error The Cuda Driver Failed Initialization Error=20

Q: Why do I get an initialization error in CUDA?

An initialization error usually indicates that something went wrong when the CUDA runtime was presented using the CUDA driver. One of the most common causes of this error is that the driver is older than the CUDA Toolkit. Each version of the CUDA Toolkit comes with a driver. Pay attention to the version because of this driver.

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You may come across an error code indicating that the driver initialization error is cuda = 20. There are several ways to fix this problem, and we will fix it shortly.

I have system 2, Geforce 8400 GS absolute and Geforce GT 520. But when using cuda-gdb for debugging, I get an error saying that The initialization of the Cuda driver failed. Also, when I run a program with cuda-gdb , cudaGetDeviceCount boasts only one GPU. I can run GPU programs if I don’t just use cuda-gdb . Can anyone help me with my site?

CUDA support is being discontinued without warning. They check for the error value returned by Cuda calls at runtime. You will find that the one that refers to the first calls to the CUDA runtime, most likely cudaMalloc , does not work with a very initialization error . No initialization is required to run API calls or CUDA kernels, so now you’re wondering what this process error is and how to fix it.

NVIDIA could be more informative in their bug reports. An initialization error usually indicates where most errors occurred when the CUDA runtime was declared with the CUDA driver. One of the most common causes of this error is that the driver is older than the CUDA Toolkit. Each version of the CUDA Toolkit is built with a driver. TotalPay attention to the version of the corresponding driver. Only drivers with the exact same or newer version numbers will certainly work with this CUDA toolkit. Install the best driver and this error should go away.

error the cuda driver failed initialization error=20

If you are trying to run the Dcoer GPU renderer eg. Example:
sudo nvidia-docker run -it -p 8888: 8888 tensorflow / tensorflow: last-gpu

I have the following error:

= 9. –pid = 8276 0 / var / lib / docker / overlay2 / b956d7f169cca157457e107ee8c99a050c33199ded8f4fa4d68ie3ace] error: Operator error : The request could not be processed n “” “: unknown.Error’>

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  docker: response from daemon: failure to start OCI run: container_linux.Starting go: 348: container process on "process_linux.go: 402: container initialization calls " process_linux.go: 385: run before running catch 1 caused  "an error while executing a trap: exiting respected name 1, stdout:, stderr: command exec: [/ usr / bin / nvidia-container-cli - load-kmods --ldconfig = @ / sbin / ldconfig configure .real --device = all --compute --utility --require = cuda> = 9. --pid = 8276 8 / var / lib / docker / overlay2 / b956d7f169cca157457e107ee8c99a050c33199ded8f4fa4d68e3ace612c6d0c driver / id: c  n  "" ": unknown.

3. Information (possibly Attach If Deemed Inappropriate)

Kernel version with uname -a
Linux de 4.4.0-122-generic # 146-Ubuntu SMP Mon Apr 15:34:04 23 UTC 2018 x86_64 x86_64 x86_64 GNU / Linux
Using Ubuntu 16.04
All related lines of kernel output from dmesg

can be used[0.000000] e820: change 0x579b0018-0x579c9257] [usable mem ==> usable[0.000000] Extended physical memory allocation:[0.000000] Reserve setup_data: [usable memory[0x0000000000000000-0x0000000000057fff] 0.000000] Save setup_data: [mem0 x00000000000058000-0x0000000000058fff] reserved[null .000000] backup install_data: [mem 0x000000000000059000-0x00000000000085fff] can be used[0.000000] backup setup_data: [mem 0x00000000000086000-0x00000000000fffff] reserved[0.Reserve 000000] setup_data: [mem 0x0000000000100000-0x00000000579b0017] can be used[0.000000] secure install_data: [mem 0x00000000579b0018-0x00000000579c9257] can be used[0.000000] Reserve setup_data: [usable memory[0x00000000579c9258-0x00000000579ca017] 0.Reserve 000000] setup_data: [mem 0x00000000579ca018-0x00000000579da057] can be used[0.000000] setup_data: Problem [mem 0x00000000579da058-0x0000000059042fff] can be used[0.000000] Reservedinstall_data: [mem 0x0000000059043000-0x0000000059043fff] ACPI NVS[0.000000] backup install_data: [mem 0x0000000059044000-0x000000005906dfff] reserved[0.000000] Buy setup_data: [mem 0x000000005906e000-0x000000006f30dfff] can be used[0.000000] backup install_data: [mem0 x000000006f30e000-0x000000006fcfdfff] reserved[0 .000000] setup_data: Reserved [mem 0x000000006fcfe000-0x000000006ff7dfff] ACPI NVS[0.Reserve 000000] setup_data: [mem 0x000000006ff7e000-0x000000006fffdfff] ACPI data[0.000000] Reserve setup_data: [usable memory[0x000000006fffe000-0x000000006ffffefff] 0.000000] Reserve setup_data: [mem Reserved[0x000000006ffff000-0x000000007b7fffff] 0.000000] setup_data: safe [mem 0x00000000e0000000-0x00000000effffff]

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