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https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-23 21:28:17 +08:00
Update samples for CUDA 11.8 with correct props
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@@ -330,9 +330,9 @@ endif
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# Gencode arguments
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ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
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SMS ?= 53 61 70 72 75 80 86 87
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SMS ?= 53 61 70 72 75 80 86 87 90
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else
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SMS ?= 35 37 50 52 60 61 70 75 80 86
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SMS ?= 35 37 50 52 60 61 70 75 80 86 90
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endif
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ifeq ($(SMS),)
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@@ -6,14 +6,14 @@
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<flag>--std=c++11</flag>
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</cflags>
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<cuda_api_list>
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<toolkit>cudaStreamCreateWithFlags</toolkit>
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<toolkit>cudaStreamDestroy</toolkit>
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<toolkit>cudaFree</toolkit>
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<toolkit>cudaStreamSynchronize</toolkit>
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<toolkit>cudaMemsetAsync</toolkit>
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<toolkit>cudaMalloc</toolkit>
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<toolkit>cudaStreamCreateWithFlags</toolkit>
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<toolkit>cudaSetDevice</toolkit>
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<toolkit>cudaGetErrorName</toolkit>
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<toolkit>cudaSetDevice</toolkit>
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<toolkit>cudaStreamSynchronize</toolkit>
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<toolkit>cudaMalloc</toolkit>
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<toolkit>cudaMemsetAsync</toolkit>
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<toolkit>cudaMemcpyAsync</toolkit>
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</cuda_api_list>
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<description><![CDATA[This sample demonstrates cuDLA hybrid mode wherein DLA can be programmed using CUDA.]]></description>
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@@ -51,6 +51,7 @@
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<sm-arch>sm80</sm-arch>
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<sm-arch>sm86</sm-arch>
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<sm-arch>sm87</sm-arch>
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<sm-arch>sm90</sm-arch>
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<supported_envs>
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<env>
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<arch>aarch64</arch>
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@@ -10,7 +10,7 @@ cuDLA, Data Parallel Algorithms, Image Processing
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## Supported SM Architectures
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[SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus)
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[SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
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## Supported OSes
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@@ -23,11 +23,11 @@ aarch64
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## CUDA APIs involved
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### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
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cudaStreamDestroy, cudaFree, cudaStreamSynchronize, cudaMemsetAsync, cudaMalloc, cudaStreamCreateWithFlags, cudaSetDevice, cudaGetErrorName, cudaMemcpyAsync
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cudaStreamCreateWithFlags, cudaStreamDestroy, cudaFree, cudaGetErrorName, cudaSetDevice, cudaStreamSynchronize, cudaMalloc, cudaMemsetAsync, cudaMemcpyAsync
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## Prerequisites
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Download and install the [CUDA Toolkit 11.6](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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Download and install the [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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## Build and Run
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