# cuDLALayerwiseStatsHybrid - cuDLA Layerwise statistics HybridMode

## Description

This sample is used to provide layerwise statistics to the application in the cuDLA hybrid mode wherein DLA is programmed using CUDA.

## Key Concepts

cuDLA, Data Parallel Algorithms, Image Processing

## 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, QNX

## Supported CPU Architecture

aarch64

## CUDA APIs involved

### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaStreamCreateWithFlags, cudaStreamDestroy, cudaFree, cudaGetErrorName, cudaSetDevice, cudaStreamSynchronize, cudaMalloc, cudaMemsetAsync, cudaMemcpyAsync

## Prerequisites

Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.

## References (for more details)