Preparing for Exascale Science on Day 1

ESP research projects are in the areas of chemistry, physics (high energy physics, fusion energy, cosmology), biosciences (cancer treatment informatics, modeling metastasis, brain connectomics, molecular dynamics of cell membrane transport proteins), engineering (aerodynamics, nuclear reactor coolant, combustion in coal boilers), materials science (functional materials, semi-conductors).

William Tang, professor of astrophysical sciences at Princeton University and principal research physicist with the DOE’s Princeton Plasma Physics Laboratory (PPPL), is leading an ESP project that is one of the more successful efforts in artificial intelligence (AI) for science using pre-exascale systems. His work is focused on using deep learning and exascale computing power to improve the behavior of fusion reactors aiming to produce sustainable clean energy.  Tang’s AI research studies disruptions in confinement devices called tokamaks, which use a powerful magnetic field to confine hot plasma to produce controlled thermonuclear fusion power.

Engineers working with the potential energy source have estimated a window

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