Search Results for "parallel"

Parallel text aligner dessigned to generate transation memories (TMX files) from two files tagged with any kind of XML-based tags. The application uses the tag structure and the text blok length to perform the alignment.

Freemat is an interpreted, matrix-oriented development environment for engineering and scientific applications, similar to the commercial package MATLAB. Freemat provides visualization, image manipulation, and plotting as well as parallel programming.

jAgg is a Java 5.0 API that supports “group by” operations on Lists of Java objects: aggregate operations such as count, sum, max, min, avg, and many more. It supports Super Aggregation: Rollups, Cube, and Grouping Sets. It supports analytic operations such as lag/lead and row number and more. It also allows custom aggregate and analytic operations.

The Thot toolkit repository has moved to http://daormar.github.io/thot/ Thot is a toolkit for statistical machine translation. The new Thot toolkit includes fully automatic and interactive machine translation, incremental training of statistical models, parallel estimation, ...

ProC 3.0 is a scientific workflow engine to build, manage and execute workflows (pipelines) in heterogeneous environments, supporting GRID and other means of parallel processing. It includes a data management component (DMC) to transparently access databases for storage of results and automatically adds metadata to track the processing of data products, so that at every time a full processing history is available. The software was developed and used within the ESA Planck satellite mission.

Clique percolation method On Steroids (COS) enable k-clique communities to be detected, in parallel, from large-scale networks. Its low memory requirements, together with its linear speedup, make it really efficient, even on dense, highly interconnected networks. COS should be the method of choice for k-clique community detection aiming at very high performance and low resource requirements.

...CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. Currently, when training corpus, compared with CRF++, CRF# can make full use of multi-core CPUs and only uses very low memory, and memory grow is very smoothly and slowly while amount of training corpus, tags increase. with multi-threads process, CRF# is more suitable for large data and tags training than CRF++ now. ...

A Machine Learning and Data Retrieval Framework

Cloudster is a generic and parallel implementation of the k-means algorithm. It is written in C# and uses the Windows Azure environment.

We are using a large archive of newspaper stories(GigaWordCorpus) as input to a parallel MPI program, and produce from that a list of top R terms of varying lengths M through N that are especially interesting. The program is done in C using MPI.

Parallel IBDWS is an upgrade from IBDWS that utilizes parallel processing. Also, the incorporation of DNA sequence data has been added since the last code release

FlexCRFs: A Flexible Conditional Random Fields Toolkit for Labeling and Segmenting Sequence Data (this includes a parallel implementation of CRFs called PCRFs to support training CRF models on massively parallel computer systems).

WebDip is a platform for the tracking of information search in a psychological decision making experiment. It enables to run parallel experiments, with different search modes and comfortabel user management.

A distributed/parallel implementation of SPM. It allows SPM to be run on multiple processors/computer using the Message Passing Interface (MPI). Primarily, it is designed to parallelize all the pre-processing steps and simple first-level statistical ana

Incridge - A Software Tool for Scalable, Parallel, Incremental and Decremental Classification based on Support Vector Machine (SVM) Approximation Algorithms. Possible use include: web usage mining, bioinformatics and spam-classification.

Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.