Intel to build $200 million Supercomputer for US Department of Energy

Intel has been selected by US Department of Energy to built $200 Mn Supercomputers named as Theta and Aurora, these systems are part of Argonne National Labs project CORAL

Santa Clara, California headquartered Intel Inc. [NASDAQ:INTC] has been awarded a contract by US Department of Energy to produce two Supercomputers. The Supercomputers would be based at Argonne National Laboratory in Illinois. This is a major win for Intel which wants to consolidate its position as largest producer of Chips in the world.

Intel Inc’s arm Intel Federal LLC has partnered with Seattle based Cray Inc. (which is a Supercomputer manufacturer) to build this Supercomputer. The Supercomputers are part of CORAL venture to build   for Argonne Leadership Computing Facility (ALCF). CORAL is a joint collaboration of three labs Oak Ridge, Argonne and Lawrence to help build fastest Supercomputers much ahead of any Supercomputer till date.

The Supercomputers will be called Theta and Aurora to be released in 2016 and 2018 respectively. While the Theta system will have a peak performance of 8.5 Petaflops, Aurora will have a peak performance of 180 Petaflops. Petaflops is a unit of measuring a Supercomputer’s performance. 1 Petaflops is equal to 1 Quadrillion Floating Operations per Second.

According to Mr. Raj Hazra, vice president, Data Center Group and general manager, Technical Computing Group at Intel – “The selection of Intel to deliver the Aurora supercomputer is validation of our unique position to lead a new era in HPC”

Aurora system will be deployed to research on a number of topics including better and more efficient solar batteries, improved bio-fuels, efficient engines and wind turbine engines. Aurora system will be based on Intel’s Xeon Phi processors and Intel Omni-Path Fabric Interconnect. This system will be built on Intel’s HPC Scalable System Framework. This Framework is highly power-efficient, more reliable, high in performance and support both compute and data intensive work.