227 Repositories
Python distributed-tracing Libraries
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data based on Pytorch Framework
VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-
A ray tracing render implemented using Taichi language.
A ray tracing render implemented using Taichi language.
Qtas(Quite a Storage)is an experimental distributed storage system developed by Q-team in BJFU Advanced Computer Network sources.
Qtas(Quite a Storage)is a experimental distributed storage system developed by Q-team in BJFU Advanced Computer Network sources.
Qtas(Quite a Storage)is an experimental distributed storage system developed by Q-team in BJFU Advanced Computer Network sources.
Qtas(Quite a Storage)is a experimental distributed storage system developed by Q-team in BJFU Advanced Computer Network sources.
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation
DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning
Generalized and Efficient Blackbox Optimization System.
OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio
Revealing and Protecting Labels in Distributed Training
Revealing and Protecting Labels in Distributed Training
Migration of Edge-based Distributed Federated Learning
FedFly: Towards Migration in Edge-based Distributed Federated Learning About the research Due to mobility, a device participating in Federated Learnin
Enhancing Knowledge Tracing via Adversarial Training
Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
Django GUID attaches a unique correlation ID/request ID to all your log outputs for every request.
Django GUID Now with ASGI support! Django GUID attaches a unique correlation ID/request ID to all your log outputs for every request. In other words,
Distributed Synchronization for Python
Distributed Synchronization for Python Tutti is a nearly drop-in replacement for python's built-in synchronization primitives that lets you fearlessly
A fantasy life simulator and role-playing game hybrid distributed as CLI, written in Python 3.
Life is Fantasy Epic (LIFE) A fantasy life simulator and role-playing game hybrid distributed as CLI, written in Python 3. This repository will be pro
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
Hapi is a Python library for building Conceptual Distributed Model using HBV96 lumped model & Muskingum routing method
Current build status All platforms: Current release info Name Downloads Version Platforms Hapi - Hydrological library for Python Hapi is an open-sourc
A Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids.
pyHype: Computational Fluid Dynamics in Python pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve
Pytorch implementation for DFN: Distributed Feedback Network for Single-Image Deraining.
DFN:Distributed Feedback Network for Single-Image Deraining Abstract Recently, deep convolutional neural networks have achieved great success for sing
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
An implementation of Ray Tracing in One Weekend using Taichi
又一个Taichi语言的Ray Tracer 背景简介 这个Ray Tracer基本上是照搬了Peter Shirley的第一本小书Ray Tracing in One Weekend,在我写的时候参考的是Version 3.2.3这个版本。应该比其他中文博客删改了不少内容。果然Peter Shir
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Pritunl is a distributed enterprise vpn server built using the OpenVPN protocol.
Pritunl is a distributed enterprise vpn server built using the OpenVPN protocol.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
An experimental Fang Song style Chinese font generated with skeleton-tracing and pix2pix
An experimental Fang Song style Chinese font generated with skeleton-tracing and pix2pix, with glyphs based on cwTeXFangSong. The font is optimised fo
Python implementation of the IPv8 layer provide authenticated communication with privacy
Python implementation of the IPv8 layer provide authenticated communication with privacy
Pytorch implementation of Distributed Proximal Policy Optimization
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
A fast python implementation of Ray Tracing in One Weekend using python and Taichi
ray-tracing-one-weekend-taichi A fast python implementation of Ray Tracing in One Weekend using python and Taichi. Taichi is a simple "Domain specific
A suite of utilities for AWS Lambda Functions that makes tracing with AWS X-Ray, structured logging and creating custom metrics asynchronously easier
A suite of utilities for AWS Lambda Functions that makes tracing with AWS X-Ray, structured logging and creating custom metrics asynchronously easier
Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021)
Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021) Zeyu Wang, Sherry Qiu, Nicole Feng, Holly Rushmeier, Leonard McMill
HyperPose is a library for building high-performance custom pose estimation applications.
HyperPose is a library for building high-performance custom pose estimation applications.
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.
WAGMA-SGD is a decentralized asynchronous SGD for distributed deep learning training based on model averaging.
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.
Bagua is a flexible and performant distributed training algorithm development framework.
Bagua is a flexible and performant distributed training algorithm development framework.
Distributed DataLoader For Pytorch Based On Ray
Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂,CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在,这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C
This repository contains all the code and materials distributed in the 2021 Q-Programming Summer of Qode.
Q-Programming Summer of Qode This repository contains all the code and materials distributed in the Q-Programming Summer of Qode. If you want to creat
Tracing instruction in lldb debugger.Just a python-script for lldb.
lldb-trace Tracing instruction in lldb debugger. just a python-script for lldb. How to use it? Break at an address where you want to begin tracing. Im
Secure Distributed Training at Scale
Secure Distributed Training at Scale This repository contains the implementation of experiments from the paper "Secure Distributed Training at Scale"
DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters
DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters
A parallel framework for population-based multi-agent reinforcement learning.
