Capable exascale systems will be able to analyze massive volumes of data in less time, and power the advanced models and simulations required for discovering insights and answers to crucial scientific and technology challenges.
Scientific applications for high-performance and data analytic computing impact nearly every corner of research and development, from the physics of star explosions to squeezing the last percent of efficiency out of a jet engine.
Accelerate design and commercialization of next-generation small modular reactors.
Accurate regional impact assessment of climate change.
Scaling carbon capture/storage laboratory designs of multiphase reactors to industrial size.
Increase efficiency and reduce cost of turbine wind plants sited in complex terrains.
Design high-efficiency, low-emission combustion engines and gas turbines.
Predict and guide stable ITER operational performance with an integrated, whole-device model.
Additive manufacturing process design for qualifiable metal components.
Biofuel catalysts design; stress-resistant crops.
Accelerate and translate cancer research in RAS pathways, drug responses, and treatment strategies.
Retrofit and improve urban districts with new technologies, knowledge, and tools.
Cosmological probe of standard model (SM) of particle physics: inflation, dark matter, and dark energy.
QCD-based elucidation of fundamental laws of nature: SM validation and beyond SM discoveries.
Practical economic design of 1 TeV electron-positron high-energy collider with plasma wakefield acceleration.
Demystify origin of chemical elements
(> Fe); confirm LIGO gravitational wave and DUNE neutrino signatures.
Safe and efficient use of subsurface for carbon capture and storage, petroleum extraction, geothermal energy, and nuclear waste.
Leveraging microbial diversity in metagenomic data sets for new products and life-forms.
Simulations that fully exploit exascale can solve key problems in fission and fusion materials.
Reliable earthquake hazard and risk assessment in relevant frequency ranges.
Reliably and efficiently planning our nation’s grid for societal drivers: rapidly increasing renewable energy penetration and more active consumers.