• August 2014
    M T W T F S S

The Internet Was Delivered to the Masses; Parallel Computing Is Not Far Behind

Virginia Tech News (08/21/14)

Virginia Polytechnic Institute and State University (Virginia Tech) professor Wu Feng has been a leader in the field of parallel computing, especially in relation to the field of biomedicine. In the mid-2000s, Feng worked on a multi-institutional project to combine the capabilities of supercomputers at six U.S. institutions in an early example of parallel computing in the cloud. Feng recently has brought together funding from a wide range of sources, including the U.S. National Science Foundation and the National Institute of Health, to pursue research into ways of making the power of parallel computing more readily available to everyone. He says this has become increasingly important as the rate at which data is being generated dramatically outstrips the pace of advances in computing power. Feng says to handle the vast and ever-growing amounts of data generated in a number of fields and industries requires access to the power of parallel computing. To that end, Virginia Tech is establishing a new research center: Synergistic Environments for Experimental Computing. The center will focus on multidisciplinary efforts to design new algorithms, software, and hardware focusing on five areas of synergistic computing: the intersection of computer and physical systems, the health and life sciences, business and financial analytics, cybersecurity, and scientific simulation.


IBM Forging Bigger Power8 Systems, Adding FPGA Acceleration

Enterprise Tech Systems Edition (28/7/2014) Timothy Prickett Morgan

IBM launched its first servers based on the Power8 processors back in April, and the initial machines were aimed at scale-out clusters as well as at customers needing a modest standalone machine with one or two processor sockets to run their workloads. Big Blue was expected to focus initially on these scale-out machines, and was pretty vague about its plans for larger systems that gang up many more processors and larger memory footprints to go along with it.