![]() ![]() Support for virtual aliasing across kernel boundaries.New CUDA Driver API cuGetProcAddress() and CUDA Runtime APIĬudaDriverGetEntryPoint() to query the memory addresses.Stream priorities, up from the 3 exposed in prior releases. The CUDA Driver API cuCtxGetStreamPriorityRange() now exposes a total of 6.Graph Debug: New API to produce a DOT graph output from a given CUDA.Lifetime not under control of the code that created the resource, such as Their derivatives and asynchronous executions have an unknown/unbounded User object lifetime assistance: Functionality to assist user code in lifetime managementįor user-allocated resources referenced in graphs.Enhancements to make stream capture more flexible: Functionality to provide read-writeĪccess to the graph and the dependency information of a capturing stream,.Stream ordered memory allocator enhancements.Skipped on Windows (when using the interactive or silent installation) or onįor more information on customizing the install process on Windows, see. Recommended for use in production with Tesla GPUs.įor running CUDA applications in production with Tesla GPUs, it is recommended toĭownload the latest driver for Tesla GPUs from the NVIDIA driver downloads site atĭuring the installation of the CUDA Toolkit, the installation of the NVIDIA driver may be Note that this driver is for development purposes and is not * Using a Minimum Required Version that is different from Toolkitĭriver Version could be allowed in compatibility mode - please read theįor convenience, the NVIDIA driver is installed as part of the CUDA Toolkit CUDA Toolkit and Minimum Compatible Driver Versions CUDA ToolkitĬUDA 10.1 (10.1.105 general release, and updates) Versioned, and the toolkit itself is versioned as shown in the table Note: Starting with CUDA 11.0, the toolkit components are individually More information on compatibility can be found at. The CUDA driver is backward compatible, meaning that applications compiled againstĪ particular version of the CUDA will continue to work on subsequent (later) Įach release of the CUDA Toolkit requires a minimum version of the CUDA driver. Information various GPU products that are CUDA capable, visit. Running a CUDA application requires the system with at least one CUDA capable GPUĪnd a driver that is compatible with the CUDA Toolkit. CUDA 11.3 Component Versions Component Name 4 ( 1, 2, 3)įunctionalities that perform runtime compilation such as the runtime fusion engines, and the persistent dynamic algorithm of RNN, requires NVRTC from CUDA Toolkit 11.2 update 1 or later.Table 1. Dynamic linking is supported in all cases. This column specifies whether the given cuDNN library can be statically linked against the CUDA toolkit for the given CUDA version. For the limitation when using the static cuDNN library, refer to this table and the cuDNN Release Notes for more information. Similarly, the cuDNN build for CUDA 11.x is compatible with CUDA 11.x for all x. Visual Studio Versions Based on Your Version of CUDA įor the dynamic cuDNN libraries, the cuDNN build for CUDA 12.x is compatible with CUDA 12.x for all x, including future CUDA 12.x releases that ship after this cuDNN release. Refer to the following table to view the list of supported Visual Studio versions for cuDNN. Windows 10 and Windows Server 20 are supported. ![]() Linux Versions for cuDNN ĪArch64 incorporates ARM based CPU cores for Server Base System Architecture (SBSA).įor platforms that ship a compiler version older than GCC 6 by default, linking to static cuDNN using the default compiler is not supported.įor RHEL 8.9 and Rocky 8.9 Linux, the R525 and later display driver is needed. Refer to the following table to view the list of supported Linux versions for cuDNN. The following tables highlight the compatibility of cuDNN versions with the various supported OS versions. These are the configurations used for tuning heuristics. For GPUs prior to Volta (that is, Pascal and Maxwell), the recommended configuration is cuDNN 9.0.0 with CUDA 11.8. Supported NVIDIA Hardware and CUDA Version įor best performance, the recommended configuration for GPUs Volta or later is cuDNN 9.0.0 with CUDA 12.3. The following sections highlight the compatibility of NVIDIA cuDNN versions with the various supported NVIDIA CUDA Toolkit, CUDA driver, and NVIDIA hardware versions. Support Matrix GPU, CUDA Toolkit, and CUDA Driver Requirements ![]()
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