NumPy & SciPy for GPU

A flexible framework of neural networks for deep learning

Introduction to Deep Neural Networks with Keras and Tensorflow

1st place solution

Deep learning in Rust, with shape checked tensors and neural networks

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

SCUDA is a GPU over IP bridge allowing GPUs on remote machines to be attached to CPU-only machines.

Safe rust wrapper around CUDA toolkit

GPU-accelerated Deep Learning on Windows 10 native

Minimal runtime core of Caffe, Forward only, GPU support and Memory efficiency.

Efficient, transparent deep learning in hundreds of lines of code.

🔥🔥🔥 A collection of some awesome public CUDA, cuBLAS, cuDNN, CUTLASS, TensorRT, TensorRT-LLM, Triton, TVM, MLIR and High Performance Computing (HPC) projects.

The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch

OpenCV installation script with CUDA and cuDNN support

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

VGG-19 deep learning model trained using ISCX 2012 IDS Dataset

TensorFlow wheels built for latest CUDA/CuDNN and enabled performance flags: SSE, AVX, FMA; XLA

Tutorial for using Singularity containers

Script to remotely check GPU servers for free GPUs

PyTorch installation wheels for Jetson Nano