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XLcloud aims to define and demonstrate the principles of HPC as a Service (High Performance Computing) for all those applications that involve highly intensive calculations. XLcloud is designed as a collaborative tool that enables users to work together on highly sophisticated software in the Cloud, thus sidestepping the need for individuals to have to purchase expensive software on their own. XLcloud combines the expertise of companies and academics that are innovative in the field of high performance computer architectures and flow visualization HD/3D and video. While many Internet-based applications are now available on the Cloud, high-performance applications still face a number of technological obstacles before they are cloud ready. For example, high performance applications often need large capacity processing, lots of storage and huge network bandwidth, needs that are difficult to meet in today’s Cloud. In developing HPC as a Service (HaaS), XLcloud has identified the following high performance applications involving research and industrial innovation: * Research environments such as universities or technical institutes where high performance computing is a requirement, * Online game applications, * Online streaming video in real time, * Search engines in real time, * Online three-dimensional imaging for medical use.

Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems: * Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine. * Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete. * Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

Apache Commons Crypto is a cryptographic library optimized with AES-NI (Advanced Encryption Standard New Instructions). It provides Java API for both cipher level and Java stream level. Developers can use it to implement high performance AES encryption/decryption with the minimum code and effort. Please note that Crypto doesn't implement the cryptographic algorithm such as AES directly. It wraps to OpenSSL or JCE which implement the algorithms. Features -------- 1. Cipher API for low level cryptographic operations. 2. Java stream API (CryptoInputStream/CryptoOutputStream) for high level stream encryption/decryption. 3. Both optimized with high performance AES encryption/decryption. (1400 MB/s - 1700 MB/s throughput in modern Xeon processors). 4. JNI-based implementation to achieve comparable performance to the native C/C++ version based on OpenSsl. 5. Portable across various operating systems (currently only Linux/MacOSX/Windows); Apache Commons Crypto loads the library according to your machine environment (it checks system properties, `os.name` and `os.arch`). 6. Simple usage. Add the commons-crypto-(version).jar file to your classpath. Export restrictions ------------------- This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, possession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check your country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see if this is permitted. See <http://www.wassenaar.org/> for more information. The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache Software Foundation distribution makes it eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for both object code and source code. The following provides more details on the included cryptographic software: * Commons Crypto use [Java Cryptography Extension](http://docs.oracle.com/javase/8/docs/technotes/guides/security/crypto/CryptoSpec.html) provided by Java * Commons Crypto link to and use [OpenSSL](https://www.openssl.org/) ciphers

Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive, diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come to the mailing lists to find out more. Currently Mahout supports mainly four use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session, shopping cart content) and identifies, which individual items usually appear together.

Alphatier is a resource management library. It is designed to allow different schedulers to share the resources of a pool of executors in order to execute tasks with those. Read the [detailed documentation](#io.alphatier.pools) below to get an in-depth understanding. ## License Copyright &copy; 2014 [Tobias Sarnowski](mailto:[email protected]), [Willi Schönborn](mailto:[email protected]) Permission to use, copy, modify, and distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. ## Usage The library is written in [Clojure](http://clojure.org/) and is available in the [central Maven repository](https://repo1.maven.org/maven2/io/alphatier/alphatier/): <dependency> <groupId>io.alphatier</groupId> <artifactId>alphatier</artifactId> <version>0.3.0</version> </dependency> The library is written in pure Clojure without [ahead-of-time compilation](http://clojure.org/compilation). This means, that the library does not contain any *.class files. If you work with Clojure, this is not a problem but if you like to use the library from another JVM language (like Java, Scala or Groovy), you can use [Clojure's built-in tools](http://clojure.org/java_interop#Java%20Interop-Calling%20Clojure%20From%20Java) for interoperability or try our Java library: [https://github.com/sarnowski/alphatier-java](https://github.com/sarnowski/alphatier-java) ### Development If you like to change this library, please have a look at the [README](README.md). Development is done via [Github](https://github.com/sarnowski/alphatier).

BEhavioural Agents Simple Testing Tool - BEAST Tool The aim of this project is the development of a system which allows Behavior Driven Development (BDD) in Multi-Agent Systems (MAS), to make testing practices more accessible and intuitive to everybody. In one hand, in order to let tests be writable by newcomers and experts alike, system must allow the redaction of tests in plain text, because client does not need to have knowledge of our code. This plain text will be traduced to software later. The definition of test will be realized with the terminology Given-When-Then, which allows trace an easy guide of the behavior of a given scenario when something happened. In the other hand, due to the complexity of MAS, making unit testing of an agent that needs the interaction with others is almost impossible until the whole system is finished. This implies to leave testing issues to the end of the project, generating big troubles in case of malfunction. Consequently, its necessary to carry out a tool to allow the creation of mock agents and to perform tests during the whole development process. Therefore another objective of our systems is to include a mocking tool which permits testing continuously. Definitively, our tool allows the testing of any MAS in the development process, increasing its modularity and decreasing its elaboration and testing cost. These tests will be written in plain text so that anyone would be able to understand them. For further reading, a paper published in ITMAS2012 workshop can be found in: http://scholar.google.es/citations?view_op=view_citation&hl=es&user=mT3KgXUAAAAJ&citation_for_view=mT3KgXUAAAAJ:Tyk-4Ss8FVUC