NumPy & SciPy for GPU

CUDA Library Samples

Python interface to GPU-powered libraries

A 100x faster SVD for PyTorch⚡️

Hooked CUDA-related dynamic libraries by using automated code generation tools.

Bandicoot: C++ library for GPU linear algebra & scientific computing - https://coot.sourceforge.io

Harness the power of GPU acceleration for fusing visual odometry and IMU data with an advanced Unscented Kalman Filter (UKF) implementation. Developed in C++ and utilizing CUDA, cuBLAS, and cuSOLVER, this system offers unparalleled real-time performance in state and covariance estimation for robotics and autonomous system applications.

Sample CMake template solving Ax=b

A complete example of batched refactorization in cuSOLVER.

Matrix Exponential Approximation using CUDA

test stream of cusolver

Newton's and Halley's Method for the Matrix Polar Decomposition using CUDA

VTensor, a C++ library, facilitates tensor manipulation on GPUs, emulating the python-numpy style for ease of use. It leverages RMM (RAPIDS Memory Manager) for efficient device memory management. It also supports xtensor for host memory operations.

K-means Clustering in CUDA with OpenGL Visualization

NumPy-like API accelerated with CUDA

Framework, toolkit and ready-to-use applications for numerical linear algebra dependent machine learning algorithms.

matrix operation using gpu