Search Results for "high performance computing"

GridLAB-D is a new power system simulation tool that provides valuable information to users who design and operate electric power transmission and distribution systems, and to utilities that wish to take advantage of the latest smart grid technology. It incorporates advanced modeling techniques with high-performance algorithms to deliver the latest in end-use load modeling technology integrated with three-phase unbalanced power flow, and retail market systems. Historically, the inability to effectively model and evaluate smart grid technologies has been a barrier to adoption; GridLAB-D is designed to address this problem. User documentation can be found at: http://gridlab-d.shoutwiki.com/wiki/Quick_links The source code is available from GitHub. ...

...Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data Creation, Meta Data Discovery, Anomaly Discovery, Data Cleansing, Reporting and Analytic. It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. ...

GISBox by Citiviz is a ready-to-use virtual appliance containing an assortment of powerful, free and open source GIS, Data Mining and Analysis, Modelling and Programming software and packages. The pre-configured and tested GISBox allows you to try and use in few minutes a variety of software used by data scientists, engineers, physicists, mathematicians, geomatics engineers, and geographers from around the globe, without installing anything more than once the Oracle VirtualBox™ software...

This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so any help shall be welcome. ...

...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.

PerfParse. Storage and analysis of binary performance data produced by Nagios. High quality accurate graphs of live data from standard Nagios plugins. Permanent history of plugin results with advanced analysis tools.

A high-performance implementation of bloom filters, a lightweight duplicate detection algorithm.

The Toolkit for Advanced Discriminative Modeling (TADM) is a C++ implementation for estimating the parameters of discriminative models, such as maximum entropy models. It uses the PETSc and TAO toolkits to provide high performance and scalability.

Comprehensive & high performance data distribution &transformation system. Features a simple, user-friendly event driven scripting interface transparently generates & execs highly efficient Perl/C code. Uses:ETL,datawarehousing,statistics,data-cleansing.

PyVisi is the Python visualisation interface: a generic Python-based interface to many different scientific visualisation packages. PyVisi is intended for use in both standard and high-performance computing environments, and with the escript package.

Celerity, an open-source, Java based data-flow architecture that provides high performance with fine data granuality. Celerity offers a module based programming environment, which can parrellelize across processors, machines and architectures.

ktdata is a C++ library for accessing tabular data, like from CSV files. Its goals are: 1. object design 2. portability (Linux and Windows support at least) 3. high performance 4. support for common data file formats, like CSV, ARFF (Weka), etc.