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Nvidia jetson install cuda toolkit 9.03/18/2024 ![]() If enabled, accuracy improvement and performance drop can be expected. The default and recommanded setting is false. ![]() Whether to use strict mode in SkipLayerNormalization cuda implementation. (sample below)ĭefault value: 0 enable_skip_layer_norm_strict_mode This flag is only supported from the V2 version of the provider options struct when used using the C API. (sample below)Ĭheck using CUDA Graphs in the CUDA EP for details on what this flag does. ![]() This flag is only supported from the V2 version of the provider options struct when used using the C API.(sample below)ĭefault value: 1, for versions 1.14 and later 0, for previous versions cudnn_conv1d_pad_to_nc1dĬheck convolution input padding in the CUDA EP for details on what this flag does. Lightweight heuristic based search using cudnnGetConvolutionForwardAlgorithm_v7ĭefault algorithm using CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMMĭefault value: EXHAUSTIVE cudnn_conv_use_max_workspaceĬheck tuning performance for convolution heavy models for details on what this flag does. The strategy for extending the device memory arena.Įxpensive exhaustive benchmarking using cudnnFindConvolutionForwardAlgorithmEx Note: Will be over-ridden by contents of default_memory_arena_cfg (if specified) arena_extend_strategy s: max value of C++ size_t type (effectively unlimited) The total device memory usage may be higher. This size limit is only for the execution provider’s arena. The size limit of the device memory arena in bytes. This is implicitly enabled by has_user_compute_stream, enable_cuda_graph or when using an external allocator. Uses the same CUDA stream for all threads of the CUDA EP. If false, there are race conditions and possibly better performance.ĭefault value: true use_ep_level_unified_stream Whether to do copies in the default stream or use separate streams. To take advantage of user compute stream, it is recommended to use I/O Binding to bind inputs and outputs to tensors in device. InferenceSession ( "my_model.onnx", sess_options = sess_options, providers = providers ) This cannot be used in combination with an external allocator. It cannot be set through UpdateCUDAProviderOptions, but rather UpdateCUDAProviderOptionsWithValue. It implicitly sets the has_user_compute_stream option. device_idĭefines the compute stream for the inference to run on. The CUDA Execution Provider supports the following configuration options. Buildįor build instructions, please see the BUILD page. Requires cublas10-10.2.1.243 cublas 10.1.x will not workĬUDA versions from 9.1 up to 10.1, and cuDNN versions from 7.1 up to 7.4 should also work with Visual Studio 2017įor older versions, please reference the readme and build pages on the release branch.įor Windows, Microsoft C and C++ (MSVC) runtime libraries is also required. Tested with CUDA versions from 11.6 up to 11.8, and cuDNN from 8.2.4 up to 8.7.0 To install CUDA 12 package, please look at Install ORT.ĭue to low demand on Java GPU package, only C++/C# Nuget and Python packages are released with CUDA 12.2 The default CUDA version for ORT 1.17 is CUDA 11.8. This site uses Just the Docs, a documentation theme for Jekyll.
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