A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Video stabilization using gyroscope data

[ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl

High-performance TensorFlow library for quantitative finance.

The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs and CPUs via OpenCL. Free for non-commercial use.

Lingvo

Resource scheduling and cluster management for AI

General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.

GPGPU microprocessor architecture

CUDA integration for Python, plus shiny features

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

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

The write-once-run-anywhere GPGPU library for Rust

😎 Curated list of awesome things around WebGPU ecosystem.

Simulation of spiking neural networks (SNNs) using PyTorch.

Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!

CUDA Core Compute Libraries

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

An efficient C++17 GPU numerical computing library with Python-like syntax

TornadoVM: A practical and efficient heterogeneous programming framework for managed languages