>
Thune Moves Forward With 'Nuclear Option' To Confirm Trump's Nominees
Father Of Ukrainian Girl Brutally Murdered In US Missed Funeral Due To Martial Law
The Assassination of Charlie Kirk
Shell promises 10-minute EV charging with its magical battery fluid
Tesla Megapack Keynote LIVE - TESLA is Making Transformers !!
Methylene chloride (CH2Cl?) and acetone (C?H?O) create a powerful paint remover...
Engineer Builds His Own X-Ray After Hospital Charges Him $69K
Researchers create 2D nanomaterials with up to nine metals for extreme conditions
The Evolution of Electric Motors: From Bulky to Lightweight, Efficient Powerhouses
3D-Printing 'Glue Gun' Can Repair Bone Fractures During Surgery Filling-in the Gaps Around..
Kevlar-like EV battery material dissolves after use to recycle itself
Laser connects plane and satellite in breakthrough air-to-space link
Lucid Motors' World-Leading Electric Powertrain Breakdown with Emad Dlala and Eric Bach
Murder, UFOs & Antigravity Tech -- What's Really Happening at Huntsville, Alabama's Space Po
U.S. Department of Energy's Argonne National Laboratory and Hewlett Packard Enterprise (NYSE: HPE) unveiled a new testbed supercomputer to prepare critical workloads for future exascale systems that will deliver up to four times faster performance than Argonne's current supercomputers.
Polaris will enable scientists and developers to test and optimize software codes and applications to tackle a range of artificial intelligence (AI), engineering and scientific projects planned for the forthcoming exascale supercomputer, Aurora, a joint collaboration between Argonne, Intel and HPE.
The $500+ million Exaflop Aurora was planned for 2021 but it has been delayed until 2022-2023. Aurora has been delayed waiting for Intel's Sapphire Rapids server chips. The first plan was for a 180 petaflop Aurora for 2018 but delays in earlier Intel chips caused the need for a new plan.
Polaris will deliver approximately 44 petaflops of peak double precision performance and nearly 1.4 exaflops of theoretical AI performance, which is based on mixed-precision compute capabilities. Polaris 1.4 AI ExaFLOPS does not use standard FP64 (64 bit floating point) for standard supercomputer performance metrics.