Nallatech and SGI cooperate on pushing performance -

Nallatech and SGI cooperate on pushing performance

LONDON — Nallatech has signed a strategic collaborative arrangement with Silicon Graphics to develop new business opportunities within the high-performance computing market. New products and services will be based on SGI’s reconfigurable system technology and Nallatech’s field programmable gate array (FPGA) computing technology. Nallatech (Cumbernauld, U.K.) and SGI will work together to apply FPGA-based computing solutions for growth markets that could include oil and gas geophysical; homeland security; bioinformatics; medical imaging; and data distribution and visualization systems.

The collaboration is seen as a natural extension to SGI’s research and development initiatives focused on tightly coupling FPGAs into its shared-memory NUMAflex architecture, to provide an application-adaptive high-performance computing environment.

Dave Parry, senior vice president and general manager, server and platform group at SGI, said, “Working with Nallatech, we continue on SGI’s path toward delivering a revolutionary class of supercomputers that will catapult users into a new era of computing. Ultimately we plan to offer reconfigurable computing technology as one of the primary vehicles for accelerating application performance within SGI’s renowned high-bandwidth, low-latency multiparadigm computing architecture.” Allan Cantle, CEO of Nallatech, added, “Organizations that require highest levels of performance, reliability and flexibility in demanding processing applications will benefit from our shared resources and innovative technology.” The combination of Nallatech’s FPGA computing technology with SGI’s Reconfigurable Application-Specific Computing (RASC) systems and shared cross-market application expertise in a co-processor model, should create a solution for addressing the most demanding multicomputing problems. FPGAs allow for efficient implementation of highly parallel, compute-intensive functions which are required for real-time, data-intensive processing systems.

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