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Sometime next year, managers at the US Department of Energy’s (DOE) Argonne National Laboratory in Lemont, IL, will power up a calculating machine the size of 10 tennis courts and vault the country into a new age of computing. The $500-million mainframe, called Aurora, could become the world’s first “exascale” supercomputer, running an astounding 1018, or 1 quintillion, operations per second.Rows of cabinets hold incredible processing power for one of the world's best supercomputers, Summit, at Oak Ridge National Laboratory in TN. Exascale computing will surpass these existing computers by leaps and bounds. Image credit: Flickr/Oak Ridge National Laboratory, licensed under CC BY 2.0.Aurora is expected to have more than twice the peak performance of the current supercomputer record holder, a machine named Fugaku at the RIKEN Center for Computational Science in Kobe, Japan. Fugaku and its calculation kin serve a vital function in modern scientific advancement, performing simulations crucial for discoveries in a wide range of fields. But the transition to exascale will not be easy. “As these machines grow, they become harder and harder to exploit efficiently,” says Danny Perez, a physicist at Los Alamos National Laboratory in NM. “We have to change our computing paradigms, how we write our programs, and how we arrange computation and data management.”That’s because supercomputers are complex beasts, consisting of cabinets containing hundreds of thousands of processors. For these processors to operate as a single entity, a supercomputer needs to pass data back and forth between its various parts, running huge numbers of computations at the same time, all while minimizing power consumption. Writing programs for such parallel computing is not easy, and theorists will need to leverage new tools such as machine learning and artificial intelligence to make scientific breakthroughs. Given these challenges, researchers have …

Nascent exascale supercomputers offer promise, present challenges