Open Source Mac Distributed Computing Software
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Distributed Computing Software for Mac
View 50 business solutionsBrowse free open source Distributed Computing software and projects for Mac 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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JupyterLab
JupyterLab computational environment
JupyterLab is the next-generation web-based user interface for Project Jupyter. Try it on Binder. JupyterLab follows the Jupyter Community Guides. JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner. You can arrange multiple documents and activities side by side in the work area using tabs and splitters. Documents and activities integrate with each other, enabling new workflows for interactive computing. JupyterLab also offers a unified model for viewing and handling data formats. JupyterLab understands many file formats (images, CSV, JSON, Markdown, PDF, Vega, Vega-Lite, etc.) and can also display rich kernel output in these formats. See File and Output Formats for more information. To navigate the user interface, JupyterLab offers customizable keyboard shortcuts and the ability to use key maps from vim, emacs, and Sublime Text in the text editor. -
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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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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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JPPF
The open source grid computing solution
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid. -
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Datahike
A durable Datalog implementation adaptable for distribution
Datahike is a durable Datalog database powered by an efficient Datalog query engine. This project started as a port of DataScript to the hitchhiker-tree. All DataScript tests are passing, but we are still working on the internals. Having said this we consider Datahike usable for medium sized projects, since DataScript is very mature and deployed in many applications and the hitchhiker-tree implementation is heavily tested through generative testing. We are building on the two projects and the storage backends for the hitchhiker-tree through konserve. We would like to hear experience reports and are happy if you join us. We provide a small stable API for the JVM at the moment, but the on-disk schema is not fixed yet. We will provide a migration guide until we have reached a stable on-disk schema. Take a look at the ChangeLog before upgrading. -
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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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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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GridSim allows modeling and simulation of entities in parallel and distributed computing systems such as users, applications, resources, and resource brokers/schedulers for design and evaluation of scheduling algorithms. http://www.gridbus.org/gridsim
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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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Pholcus
Distributed high-concurrency crawler software written in pure golang
Pholcus is a high-concurrency crawler software written in pure Go language that supports distributed, only used for programming learning and research. It supports three operating modes of stand-alone, server and client, and has three operating interfaces, Web, GUI, and command line; simple and flexible rules, concurrent batch tasks, and rich output methods (mysql/mongodb/kafka/csv/excel, etc.); In addition, it also supports horizontal and vertical grabbing modes, and a series of advanced functions such as simulated login and task suspension and cancellation. This software is only used for academic research, users need to abide by the relevant laws and regulations of their location, please do not use it for illegal purposes! Provide users with a certain Go or JS programming foundation with a heavyweight crawler tool that only needs to pay attention to rule customization and complete functions. -
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Ganglia
Scalable, distributed monitoring system for high-performance computing
Ganglia is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters. Supports clusters up to 2000 nodes in size. -
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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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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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Vine Server(OSXvnc) is a robust, full-featured VNC server for MacOS X. It allows VNC clients to remotely view or control the machine. It is provided by TestPlant, for use with Vine Viewer AND Eggplant for cross-platform testing,
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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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RealmForge (now Visual3D Game Engine)
1st 3D game engine built in C# for .NET, Visual3D Engine's predecessor
The first 3D game engine built in C# for .NET, predecessor to the Visual3D Game Engine (https://www.poweraccess.net/visual3d-game-engine), an All-in-One Game Development Tool for Next-Gen 3D Games, MMOs, Simulations and Virtual Worlds powered by Microsoft XNA. -
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Portable Linux
Portable Ubuntu Linux for Scientific Computing
Released August 22, 2013 Lubuntu Blends: Biochemistry 13.04 (Raring) v5.44 Linux Kernel Image 3.8.0-29 Lubuntu Blends are pre-installed Wubi disk image remixes of Ubuntu and Debian Science meta packages, A custom boot loader allows installations to be copied and automatically booted from most external or USB flash drives. Once up and running, use earlier Lubuntu Remix README instructions here until documentation is updated. https://sourceforge.net/projects/portable-linux/files/ Installation 1. Download the Wubi installer http://releases.ubuntu.com/saucy/wubi.exe 2. Install any flavor of Ubuntu. 3. Swap out the root.disk with the ones provided here. Overview LAMP stack running on localhost (127.0.0.1). Scientific, productivity & media packages include R (Rattle Data Miner), GridEngine, Condor, cooperative computing tools, WINE, LibreOffice, Evolution, Clinica, Neuro Debian Desktop, PsycoPy, OpenVibe, 3DSlicer, Paraview, Openshot. Cheers, Gregory Remington -
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eBus
Publish/Subscribe, Request/Reply Messaging API for Java.
A Java middleware API supporting broker-less, type+topic-based publish/subscribe and request/reply messaging for both intra- and inter-application, object-level communication. Broker-less: messages are transmitted directly between eBus applications. There is no message broker (i.e. server) in between. Type+topic addressing: eBus clients subscribe to a message class (type) and message topic, providing stronger typing than just topic-based subscriptions. Object-level communication: eBus delivers messages directly to client objects, not to a client process. -
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Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
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Jadex is a Belief Desire Intention (BDI) reasoning engine that allows for programming intelligent software agents in XML and Java. The resoning engine is very flexible.
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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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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.