MALib: A parallel framework for population-based multi-agent reinforcement learning MALib is a parallel framework of population-based learning nested
A simple multi-threaded distributed SSH brute-forcing tool written in Python.
OrbitalDump A simple multi-threaded distributed SSH brute-forcing tool written in Python. How it Works When the script is executed without the --proxi
dask-sql is a distributed SQL query engine in python using Dask
dask-sql is a distributed SQL query engine in Python. It allows you to query and transform your data using a mixture of common SQL operations and Python code and also scale up the calculation easily if you need it.
A general-purpose multi-agent training framework.
MALib A general-purpose multi-agent training framework. Installation step1: build environment conda create -n malib python==3.7 -y conda activate mali
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
GenSen Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning Sandeep Subramanian, Adam Trischler, Yoshua B
Inject an ID into every log message from a Django request. ASGI compatible, integrates with Sentry, and works with Celery
Django GUID Now with ASGI support! Django GUID attaches a unique correlation ID/request ID to all your log outputs for every request. In other words,
Ray provides a simple, universal API for building distributed applications.
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Distributed Task Queue (development branch)
Version: 5.1.0b1 (singularity) Web: https://docs.celeryproject.org/en/stable/index.html Download: https://pypi.org/project/celery/ Source: https://git
A multiprocessing distributed task queue for Django
A multiprocessing distributed task queue for Django Features Multiprocessing worker pool Asynchronous tasks Scheduled, cron and repeated tasks Signed
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform
(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
BRNet Introduction This is a release of the code of our paper Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds,
(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
BRNet Introduction This is a release of the code of our paper Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds,
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing
Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.
NoPdb: Non-interactive Python Debugger
NoPdb: Non-interactive Python Debugger Installation: pip install nopdb Docs: https://nopdb.readthedocs.io/ NoPdb is a programmatic (non-interactive) d
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a
The goal of this library is to generate more helpful exception messages for numpy/pytorch matrix algebra expressions.
Tensor Sensor See article Clarifying exceptions and visualizing tensor operations in deep learning code. One of the biggest challenges when writing co
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her
🎛 Distributed machine learning made simple.
🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight
Distributed Evolutionary Algorithms in Python
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
Distributed scikit-learn meta-estimators in PySpark
sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
Distributed Computing for AI Made Simple
Project Home Blog Documents Paper Media Coverage Join Fiber users email list [email protected] Fiber Distributed Computing for AI Made Simp
A high performance and generic framework for distributed DNN training
BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith
a distributed deep learning platform
Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray What is Analytics Zoo? Analytics Zo
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas
Distributed Deep learning with Keras & Spark
Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc
BigDL: Distributed Deep Learning Framework for Apache Spark
BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear
Pytorch Lightning Distributed Accelerators using Ray
Distributed PyTorch Lightning Training on Ray This library adds new PyTorch Lightning plugins for distributed training using the Ray distributed compu
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intention of Apex is to make up-to-date utilities available to users as quickly as possible.
Pytorch Lightning Distributed Accelerators using Ray
Distributed PyTorch Lightning Training on Ray This library adds new PyTorch Lightning accelerators for distributed training using the Ray distributed
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Microsoft Distributed Machine Learning Toolkit
DMTK Distributed Machine Learning Toolkit https://www.dmtk.io Please open issues in the project below. For any technical support email to dmtk@microso
Framework and Library for Distributed Online Machine Learning
Jubatus The Jubatus library is an online machine learning framework which runs in distributed environment. See http://jubat.us/ for details. Quick Sta
Distributed machine learning platform
Veles Distributed platform for rapid Deep learning application development Consists of: Platform - https://github.com/Samsung/veles Znicz Plugin - Neu
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
Distributed Asynchronous Hyperparameter Optimization in Python
Hyperopt: Distributed Hyperparameter Optimization Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which
Distributed Evolutionary Algorithms in Python
DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru
Modin: Speed up your Pandas workflows by changing a single line of code
Scale your pandas workflows by changing one line of code To use Modin, replace the pandas import: # import pandas as pd import modin.pandas as pd Inst
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Master Docs License Apache MXNet (incubating) is a deep learning framework designed for both efficiency an
Distributed Deep learning with Keras & Spark
Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
PySpark + Scikit-learn = Sparkit-learn
Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.
Py4J enables Python programs to dynamically access arbitrary Java objects
Py4J Py4J enables Python programs running in a Python interpreter to dynamically access Java objects in a Java Virtual Machine. Methods are called as
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
CNTK Chat Windows build status Linux build status The Microsoft Cognitive Toolkit (https://cntk.ai) is a unified deep learning toolkit that describes
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l
An Open Source Machine Learning Framework for Everyone
Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a