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33 lines
1.4 KiB
Markdown
33 lines
1.4 KiB
Markdown
# streamOrderedAllocation - stream Ordered Allocation
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## Description
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This sample demonstrates stream ordered memory allocation on a GPU using cudaMallocAsync and cudaMemPool family of APIs.
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## Key Concepts
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Performance Strategies
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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) [SM 8.9 ](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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Linux, Windows
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## Supported CPU Architecture
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x86_64, armv7l
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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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cudaDeviceGetDefaultMemPool, cudaFreeAsync, cudaStreamCreateWithFlags, cudaStreamDestroy, cudaDeviceGetAttribute, cudaMallocAsync, cudaSetDevice, cudaEventSynchronize, cudaEventRecord, cudaStreamSynchronize, cudaMemPoolSetAttribute, cudaEventElapsedTime, cudaMemcpyAsync, cudaEventCreate
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## Prerequisites
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Download and install the [CUDA Toolkit 12.5](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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## References (for more details)
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