SYSTEM@TIC PARIS-REGION is a competitive cluster aimed at making the Ile de France one of the few regions with a worldwide profile in terms of designing, building and harnessing complex systems.

Following the launch of various projects, including Num@tec Automotive (automotive transport), Usine Numérique (digital factory), Usine Logicielle (software factory) and IOLS (infrastructures and software tools for simulation), in March SYSTEM@TIC PARIS-REGION launched the FAME2 program. The aim of FAME2 is to adapt a new generation of HPC (High-Performance Computing) servers capable of processing huge volumes of data, by 2008. This new generation of machines will enable the construction of extremely powerful supercomputers, delivering several PetaFLOPS (million billion operations per second, Floating Point operations).

The FAME2 project will particularly focus on defining the hardware architecture and optimizing the Linux® kernel in an environment with several tens of thousands of processors. It will enable the validity of the chosen concepts to be demonstrated with the help of a prototype ahead of the manufacturing phase. The program also involves validating all the base software, libraries and optimization tools specifically required to implement simulation or information gathering applications using very large-scale databases (more than 50 Terabytes) in a multi-media, multi-lingual environment applicable both to life sciences and physical sciences.

The main players involved in the projects include major manufacturers and research laboratories, universities and SMEs: Bull, CAPS entreprise, the French Atomic Energy Authority (CEA), Dassault-Aviation, the Ecole Centrale de Paris, ILOG, the French National Petroleum Institute, the National Telecommunications Institute (INT at Evry), NewPhenix, Resonate MP4, the University of Evry and the University of Versailles Saint-Quentin. FAME2 has also been given the support of the French Industry Ministry and Yvelines Council, the local authority for the area hosting the project.

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or contact Claude Camozzi, the FAME project coordinator (claude.camozzi@bull.net)

SAS, global leader in business intelligence (BI) systems, and Bull are further strengthening their partnership with a new offering destined for the implementation of advanced BI solutions for ERP (Enterprise Resource Planning) environments. The new partnership applies in Europe.

Building on the two companies’ respective expertise in complex infrastructures and BI solutions, Bull and SAS will enable organizations to improve their business performance and strategic management using data collected from an ERP system.

A number of major customers have already decided to implement SAS®9 with direct access to an ERP, with the aim of controlling their business more effectively or introducing data mining. This is seen as a particularly effective approach when processing large volumes of data. So, Bull and SAS have, for example, worked together to develop a benchmark for Electricité de France (EDF) which has enabled this very large company to optimize response times of its global infrastructure by a factor of 10 and to validate its solution, initially used for some 170,000 business customers and eventually by three million customers.

“The quality and performance of SAS solutions running on Bull servers enables very large volumes of data to be processed, enabling us to optimize our marketing programs and control our activities in the business marketplace more effectively,” underlined Philippe Futtersack, Project Manager in the CRM Analysis Department of EDF’s Commercial Division.

In the area of BI and ERP systems, Bull capitalizes on the expertise of its consultants in France and elsewhere in Europe, and has also established SAS and SAP centers of excellence, which are charged with defining and specifying architectures. These centers also get involved in the implementation and optimization of applications running on Bull NovaScale, Escala and E xpress 5800 servers. Bull experts work in close collaboration with SAS’s support and R&D teams.