Search Results for "compute"
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Showing 35 open source projects for "compute"
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
CCCL, or CUDA Core Compute Libraries, is a unified repository that consolidates several foundational CUDA C++ libraries into a single, cohesive development platform. It brings together Thrust, CUB, and libcudacxx, which collectively provide high-level abstractions, low-level performance primitives, and a CUDA-compatible standard library for GPU programming. -
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VulkanSceneGraph
Vulkan & C++17 based Scene Graph Project
VulkanSceneGraph (VSG), is a modern, cross-platform, high-performance scene graph library built upon Vulkan graphics/compute API. The software is written in C++17 and follows the CppCoreGuidelines and FOSS Best Practices. The source code is published under the MIT License, with the exception of vulkan.h, used for Vulkan extensions, which is under Apache License 2.0. This repository contains C++ headers and source and CMake build scripts to build the libvsg library. -
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Reselect
Selector library for Redux
Simple “selector” library for Redux (and others) inspired by getters in NuclearJS, subscriptions in re-frame and this proposal from speedskater. Selectors can compute derived data, allowing Redux to store the minimal possible state. Selectors are efficient. A selector is not recomputed unless one of its arguments changes. Selectors are composable. They can be used as input to other selectors. Reselect provides a function createSelector for creating memoized selectors. createSelector takes an array of input-selectors and a transform function as its arguments. ... -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
...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. On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. The team regularly updates it with performance improvements; for example, a 2025 update claims 5 % to 15 % gains on compute-bound workloads while maintaining API compatibility. -
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Microsoft SEAL
Easy-to-use and powerful homomorphic encryption library
...Developed by the Cryptography and Privacy Research group at Microsoft, it enables software engineers to build end-to-end encrypted data storage and computation services that never have to procure the customer's key. Microsoft SEAL is very easy to use, compile and run in many different environments. Homomorphic encryption is an encryption scheme that allows the cloud to compute directly on the encrypted data, without requiring the data to be decrypted first. This results in encrypted computations remaining encrypted, decrypted only by the data owner using the secret key. -
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Google Cloud Platform Go Samples
Sample apps and code written for Google Cloud
Google Cloud Platform Go Samples repository is a comprehensive collection of Go-based code examples that demonstrate how to build applications and services using Google Cloud Platform. It provides developers with practical implementations that cover a wide spectrum of cloud functionalities, including storage, compute, networking, and machine learning services. Each sample is designed to be easily reusable, allowing developers to copy code directly into their own projects as a starting point for development. The repository includes both simple quickstart examples and more advanced application patterns, often accompanied by documentation guides that explain how to deploy and run them in different environments. ... -
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rspirv
Rust implementation of SPIR-V module processing functionalities
rspirv is a Rust-based parser, builder, and disassembler for SPIR-V, the intermediate binary format used in Vulkan and OpenCL for shaders and compute kernels. It’s part of the gfx-rs ecosystem, a suite of graphics tools aiming to provide cross-platform rendering capabilities in Rust. rspirv enables manipulation and inspection of SPIR-V modules, which is useful in shader compilers, graphics drivers, and development tools for low-level GPU programming. The library strictly follows the SPIR-V specification and is used in projects that need to generate, analyze, or modify shaders dynamically. -
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and... -
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nivo
A rich set of dataviz components
...In order to use nivo, you have to install the @nivo/core package and then choose some of the scoped @nivo packages according to the charts you wish to use. Given an array of data series having an id and a nested array of points (with x, y properties), it will compute the line for each data series. All datum having null x or y will be treated as holes, thus portions of the corresponding line will be skipped. You can fully customize it using the circleComponent property to define your own, if you wish to do so you should have a look at the default SVG component to get started. Bar chart which can display multiple data series, stacked or side by side. ... -
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Caire
Content aware image resize library
...Using a dynamic programming approach the algorithm will generate individual seams across the image from top to down, or from left to right (depending on the horizontal or vertical resizing) and will allocate for each seam a custom value, the least important pixels having the lowest energy cost and the most important ones having the highest cost. We traverse the image from the second row to the last row and compute the cumulative minimum energy for all possible connected seams for each entry. The minimum energy level is calculated by summing up the current pixel value with the lowest value of the neighboring pixels obtained from the previous row. -
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oneDNN
oneAPI Deep Neural Network Library (oneDNN)
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the... -
