Open Source Windows Distributed Computing Software
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Distributed Computing Software for Windows
View 76 business solutionsBrowse free open source Distributed Computing software and projects for Windows below. Use the toggles on the left to filter open source Distributed Computing software by OS, license, language, programming language, and project status.
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TurboVNC
High-speed, 3D-friendly, TightVNC-compatible remote desktop software
TurboVNC is a high-performance, enterprise-quality version of VNC based on TightVNC, TigerVNC, and X.org. It contains a variant of Tight encoding that is tuned for maximum performance and compression with 3D applications (VirtualGL), video, and other image-intensive workloads. TurboVNC, in combination with VirtualGL, provides a complete solution for remotely displaying 3D applications with interactive performance. TurboVNC's high-speed encoding methods have been adopted by TigerVNC and libvncserver, and TurboVNC is also compatible with any other TightVNC derivative. TurboVNC forked from TightVNC in 2004 and still covers all of the TightVNC 1.3.x features, but TurboVNC contains numerous feature enhancements and bug fixes relative to TightVNC, and it compresses 3D and video workloads much better than TightVNC while using generally only 5-20% of the CPU time of the latter. Using non-default settings, TurboVNC can also be made to compress 2D workloads as "tightly" as TightVNC. -
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Xming X Server for Windows
X Window System Server for Windows
Xming is the leading X Window System Server for Microsoft Windows 8/7/Vista/XP (+ server 2012/2008/2003). It is fully featured, small and fast, simple to install and because it is standalone native Microsoft Windows, easily made portable (not needing a machine-specific installation). -
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Zipkin
Distributed tracing system to gather timing data
Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in service architectures. Features include both the collection and lookup of this data. If you have a trace ID in a log file, you can jump directly to it. Otherwise, you can query based on attributes such as service, operation name, tags and duration. Some interesting data will be summarized for you, such as the percentage of time spent in a service, and whether or not operations failed. The Zipkin UI also presents a Dependency diagram showing how many traced requests went through each application. This can be helpful for identifying aggregate behavior including error paths or calls to deprecated services. Applications need to be “instrumented” to report trace data to Zipkin. -
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Antseed
An open market for AI inference. No gatekeepers
Antseed is a free, open-source peer-to-peer network for discovering, providing, and accessing AI inference services without a centralized gateway. It connects AI service providers with consumers through a distributed hash table and encrypted peer-to-peer communications. Providers can offer services backed by local Ollama models, Anthropic, OpenAI-compatible APIs, or specialized AI workflows. Buyers discover available providers and route requests according to pricing, latency, and reputation scores. A local HTTP proxy exposes OpenAI- and Anthropic-compatible endpoints for existing applications. Its command-line interface supports configuring provider services, routing preferences, and network connections. Modular plugins allow developers to extend supported models and routing behavior. The project includes infrastructure for request metering, provider discovery, and payment coordination. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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SocketTest - powerful and small software tool for socket testing. It can create both TCP and UDP client or server. It can be used to test any server or client that uses TCP or UDP protocol to communicate.
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Tyrex provides J2EE services for security and authentication, local and distributed transactions, resource configuration and pooling, and TP monitoring.
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MX4J is an Open Source implementation of the Java Management Extensions technology, for both JSR 3 (JMX) and JSR 160 (JMX Remote API).
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A distributed, peer-to-peer, server-less communication & messaging solution for JAVA (JMS), C++ and .NET applications, integrates with JBoss, WebLogic & WebSphere. Offers guaranteed delivery, security and transactions. Supports TCP, SSL & HTTP protocols.
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Blazegraph (powered by bigdata)
Fast, scalable, robust graph database platform
Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/. -
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Render Farm Manager, Project Tracker.
CGRU: Afanasy render farm manager and RULES project tracker.
CGRU is an open source CG tools pack, includes Afanasy render farm manager and RULES project tracker. -
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DelphiWebStart (DWS) is an Application Loader with TCP Sockets based on a ThinClient first spread over the Web, VPN or Intranet. So a user can download data (exes, maps, files) from a list and start it. DWS supports OpenSSL including a PKI HTTPS-Server.
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MARIE is a robotic development and integration environment focused on software reusability and exploitation of already available APIs and middlewares used in robotics. Its main purpose is to create a rapid-prototyping approach to robotics developments.
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FRODO 2
Open-Source Framework for Distributed Constraint Optimization (DCOP)
FRODO is a Java platform to solve Distributed Constraint Satisfaction Problems (DisCSPs) and Optimization Problems (DCOPs). It provides implementations for a variety of algorithms, including DPOP (and its variants), ADOPT, SynchBB, DSA... -
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RabbitRemoteControl
Remote control. Support VNC, RDP, Terminal, SSH, TELNET etc
Rabbit Remote Control is a open-source, cross-platform, multi-protocol remote control software. Allows you to use any device and system in anywhere and remotely manage any device and system in any way. Its goal is to be simple, convenient, security and easy to use, improving work efficiency. It include remote desktop, remote control, file transfer(FTP, SFTP), terminal, remote terminal(SSH, TELNET), player, network tools etc functions. This is only a read-only mirror repository. Main repository: https://github.com/KangLin/RabbitRemoteControl -
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Kraken
P2P Docker registry capable of distributing TBs of data in seconds
Kraken is a P2P-powered Docker registry that focuses on scalability and availability. It is designed for Docker image management, replication, and distribution in a hybrid cloud environment. With pluggable backend support, Kraken can easily integrate into existing Docker registry setups as the distribution layer. Kraken has been in production at Uber since early 2018. In our busiest cluster, Kraken distributes more than 1 million blobs per day, including 100k 1G+ blobs. At its peak production load, Kraken distributes 20K 100MB-1G blobs in under 30 sec. Kraken is capable of distributing Docker images at > 50% of max download the speed limit on every host. Cluster size and image size do not have a significant impact on download speed. Support uploader authentication and data integrity protection through TLS. Other than pluggable storage, Kraken only has an optional dependency on DNS. -
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GloVe
GloVe model for distributed word representation
GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space. The links provided contain word vectors obtained from the respective corpora. If you want word vectors trained on massive web datasets, you need only download one of these text files! Pre-trained word vectors are made available under the Public Domain Dedication and License. If the web datasets above don't match the semantics of your end use case, you can train word vectors on your own corpus. The demo.sh script downloads a small corpus, consisting of the first 100M characters of Wikipedia. It collects unigram counts, constructs and shuffles cooccurrence data, and trains a simple version of the GloVe model. It also runs a word analogy evaluation script in python to verify word vector quality. -
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Madara
Middleware for distributed applications
The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. This project is currently in process of being ported from http://madara.googlecode.com. -
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SBW (Systems Biology Workbench)
Framework for Systems Biology
The Systems Biology Workbench(SBW) is a framework for application intercommunications. It uses a broker-based, distributed, message-passing architecture, supports many languages including Java, C++, Perl & Python, and runs under Linux,OSX & Win32. It comes with a large number of modules, encompassing the whole modeling cycle: creating computational models, simulating and analyzing them, visualizing the information, in order to improve the models. All using community standards, such as SED-ML, SBML and MIRIAM. -
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Joone is a neural net framework written in Java(tm). It's composed by a core engine, a GUI editor and a distributed training environment and can be extended by writing new modules to implement new algorithms or architectures starting from base component
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MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
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ClusterIt is a collection of clustering tools to allow simple administration of groups of UNIX machines. It can also be used to facilitate parallel shell scripting, and compiling.
