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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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Crowdtesting That Delivers | TesteumTesteum connects your software, app, or website to a worldwide network of testers, delivering detailed feedback in under 48 hours. Ensure functionality and refine UX on real devices, all at a fraction of traditional costs. Trusted by startups and enterprises alike, our platform streamlines quality assurance with actionable insights.
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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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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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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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Deliver secure remote access with OpenVPN.OpenVPN's products provide scalable, secure remote access — giving complete freedom to your employees to work outside the office while securely accessing SaaS, the internet, and company resources.
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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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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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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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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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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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Tyrex provides J2EE services for security and authentication, local and distributed transactions, resource configuration and pooling, and TP monitoring.
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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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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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HPCC Systems
End-to-end big data in a massively scalable supercomputing platform.
HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and decisions. HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single, complete end-to-end architecture for efficient processing. Read our blog (http://hpccsystems.com/blog ), or connect with us on Twitter (@hpccsystems), Facebook (https://www.facebook.com/hpccsystems ) and LinkedIn (http://www.linkedin.com/company/hpcc-systems) HPCC Systems is available on AWS & can be configured through the Instant Cloud Solution. -
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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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omniEvents is an implementation of the OMG Event Services Specification v1.1 for omniORB, a CORBA Object Request Broker for C++ and Python.
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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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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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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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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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IIOP.NET allows a seamless interoperation between .NET, CORBA and J2EE distributed objects. This is done by incorporating CORBA/IIOP support into .NET, leveraging the remoting framework.
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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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A Console-based BitTorrent Client with built-in scheduler for handling multiple sessions. It is designed to manage sessions in queue easily without heavy-weight GUI. External module can search for new torrents in trackers and submit it automatically.
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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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