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#

accelerated-computing

Here are 15 public repositories matching this topic...

My solutions for NVIDIA course Fundamentals of Accelerated Computing with CUDA C/C++

  • UpdatedJan 27, 2023
  • Cuda

Fundamentals of Accelerated Computing C/C++ is a course provided by NVIDIA.

  • UpdatedOct 9, 2020
  • Cuda

AMD GPU Profiler for ROCm compatible GPU.

  • UpdatedNov 21, 2025
  • C

Written by Sem Kirkels, Nathan Bruggeman and Axel Vanherle. Grayscales an image, applies convolution, maximum pooling and minimum pooling.

  • UpdatedFeb 20, 2023
  • Jupyter Notebook

Parallelism standards for accelerating performance on calculations for detection of positive DNA selection

  • UpdatedNov 19, 2024
  • C

The project aims to optimize the Dynamic Time Warping (DTW) algorithm and accelerate it using Graphics Processing Units (GPUs), So that algorithm can be executed in a GPU-equipped laptop or a GPU-equipped embedded device like NVIDIA Jetson, rather than connecting to a massive server.

  • UpdatedFeb 22, 2023

This repository contains an advanced tutorial on optimizing Python code for machine learning applications, focusing on processing large amounts of data efficiently. It covers three powerful libraries: Numba, NumPy, and Polars.

  • UpdatedOct 9, 2024
  • Jupyter Notebook

Talks and Presentations on Deep Learning principles,models and architectures

  • UpdatedAug 18, 2025

Advance Statistical Computing, 2019, Seoul National University

  • UpdatedJan 18, 2023
  • Jupyter Notebook

Fundamental tools and techniques for running GPU-accelerated Python applications using CUDA® GPUs and the Numba compiler.

  • UpdatedJan 20, 2025
  • Jupyter Notebook

How to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results.

  • UpdatedJul 23, 2025
  • Jupyter Notebook

Repository of the lab7 assignment for the Parallel Programming course.

  • UpdatedJul 3, 2025
  • C++

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