Gpu
Showing 36 of 100 projects
A Python library for loading, shaping, embedding, and exploring large graphs with GPU-accelerated visualization and analytics.
A curated list of awesome OpenGL libraries, debuggers, tutorials, and resources for graphics programming.
A curated collection of high-quality OpenGL libraries, debuggers, tutorials, and resources for graphics developers.
NVIDIA's implementation of the C++ Standard Library for CUDA C++ development.
A collection of tools for inspecting, tweaking, and replaying graphics API calls between applications and GPU drivers.
A collection of GPU-accelerated graph analytics libraries for creating, manipulating, and executing scalable graph algorithms.
A Vulkan-based source port of id Software's Quake, offering enhanced graphics and performance over QuakeSpasm.
A GPU-accelerated image and video processing framework for Apple platforms built on Metal.
A fast 2kB low-level WebGL library for GPU-accelerated particle systems and high-performance visual effects.
A fork of Emacs that adds modern features like TypeScript/JavaScript support via Deno, GPU-accelerated rendering with WebRender, and improved async I/O.
A JIT compiler for writing high-performance GPU programs in .NET languages like C#, offering CUDA-level performance with C# convenience.
A C++ GPU computing library providing an STL-like interface for OpenCL-based parallel programming.
A collection of high-performance GICP-based point cloud registration algorithms with multi-threaded and GPU-accelerated implementations.
A fast Support Vector Machine (SVM) library that leverages GPUs and multi-core CPUs for high-performance machine learning.
A write-once-run-anywhere GPGPU library for Rust that abstracts WebGPU for CUDA-like compute with portability across desktop, mobile, and browser.
A high-level Deep Learning API for JVM and Android developers, written in Kotlin and inspired by Keras.
A curated list of awesome WebGL libraries, resources, tutorials, and tools for developers.
A modern C++20 GPU numerical computing library with Python-like syntax for near-native performance on NVIDIA GPUs.
A C++17 library providing efficient STL-like data structures (vector, unordered_map, etc.) for GPU programming with CUDA, OpenMP, and HIP backends.
A C++17 utility library that simplifies Vulkan initialization by handling instance creation, device selection, and swapchain setup.
A React Native library that provides WebGPU API access for high-performance graphics and compute on iOS, Android, and Web.
A high-performance Clojure library for matrix and linear algebra computations using optimized BLAS/LAPACK routines on CPU and GPU.
A WebGL-powered library for visualizing wind patterns using particle systems, capable of rendering up to 1 million particles at 60fps.
A CUDA-accelerated library for rapid 3D data processing in robotics, enabling GPU-powered SLAM, collision avoidance, and path planning.
A modernized source port of id Software's Quake 2 v3.21 with Vulkan support, mission packs, and cross-platform compatibility.
A scalable, hardware-accelerated neuroevolution toolkit built on JAX for parallel training across TPUs/GPUs.
Thin, unified C++ wrappers for NVIDIA's CUDA APIs (Runtime, Driver, NVRTC, NVTX) that improve safety and ease of use.
A lightweight middleware layer that simplifies Vulkan API usage for professional workstation applications.
A Vulkan binding generator for Zig that provides idiomatic Zig APIs, error integration, and automatic function loading.
Rust bindings for ArrayFire, a high-performance parallel computing library with support for CUDA, OpenCL, and CPU backends.
A high-performance 2D vector graphics library using Vulkan as its rendering backend, with a Cairo-like API.
A high-performance GPU rendering library for scientific data visualization, built on Vulkan and up to 10,000x faster than matplotlib.
A pre-trained BERT model designed for DNA sequence analysis, enabling genome understanding tasks like classification and motif discovery.
A fast GPU-accelerated library for training Gradient Boosting Decision Trees (GBDT) and Random Forests.
A JAX-based framework for training large language models with a focus on legibility, scalability, and reproducibility.
A tensor library for differentiable functional programming in F#, with PyTorch-like APIs and GPU support.
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