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Flutter Rust Bridge
Rust binding generator, feature-rich, but seamless and simple
...The project supports passing complex types, handling async operations and streams, and integrating with Flutter across mobile and desktop targets. By leaning on Rust’s memory safety and zero-cost abstractions, it enables compute-heavy tasks—parsing, crypto, image/audio processing, and more—without sacrificing Flutter’s developer experience. Build scripts and templates streamline packaging and distribution so the Rust side fits cleanly into CI and multi-platform releases. In practice, teams gain a maintainable way to share one performant Rust core across multiple Flutter apps while keeping the UI reactive and fast. -
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DCV Color Primitives
DCV Color Primitives Library
...You might want to propagate errors to the caller function or mix with some other error types. So far, buffers were sized taking into account the image pixel format and dimensions; However, you can use a function to compute how many bytes are needed to store an image of a given format and size. If your data is scattered in multiple buffers that are not necessarily contiguous, you can provide image planes. To take into account data which is not tightly packed, you can provide image strides. -
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Micronaut Data
Ahead of Time Data Repositories
Micronaut Data is a database access toolkit that uses Ahead of Time (AoT) compilation to pre-compute queries for repository interfaces that are then executed by a thin, lightweight runtime layer. Both GORM and Spring Data maintain a runtime meta-model that uses reflection to model relationships between entities. This model consumes significant memory and memory requirements grow as your application size grows. The problem is worse when combined with Hibernate which maintains its own meta-model as you end up with duplicate meta-models. ... -
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GenAI Processors
GenAI Processors is a lightweight Python library
...The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking. -
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sebastian/diff
Diff implementation
diff is a standalone PHP library for computing and rendering textual differences, widely used to display “expected vs actual” output in testing tools. It supports line-based and character/word-granular comparisons so you can get both coarse and fine-grained views of changes. Output builders can produce formats like unified or context diffs, or more human-friendly renderings suitable for terminals and HTML reports. Internally, the library splits input into hunks and manages edge cases such as... -
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libTheSky
Fortran library to compute positions of celestial bodies
libTheSky is a Fortran library to compute positions of celestial bodies (Moon, planets, stars) and events (conjunctions, eclipses). It forms the core of the software that produces the Dutch popular-astronomy website http://hemel.waarnemen.com -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
...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, perform exact GP inference, and study training dynamics analytically for infinitely wide networks. The library closely mirrors JAX’s stax API while extending it to return a kernel_fn alongside init_fn and apply_fn, enabling drop-in workflows for kernel computation. Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling. -
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Open Food Facts
Native version of Open Food Facts on Android
...Open Food Facts contributors gather information and data on food products from around the world, using mobile apps. Open Food Facts is a database of food products with ingredients, allergens, and nutrition facts… which allow us to compute scores like Nutri-Score, NOVA groups, and Eco-Score. Open Food Facts is a non-profit association of volunteers. 25,000+ contributors like you have added 3M+ products from 150 countries using our Android or iPhone apps to scan barcodes and upload pictures of products and their labels. Data about food is of public interest and has to be open. ... -
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Jadecy
Java lib to compute (code) deps, SCCs, and cycles (Johnson algorithm).
...Since version 1.1, can also compute shortest cycles covering all edges of SCCs. Usage from command line is also possible but with reduced flexibility (cf. JadecyMain class). API entry point for Java code dependencies is the Jadecy class, or DepUnit that makes use of it and is designed for unit tests. API entry point for general graph computations is the net.jadecy.graph package. -
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Veldrid
A low-level, portable graphics library for .NET
Veldrid is a low-level, portable graphics library for .NET, providing a unified API over multiple graphics backends such as Direct3D, Vulkan, OpenGL, and Metal. It enables developers to write high-performance, cross-platform graphics applications without being tied to a specific graphics API. Veldrid is suitable for game development, simulations, and other applications requiring advanced graphics capabilities. -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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fog
The Ruby cloud services library
Whether you need compute, dns, storage, or a multitude of other services, fog provides an accessible entry point and facilitates cross-service compatibility. Just getting started working with cloud resources? You are not alone, and having so many complicated options makes it hard to know where to start. fog delivers the knowledge of cloud experts to you, helping you to bootstrap your cloud usage and guiding you as your own expertise develops. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
...These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. Tasks store dictionaries and provide helpers for loading/iterating over Datasets, initializing the Model/Criterion and calculating the loss.
