Search Results for "high performance computing" - Page 55
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Showing 2510 open source projects for "high performance computing"
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1
ThinkJulia.jl
Port of the book Think Python to the Julia programming language
...Downey into the Julia programming language, with contributions by Ben Lauwens. It provides a comprehensive introduction to programming and computational thinking using Julia’s modern, high-performance features. The book is structured to gradually teach core concepts such as variables, control flow, functions, recursion, object-oriented programming, and data structures, while offering hands-on exercises to reinforce each topic. By combining clear explanations with practical examples, the project helps both beginners and experienced programmers transition to Julia. ... -
2
Pyrogram
Elegant, modern and asynchronous Telegram MTProto API framework
...Easy: Makes the Telegram API simple and intuitive, while still allowing advanced usages. Elegant: Low-level details are abstracted and re-presented in a more convenient way. Fast: Boosted up by TgCrypto, a high-performance cryptography library written in C. Type-hinted: Types and methods are all type-hinted, enabling excellent editor support. Async: Fully asynchronous (also usable synchronously if wanted, for convenience). Powerful: Full access to Telegram's API to execute any official client action and more. -
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Nano JSON
Lightweight, facility, high performance golang based game server
Nano is an easy-to-use, fast, lightweight game server networking library for Go. It provides a core network architecture and a series of tools and libraries that can help developers eliminate boring duplicate work for common underlying logic. The goal of nano is to improve development efficiency by eliminating the need to spend time on repetitious network-related programming. Nano was designed for server-side applications like real-time games, social games, mobile games, etc of all sizes. In... -
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HiFi-SoRaP
High Fidelity Solar Raytracing Project (HiFi-SoRaP)
The aim of this project is to develop an efficient way of computing the solar radiation pressure acceleration that acts on a spacecraft. This acceleration is produced by the impact of the photons emitted by the Sun onto a spacecraft's surface. This collision generates an acceleration which affects its motion and has a relevant effect on a long-term propagation. This proposal studies which models can be used to approximate the computation of this acceleration. Some of the models are... -
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5
Ink
A fast and flexible Markdown parser written in Swift.
Ink is a fast and flexible Markdown parsing library written in Swift that is designed to convert Markdown content into structured representations suitable for rendering or further processing. Originally developed as part of the Publish ecosystem, it focuses on performance and extensibility while maintaining a relatively simple and understandable internal architecture. The parser operates by reading Markdown input through a structured reader system that processes fragments and determines how... -
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conc
Better structured concurrency for go
Conc is a Go library for managing structured concurrency, simplifying the development of concurrent applications with high performance. -
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PARL
A high-performance distributed training framework
PARL is a scalable reinforcement learning framework built on top of PaddlePaddle. It focuses on modularity and ease of use, supporting distributed training and a variety of RL algorithms. -
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Lacinia
GraphQL implementation in pure Clojure
...It allows you to define schemas with EDN or GraphQL IDL, resolve queries efficiently, and supports GraphQL capabilities like subscriptions and schema introspection. High-performance parser for GraphQL queries, built on Antlr4. Efficient and asynchronous query execution. Full support for GraphQL types, interfaces, unions, enums, input objects, and custom scalars. Full support for GraphQL subscriptions. Full support of inline and named query fragments. Full support for GraphQL Schema Introspection. -
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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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10
MMGeneration
MMGeneration is a powerful toolkit for generative models
MMGeneration has been merged in MMEditing. And we have supported new-generation tasks and models. MMGeneration is a powerful toolkit for generative models, especially for GANs now. It is based on PyTorch and MMCV. The master branch works with PyTorch 1.5+. We currently support training on Unconditional GANs, Internal GANs, and Image Translation Models. Support for conditional models will come soon. A plentiful toolkit containing multiple applications in GANs is provided to users. GAN... -
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T81 558
Applications of Deep Neural Networks
...This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. -
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ClassyVision
An end-to-end PyTorch framework for image and video classification
...Unlike traditional computer vision libraries that focus solely on modular components, Classy Vision provides a complete and unified framework, featuring distributed training, reproducible experiments, and flexible configuration tools. It offers high performance and scalability—capable of training models like ResNet-50 on ImageNet in just minutes—while remaining accessible to both researchers and production engineers. The library integrates seamlessly with PyTorch Hub for easy access to pretrained models and supports elastic training using PyTorch Elastic, making distributed training robust to changes in cluster resources or hardware failures. -
