National Institutes of Health (NIH)

Supporting Scientific Discovery and Data Analysis in the Exascale Era

ECP's Data and Visualization portfolio is delivering data management software to store, save state, share, and facilitate the analysis of exascale data.

Delivering Exascale Machine Learning Algorithms and Tools for Scientific Research

Machine learning, artificial intelligence, and data analytics are converging with high-performance computing to advance scientific discovery.

A Potential Revolution for X-Ray Free-Electron Laser Facilities

Higher resolution and deeper insight along with much faster information delivery are ways exascale computing could improve imaging at X-ray free-electron laser facilities.

Spotlight on ECP’s Cancer Distributed Learning Environment (CANDLE) Project

In a video chat, Rick Stevens, principal investigator for the Cancer Distributed Learning Environment (CANDLE) project within ECP, shares information about, and highlights from, CANDLE, a collaborative effort involving four US Department of Energy national laboratories.

Energy Department Advances Supercomputing in Fight Against Cancer

From harnessing the power of the atom to sequencing the human genome, the Department of Energy (DOE) has a long history of developing cutting-edge science and technology. One of the fresh challenges DOE has taken on is the use of supercomputers to accelerate cancer research.

Lighting the Way to Exascale Precision Medicine

Rick Stevens of Argonne National Laboratory spoke with ECP Communications at SC17 in Denver about the ECP project he leads, called CANcer Distributed Learning Environment (CANDLE).

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