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# graphMemoryFootprint - Graph Memory Footprint
## Description
This sample demonstrates how graph memory nodes re-use virtual addresses and physical memory.
## Key Concepts
CUDA Runtime API, Performance Strategies, CUDA Graphs
## Supported SM Architectures
[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)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaGraphAddMemAllocNode, cudaStreamCreateWithFlags, cudaGraphInstantiate, cudaStreamDestroy, cudaFree, cudaDeviceGetAttribute, cudaGraphAddKernelNode, cudaGraphAddMemFreeNode, cudaDeviceGetGraphMemAttribute, cudaGraphCreate, cudaGraphDestroy, cudaDriverGetVersion, cudaGraphLaunch, cudaStreamSynchronize, cudaDeviceGraphMemTrim, cudaGetDeviceProperties, cudaGraphExecDestroy
## Prerequisites
Download and install the [CUDA Toolkit 12.5](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## References (for more details)