GPU-accelerated triangle mesh processing
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Updated
Oct 29, 2024 - Cuda
GPU-accelerated triangle mesh processing
GPU-based large scale Approx. Nearest Neighbor Search, accepted at CVPR 2016
Algorithms implemented in CUDA + resources about GPGPU
Parallel reduction of boundary matrices for Persistent Homology with CUDA
Playing with CUDA and GPUs in Google Colab
University of Toronto / ECE1782 - Programming Massively Parallel Multiprocessors and Heterogeneous Systems / Project: an optimized CUDA Implementation of AES 128-bit Encryption, support any file types, benchmarked with OpenSSL
This is a program to solve the job shop scheduling problem by using the parallel genetic algorithm
WAH compression using CUDA
This is a two-dimensional fluid solver written in a hybrid CPU-GPU architecture platform This code has been written as part of the requiremnts for the following courses at the University of Utah: Computational Fluid Dynamics Parallel computing on many-cores @ Authors: Arash Nemati Hayati Akshay Singhvi Lucas Ulmer
In this code is provided a simple, efficient and fast method to calculate motion and backgroud dynamically using nVidia GPUs power
Case studies constitute a modern interdisciplinary and valuable teaching practice which plays a critical and fundamental role in the development of new skills and the formation of new knowledge. This research studies the behavior and performance of two interdisciplinary and widely adopted scientific kernels, a Fast Fourier Transform and Matrix M…
Parallel implementation of Nearest Neighbour Search algorithm
Parallel SpMV using CSR representation, built in CUDA
An efficient CUDA implementation of Adaptive Non Local Means algorithm for image denoising.
A GPU implementation of the sampling algorithm ACHR.
C++ implementation of a neural network using OpenMP and CUDA for parallelization.
A novel GPU accelerated MCMC algorithm for graph coloring
Implementation of 2048 game with CUDA
Parallel Computing starter project to build GPU & CPU kernels in CUDA & C++ and call them from Python without a single line of CMake using PyBind11
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