Massive Data Volumes No Match for Scalable, I/O-Centric Altix ICE Platform and New Memory-Optimized Xeon Processors
SUNNYVALE, Calif., March 30 /PRNewswire-FirstCall/ -- Silicon Graphics, Inc. (SGI) today unveiled another solution for enterprises and businesses with data-intensive computing environments who are struggling to derive timely results and insights from ever-larger volumes of data.
Coinciding with today's worldwide launch of the Intel(R) Xeon(R) processor 5500 series (code-named Nehalem), Silicon Graphics announced it will feature the next-generation processor in it's award-winning SGI(R) Altix(R) ICE integrated blade platform.
By integrating the scalable, I/O-intensive SGI Altix ICE platform with the high-bandwidth memory design of the Intel(R) Xeon(R) processor 5500 series, Silicon Graphics is delivering a unique solution that helps organizations avoid the costly performance inefficiencies that can occur when large data sets and intense processing overwhelm the comparatively slow memory, I/O and interconnect infrastructures of other commodity Linux(R) clusters.
'To remain competitive, users today require their IT platforms to deliver results much sooner, even as their applications increase in complexity and data sets grow exponentially,' said Silicon Graphics CEO Bo Ewald. 'The SGI Altix ICE platform is unique in its rich I/O infrastructure and high-bandwidth interconnect design, which makes it an ideal platform for solving big data problems with the new Intel(R) Xeon(R) processor 5500 series.'
'Working with fast-growing data volumes is a constant challenge for our application development teams, whose work spans chemistry, materials (including nanoscience) research, astrophysics, climate research, biology and other disciplines,' said Jeffrey Vetter, Future Technologies Group Leader at the Department of Energy's Oak Ridge National Laboratory, which conducts state-of-the-art research and development in emerging architectures and computational sciences. 'Our early evaluation of Nehalem demonstrated significant performance improvements on many of our important applications.