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textacy
NLP, before and after spaCy
textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals, tokenization, part-of-speech tagging, dependency parsing, etc., delegated to another library, textacy focuses primarily on the tasks that come before and follow after. -
14
Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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ui-box
Blazing Fast React UI Primitive
ui-box is a low-level React UI primitive library that provides a simple and performant way to build styled components using a CSS-in-JS approach. Instead of relying on traditional CSS files or complex styling systems, ui-box allows developers to apply CSS properties directly through React props, making styling more intuitive and composable. The core concept revolves around a single Box component that can render different HTML elements while accepting a wide range of style-related properties.... -
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Stork
Impossibly fast web search, made for static sites
Stork is a high-performance, client-side full-text search library designed specifically for static websites, offering instant and accurate search results without requiring a backend server. It operates through a two-part system: a command-line tool that indexes content and generates a compact search index, and a JavaScript library that loads this index in the browser and performs searches in real time. -
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Thrust
The C++ parallel algorithms library
Thrust is the C++ parallel algorithms library which inspired the introduction of parallel algorithms to the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). It also provides a number of general-purpose facilities similar to those found in the C++ Standard Library. ... -
18
KubeOperator
An open source, lightweight Kubernetes distribution
...Compared with heavyweight PaaS platforms such as OpenShift, KubeOperator only focuses on solving one problem, which is to help enterprises plan (Day 0), deploy (Day 1), and operate (Day 2) production-level K8S clusters, and achieve the ultimate. Supports multiple computing, storage and networking scenarios. Integrate Ansible and Terraform. Support online environment and offline environment deployment. Provides a visual web UI. Supports cluster planning, deployment and operations. Easily run workloads like machine learning, high-performance computing, and more. Quickly deploy and manage applications in K8S. ... -
19
ElegantRL
Massively Parallel Deep Reinforcement Learning
ElegantRL is an efficient and flexible deep reinforcement learning framework designed for researchers and practitioners. It focuses on simplicity, high performance, and supporting advanced RL algorithms. -
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UDPspeeder
A Tunnel which Improves your Network Quality
...The project is especially relevant for gaming, remote access, VPN transport, and other latency-sensitive use cases where packet loss creates visible performance problems. It gives users adjustable parameters so they can balance bandwidth overhead, latency, and resilience. UDPspeeder is not a general VPN by itself, but a network-quality enhancement layer for UDP tunnels. -
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FasterTransformer
Transformer related optimization, including BERT, GPT
FasterTransformer is a high-performance inference library designed to accelerate transformer-based models such as BERT, GPT, and T5 on NVIDIA GPUs. It provides optimized implementations of transformer encoder and decoder layers using CUDA, cuBLAS, and custom kernels to maximize throughput and minimize latency. The library supports multiple deep learning frameworks, including TensorFlow, PyTorch, and Triton, allowing developers to integrate it into existing pipelines without major changes. ... -
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playerdemo
Android multimedia demonstration project
...It focuses on implementing the full playback pipeline, including decoding, rendering, and synchronization of audio and video streams. The project demonstrates how to integrate native C/C++ code with Java through JNI to achieve high-performance playback on mobile devices. It includes examples of handling different media formats, managing buffers, and controlling playback states. The architecture is designed for educational purposes, helping developers understand low-level media processing concepts. It also highlights performance considerations such as threading and hardware acceleration. ... -
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BitSail
BitSail is a distributed high-performance data integration engine
BitSail is ByteDance's open source data integration engine which is based on distributed architecture and provides high performance. It supports data synchronization between multiple heterogeneous data sources, and provides global data integration solutions in batch, streaming, and incremental scenarios. At present, it serves almost all business lines in ByteDance, such as Douyin, Toutiao, etc., and synchronizes hundreds of trillions of data every day. -
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Ultra NPM
JavaScript package manager
Ultra is a modern, high-performance package manager designed as an alternative to npm, Yarn, and pnpm. It focuses on speed, efficiency, and security while improving dependency management. -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments.
