Exascale Computing Project Contributes to Accelerating Cancer Research
The Exascale Computing Project's CANDLE application will improve cancer research techniques and clinical outcomes
The Exascale Computing Project's CANDLE application will improve cancer research techniques and clinical outcomes
The CANcer Distributed Learning Environment (CANDLE) project provides deep-learning computing methodologies for accelerating cancer research.
ECP plays key support roles in the CANDLE project, which is addressing three significant science challenge problems in cancer research.
ECP's Data and Visualization portfolio is delivering data management software to store, save state, share, and facilitate the analysis of exascale data.
Machine learning, artificial intelligence, and data analytics are converging with high-performance computing to advance scientific discovery.
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.
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.
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.
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).