Image Rotation using NVIDIA NPP with CUDA

Overview

This project demonstrates the use of NVIDIA Performance Primitives (NPP) library with CUDA to perform image rotation. The goal is to utilize GPU acceleration to efficiently rotate a given image by a specified angle, leveraging the computational power of modern GPUs. The project is a part of the CUDA at Scale for the Enterprise course and serves as a template for understanding how to implement basic image processing operations using CUDA and NPP.

Code Organization

bin/ This folder should hold all binary/executable code that is built automatically or manually. Executable code should have use the .exe extension or programming language-specific extension.

data/ This folder should hold all example data in any format. If the original data is rather large or can be brought in via scripts, this can be left blank in the respository, so that it doesn't require major downloads when all that is desired is the code/structure.

lib/ Any libraries that are not installed via the Operating System-specific package manager should be placed here, so that it is easier for inclusion/linking.

src/ The source code should be placed here in a hierarchical fashion, as appropriate.

README.md This file should hold the description of the project so that anyone cloning or deciding if they want to clone this repository can understand its purpose to help with their decision.

INSTALL This file should hold the human-readable set of instructions for installing the code so that it can be executed. If possible it should be organized around different operating systems, so that it can be done by as many people as possible with different constraints.

Makefile or CMAkeLists.txt or build.sh There should be some rudimentary scripts for building your project's code in an automatic fashion.

run.sh An optional script used to run your executable code, either with or without command-line arguments.

Key Concepts

Performance Strategies, Image Processing, NPP Library

Supported SM Architectures

SM 3.5 SM 3.7 SM 5.0 SM 5.2 SM 6.0 SM 6.1 SM 7.0 SM 7.2 SM 7.5 SM 8.0 SM 8.6

Supported OSes

Linux, Windows

Supported CPU Architecture

x86_64, ppc64le, armv7l

CUDA APIs involved

Dependencies needed to build/run

FreeImage, NPP

Prerequisites

Download and install the CUDA Toolkit 11.4 for your corresponding platform. Make sure the dependencies mentioned in Dependencies section above are installed.

Build and Run

Windows

The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:

*_vs<version>.sln - for Visual Studio <version>

Each individual sample has its own set of solution files in its directory:

To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.

Note: Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (Tools > Options...). Check DirectX Dependencies section for details."

Linux

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:

$ cd <sample_dir>
$ make

The samples makefiles can take advantage of certain options:

• TARGET_ARCH= - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l. 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.
  $ make TARGET_ARCH=x86_64
$ make TARGET_ARCH=ppc64le
$ make TARGET_ARCH=armv7l
  See here for more details.

• dbg=1 - build with debug symbols

  $ make dbg=1
  

• 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".

  $ make SMS="50 60"
  

• HOST_COMPILER=<host_compiler> - override the default g++ host compiler. See the Linux Installation Guide for a list of supported host compilers.

    $ make HOST_COMPILER=g++

Running the Program

After building the project, you can run the program using the following command:

Copy code
make run

This command will execute the compiled binary, rotating the input image (Lena.png) by 45 degrees, and save the result as Lena_rotated.png in the data/ directory.

If you wish to run the binary directly with custom input/output files, you can use:

- Copy code
./bin/imageRotationNPP --input data/Lena.png --output data/Lena_rotated.png

• Cleaning Up To clean up the compiled binaries and other generated files, run:

- Copy code
make clean

This will remove all files in the bin/ directory.