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65 lines
3.1 KiB
Markdown
65 lines
3.1 KiB
Markdown
# simpleCUFFT_callback - Simple CUFFT Callbacks
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## Description
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Example of using CUFFT. In this example, CUFFT is used to compute the 1D-convolution of some signal with some filter by transforming both into frequency domain, multiplying them together, and transforming the signal back to time domain. The difference between this example and the Simple CUFFT example is that the multiplication step is done by the CUFFT kernel with a user-supplied CUFFT callback routine, rather than by a separate kernel call.
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## Key Concepts
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Image Processing, CUFFT Library
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## Supported SM Architectures
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[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](https://developer.nvidia.com/cuda-gpus) [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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Linux
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## Supported CPU Architecture
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x86_64, ppc64le, 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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cudaMemcpy, cudaFree, cudaMemcpyFromSymbol, cudaGetDevice, cudaMalloc, cudaGetDeviceProperties
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## Dependencies needed to build/run
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[callback](../../../README.md#callback), [CUFFT](../../../README.md#cufft)
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## Prerequisites
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Download and install the [CUDA Toolkit 12.0](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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Make sure the dependencies mentioned in [Dependencies]() section above are installed.
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## Build and Run
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### Linux
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The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
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```
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$ cd <sample_dir>
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$ make
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```
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The samples makefiles can take advantage of certain options:
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* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, aarch64.
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By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
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`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=aarch64` <br/>
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See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
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* **dbg=1** - build with debug symbols
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```
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$ make dbg=1
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```
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* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
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```
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$ make SMS="50 60"
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```
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* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
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```
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$ make HOST_COMPILER=g++
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```
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## References (for more details)
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