My personal attempt at creating a relatively fast iterative mergesort that runs on CUDA GPUs
-
Updated
Sep 27, 2024 - Cuda
My personal attempt at creating a relatively fast iterative mergesort that runs on CUDA GPUs
Implementation of One Sided Jacobi SVD using CUDA on Jetson TK1 embedded GPU
Parallelizing matrix multiplication using Cuda C. Tiling is also implemented to compare results. This repository is submitted as the third assignment for the CSC447 (Parallel Programming for Multicore and Cluster Systems) course at the Lebanese American University.
This team project is presented as the final project for the CSC447 (Parallel Programming for Multicore and Cluster Systems) course at the Lebanese American University under the supervision of Dr. Hamdan Abdellatef.
Reinforcement learning console based PacMan Game
Learning CUDA Programming
CLE Third Assignment - The objective of this project was to take the second general problem, which have been discussed in the lab classes and for which we have developed both a multithreaded and a multiprocess solution. The aim now was to convert it into a CUDA program to be ran in a GPU under Linux.
Co-occurrence matrices act as the input to many unsupervised learning algorithms, including those that learn word embedding, and modern spectral topic models. However, the computation of these inputs often takes longer time than the inference. While much thought has been given to implementing fast learning algorithms. The co-occurrence matrix co…
Add a description, image, and links to the cuda-c topic page so that developers can more easily learn about it.
To associate your repository with the cuda-c topic, visit your repo's landing page and select "manage topics."