Fast parallel CTC.

Squeeze-and-Excitation Networks

GPU Accelerated t-SNE for CUDA with Python bindings

[MICRO'23, MLSys'22] TorchSparse: Efficient Training and Inference Framework for Sparse Convolution on GPUs.

MatConvNet: CNNs for MATLAB

Efficient GPU kernels for block-sparse matrix multiplication and convolution

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing …

Automatically exported from code.google.com/p/cuda-convnet2

Reference implementation of real-time autoregressive wavenet inference

UNet diffusion model in pure CUDA

SDK for GPU accelerated genome assembly and analysis

Marching cubes implementation for PyTorch environment.

CNN accelerated by cuda. Test on mnist and finilly get 99.76%

CUDA Matrix Factorization Library with Alternating Least Square (ALS)

Implementation of Conformal curvature flow using spin transformations, to achieve a spherical embedding

Python Framework for sparse neural networks

Code for non-separable filtering in 2, 3 and 4 dimensions with the CUDA programming language.

cuda implementations of various layers