Keywords
Languages
nvidia-gpu-ml-library-test
Simple tests for JAX, PyTorch, and TensorFlow to test if the installed NVIDIA drivers are being properly picked up
Multi-Plexer
Goal: Low power cluster capable of serving 24+ streams of 4KHDR60 source transcodes while consuming no more than 100W at peak and idling at less than 10W
CUDA-quartic-solver
A general cubic equation solver and quartic equation minimisation solver written for CPU and Nvidia GPUs, for more details and results, see: https://arxiv
Apriori-and-Eclat-Frequent-Itemset-Mining
Implementation of the Apriori and Eclat algorithms, two of the best-known basic algorithms for mining frequent item sets in a set of transactions, implementation in Python
vuda
VUDA is a header-only library based on Vulkan that provides a CUDA Runtime API interface for writing GPU-accelerated applications
BlockMatching
CPU and CUDA implementation of Full Exhaustive Block Matching Algorithm using Integral Images
Background-Subtraction-on-GPU-with-CUDA-and-OpenCV
In this code is provided a simple, efficient and fast method to calculate motion and backgroud dynamically using nVidia GPUs power
CudaPerformance
Compare the performance of matrix multiplication among GPU shared memory, GPU global memory and CPU
