Search Results for "gpu"
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42 projects for "gpu" with 2 filters applied:
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Khronos KTX
KTX (Khronos Texture) Library and Tools
KTX-Software is a suite of tools and libraries for working with Khronos Texture (KTX) files, designed and maintained by the Khronos Group. KTX is a container format for storing textures that are optimized for GPU upload, supporting modern formats like Basis Universal and ASTC. This repository includes tools for creating, validating, inspecting, and converting KTX and KTX2 files, making it essential for developers working in 3D engines, games, and visualization tools where texture streaming and compression are key. -
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PortableGL
An implementation of OpenGL 3.x-ish in clean C
PortableGL is a single-header, software-only implementation of a subset of OpenGL (specifically the GL 2.1 pipeline), designed to run entirely on the CPU. This lightweight graphics library allows OpenGL-style rendering without GPU acceleration, making it ideal for educational use, debugging, embedded systems, and retro-style software rendering. Because it mirrors OpenGL syntax and design, it can act as a drop-in CPU renderer for testing or deploying 3D graphics on platforms without GPU support. -
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libplacebo
Official mirror of libplacebo
libplacebo is a flexible, high-performance graphics library built on top of Vulkan, designed to provide reusable GPU-accelerated components for media applications. It originated as a core part of the rendering pipeline for the mpv media player and has since grown into a standalone library used for tone mapping, dithering, color space conversion, and more. libplacebo is ideal for developers looking to integrate sophisticated video rendering and post-processing into their own applications with full control over shaders and rendering stages. -
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Images.jl
An image library for Julia
...Julia is well-suited to image processing because it is a modern and elegant high-level language that is a pleasure to use, while also allowing you to write "inner loops" that compile to efficient machine code (i.e., it is as fast as C). Julia supports multithreading and, through add-on packages, GPU processing. JuliaImages is a collection of packages specifically focused on image processing. It is not yet as complete as some toolkits for other programming languages, but it has many useful algorithms. It is focused on clean architecture and is designed to unify "machine vision" and "biomedical 3d image processing" communities. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. ... -
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XFrames
GPU-accelerated GUI development for Node.js and the browser
xframes is a high-performance library that empowers developers to build native desktop applications using familiar web technologies, specifically Node.js and React, without the overhead of the DOM. xframes serves as a streamlined alternative to Electron, designed for developers looking to maximize performance and efficiency. -
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webgl-plot
A high-Performance real-time 2D plotting library based on native WebGL
...Unlike traditional canvas or SVG-based charting libraries, webgl-plot is optimized for streaming and dynamic updates, making it ideal for oscilloscope-style data, biomedical signals, or any application where data updates hundreds of times per second. Its minimal memory footprint and GPU acceleration ensure excellent performance even with tens of thousands of data points, and its simple API allows developers to get started quickly. -
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Tracy Profiler
Frame profiler
...Tracy supports profiling CPU (Direct support is provided for C, C++, Lua and Python integration. At the same time, third-party bindings to many other languages exist on the internet, such as Rust, Zig, C#, OCaml, Odin, etc.), GPU (All major graphic APIs: OpenGL, Vulkan, Direct3D 11/12, OpenCL.), memory allocations, locks, context switches, automatically attribute screenshots to captured frames, and much more. -
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Theseus
A library for differentiable nonlinear optimization
...Because solves are differentiable, you can backpropagate through optimization to learn cost weights, feature extractors, or initialization networks end-to-end. The implementation supports batched optimization on GPU, robust losses, damping strategies, and custom factors, making it practical for real-time systems. Helper packages provide geometry primitives and utilities for composing priors, relative constraints, and measurement models. Theseus bridges the gap between classical optimization and deep learning, enabling hybrid systems that learn components. -
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GPUPixel
Real-time image and video processing library similar to GPUImage
GPUPixel is a real-time image and video processing library written in C++11, based on OpenGL/ES. It offers functionalities similar to GPUImage, including built-in beauty filters, enabling efficient processing and rendering of visual effects on images and videos. -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. ... -
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Floem
A native Rust UI library with fine-grained reactivity
Floem is a cross-platform GUI framework for Rust. It aims to be extremely performant while providing world-class developer ergonomics. Supporting both GPU and CPU rendering, Floem gives you performance that's closest to bare metal. Also primitives are provided to help the developer to write performant UI code without too much effect. -
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PyOpenCL
OpenCL integration for Python, plus shiny features
PyOpenCL is a Python wrapper for the OpenCL framework, providing seamless access to parallel computing on CPUs, GPUs, and other accelerators. It enables developers to harness the full power of heterogeneous computing directly from Python, combining Python’s ease of use with the performance benefits of OpenCL. PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and... -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU. -
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CGL
CGL (C Game Library) is a multipurpose library
...Designed for simplicity and portability, cgl allows rendering of primitives such as lines, circles, triangles, and text to an in-memory framebuffer, which can then be displayed with any platform-dependent backend. It’s ideal for building custom engines, retro-style games, GUIs, or educational demos where GPU acceleration is not required. Its small footprint and lack of external dependencies make it easy to embed in any C project. -
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ProbabilisticCircuits.jl
Probabilistic Circuits from the Juice library
This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units).... -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
...It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. It integrates natively with Android (replacing older atrace/Systrace paths) and can sit alongside custom instrumentation in apps or services through its SDKs. -
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Hasktorch
Tensors and neural networks in Haskell
Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions.... -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. ... -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference... -
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation... -
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Glumpy
Python+Numpy+OpenGL, scalable and beautiful scientific visualization
Glumpy is a Python library that simplifies the development of high-performance, interactive OpenGL visualizations. It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and creative exploration. -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
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QtAV
A multimedia framework based on Qt and FFmpeg
QtAV is a cross-platform and high performance multimedia playback framework based on Qt and FFmpeg. Features: timeline preview, gpu decoding etc
