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Optimizing sequential code for speed and portability! This repository showcases the results of a "Fundamentals of Parallel Programming" hackathon. We leveraged CUDA, OpenMP, and more to enhance performance, with the main notebook at the heart of it all. πŸš€

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FPP Hackathon Repository

Introduction

This repository documents the results of a hackathon conducted as part of the "Fundamentals of Parallel Programming" (FPP) course. The primary goal of this hackathon was to achieve portability and performance improvements for a sequential codebase through parallelization techniques, utilizing tools like CUDA, OpenMP, and other parallel computing frameworks.

Tools Used

  • CUDA: The codebase has been parallelized using CUDA to take advantage of GPU acceleration.
  • OpenMP: OpenMP directives have been employed for parallelization on shared-memory systems.

Notebooks

The primary notebook containing all the codes, experiments, and analyses is Laplacian_Filter_Problem_Hackathon_PT.ipynb.

Contributors

  • List of contributors and their respective contributions.

License

This project is licensed under the MIT License.

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Optimizing sequential code for speed and portability! This repository showcases the results of a "Fundamentals of Parallel Programming" hackathon. We leveraged CUDA, OpenMP, and more to enhance performance, with the main notebook at the heart of it all. πŸš€

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