pycuda

CUDA integration for Python, plus shiny features

Python interface to GPU-powered libraries

This container is no longer supported, and has been deprecated in favor of: https://github.com/joehoeller/NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV

Algorithms implemented in CUDA + resources about GPGPU

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.

Audio Fingerprinting and Recognition in Python using NVidia's CUDA

a python package for gravitational wave analysis with the F-statistic

pyCUDA implementation of forward propagation for Convolutional Neural Networks

Parallel CUDA implementation of NON maximum Suppression. PyCUDA version is now moved to https://github.com/keineahnung2345/PyCUDA_NMS

⛏ Simple SHA-1 prefix/suffix brute force in CUDA (CTF proof-of-work)

Brain tumor (low-grade and high-grade glioma) segmentation using unsupervised methods

This repo is based on https://github.com/jeetkanjani7/Parallel_NMS but add PyCUDA implementation

🐳🐍Pycuda Docker Environment for GPU Accelerated Python

Parallel Processing Teaching Toolkit

A high-level Deep Learning framework that extends PyTorch and PyCUDA.

PNG grayscale and blur filters using PyCUDA

Use CUDA for eBeam Lithography Simulation

Numpy and pyCUDA implementation of subKmeans

A Dataflow implementation of DVND Local Search for the Minimum Latency Problem using GPU card

A PyCUDA covariance matrix parallel implementation

GPU accllerated program for Neighbor-Joining algorithm of Biopython library with PyCUDA

Universal version of Tinygrad with CUDA and OpenCL support

Mandelbrot set visualisation written in Python and accelerated with PyCUDA

This code is Spatial Frequency Extraction using Gradient-liked Operator in Three-Dimension (SFEGO_3D) that use gradient and integral to mimic the Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) and Three-dimensional Empirical Mode Decomposition (TEMD) in different way. Our code can get 6 Spatial Data (128*128*128) within 1 minutes with modern GPU.

CUDA accelerated raytracer using PyCUDA in Python

GPU Accelerated Image Filters

A parallelized PyCuda implementation of the KMeans clustering algorithm.

Convolution of two audio files for Signals and systems university lesson