ProActive Distributed R Language integrates with the R Project for Statistical Computing to allow distributed and remote execution of R functions on heterogeneous infrastructures (Linux, Windows, MacOS X) through a powerful and user-friendly API directly from R command-line interpreter.
The R Language is widely used among statisticians and data miners for developing statistical software and data analysis. R provides a wide variety of statistical and graphical techniques, including linear and non linear modeling, classical statistical tests, time-series analysis, classification, clustering, and others. It is used in various domains such as Finance, Biology and BioTech, and is easily extensible.
ProActive Distributed R Language comes as standard R package, which connects to ProActive Workflows & Scheduling.Top
ProActive Distributed Spark allows to interface many Apache Spark clusters. All Spark clusters are accessed from one interface, and are monitored as a whole. Spark jobs are scheduled to efficiency utilize the current infrastructure.
Spark is a programming language intended for development on high integrity software used in systems where predictable and highly reliable operation is essential. It facilitates the development of applications that demand safety, security or business intelligence.
ProActive Distributed Spark comes as standard Spark package, which connects to ProActive Workflows and Scheduling.Top
ProActive Distributed Hadoop allows to interface many Apache Hadoop clusters. All Hadoop clusters are accessed from one interface, and are monitored as a whole. Hadoop jobs are shceduled to efficiently utilize the current infrastructure.
Apache Hadoop is an open-source software framework written in Java for distributed processing of very large data sets on computer clusters built from commodity hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are commonplace and thus should be automatically handled in software by the framework.
ProActive Distributed Hadoop comes as standard Hadoop package, which connects to ProActive Workflows and Scheduling.Top
ProActive Distributed Matlab seamlessly distributes your Matlab models and programs from your interactive Matlab environment to various resources such as your colleagues desktop machines, company servers and clusters, Grids including other company sites, and private or Hybrid Clouds. Matlab sources, your current interactive environment, input files, parameters and results are transparently transferred over the network to the target machines.
Compared to Mathworks Parallel Computing Toolbox™ and Distributed Computing Server™, ProActive Distributed Matlab is more flexible, and can deploy on heterogeneous infrastructures (combined Windows, Linux and Mac Desktops, Cloud Virtual Machines) and can even optimize the usage of Matlab Software Licences with the ProActive Licence Saver and its FlexLM integration.
ProActive Distributed Matlab comes as a standard Matlab Toolbox, which connects to ProActive Workflows & Scheduling.Top
ProActive Distributed Scilab allows distributed and remote execution of Scilab computations directly from the Scilab environment. It provides the same functionalities as the Matlab integration described above and furthermore the same API, allowing users to switch very easily from one connector to the other.
Scilab is a free, open source equivalent to Matlab. It offers the same basic functionalities such as easy matrix manipulation, implementation of algorithms, interfacing. It is known as Matlab’s best open source alternative.
ProActive Distributed Scilab comes as a standard ATOMS Scilab Module, which connects to ProActive Workflows & Scheduling.Top
ProActive License Saver offers deep integration with FlexLM to monitor token activity and schedule licence-based tasks only when enough tokens are available.
FlexLM is one of the most commonly used License Management System.Top