grla.blogg.se - Cuda driver

Each SKU maps to the NVIDIA Tesla GPU in one the following Azure GPU-enabled VM families: SKU To use GPUs in a container instance, specify a GPU resource with the following information: Support will be added for additional regions over time.Īdditional limitations: GPU resources can't be used when deploying a container group into a virtual network. In preview, the following limitations apply when using GPU resources in container groups.

If you would like to use this sku for your production container deployments, create an Azure Support request to increase the limit.

This allows you to get the interactivity of the front end while running the kernel on a remote CUDA machine.Due to some current limitations, not all limit increase requests are guaranteed to be approved. Unix users can use either SSH or X tunneling.Ī recommended alternative to VNC is to set up remote kernels. Users can use other protocols like VNC to perform remote computation. Using CUDALink over Remote DesktopĬUDALink will not work over the Windows Remote Desktop (RDP).

On such systems, users can either disable the video card switching behavior, or use tools that allow the user to switch from the menu bar (search the web for "dual-GPU switch" followed by the operating system). Laptops that perform automatic video card switching (between an Intel and an NVIDIA card, for example) may interfere with CUDALink's initialization of the CUDA device. This will allow the operating system to run the CUDA card using the proper driver. On systems with multiple GPU devices, the NVIDIA driver must be installed last. If the compiler is not in a standard installation, then the "CompilerIntallation" option can be given to use the nondefault installation, as described in "Setting a Different Compiler". Supported C compilers are Microsoft Visual Studio on Windows and GCC on Linux.ĬUDALink requires a supported C compiler to be installed on the system: NVCC compiler requires a C compiler, the NVCC compiler will not be detected without a valid C compiler. Note that macOS is not supported by NVIDIA.

Installation guides for Windows and Linux can be found here: The CUDA installation packages can be found on the CUDA Downloads Page. For convenience, NVIDIA includes a compatible CUDA driver with the toolkit. NVIDIA CUDA Toolkit and compatible CUDA driver is required for CUDALink to work. If you do not have supported hardware, you will not be able to fully use CUDALink. In addition, you should check that your operating system is supported. If you are not certain, you can see the list of hardware supported in the "GPU Hardware" section. You should confirm that you have GPU hardware supported by CUDA. It also discusses common setup problems and how to troubleshoot them. This section explains how CUDALink is set up and configured for your machine. CUDALink Compatibility With NVIDIA CUDA Toolkit