Monthly Archives: July 2017

Argonne Puts Computation Muscle Behind Cancer Code

Argonne goes deep to crack cancer code   “Precision medicine is the ability to fine tune a treatment for each patient based on specific variations, whether it’s their genetics, their

Exploring the Potential of New Hybrid Computing Architectures

Oak Ridge National Laboratory is bringing on D-Wave Systems to use quantum computing as an accelerator for the Exascale Computing Project.

Berkeley Lab Researchers Share Best Paper Award at Intel Workshop

Researchers from Berkeley Lab are co-authors of a paper receiving a best paper award at the June 22 Intel Xeon Phi User's Group workshop.

New Berkeley Lab Algorithms Extract Biological Structure from Limited Data

A team of researchers from the Lawrence Berkeley National Laboratory has developed a new algorithmic framework called multi-tiered iterative phasing that utilizes advanced mathematical techniques to determine 3D molecular structure from very sparse sets of noisy, single-particle data.

Helping Scientists Save Time and Strengthen Software Development

A mathematical, or numerical, software library is a collection of algorithms and software that can make the development of scientific applications better, faster, and cheaper. The Extreme-Scale Scientific Software Development Kit project coordinates and enables dependable mathematical software libraries designed and developed for exascale platforms.

New Algorithms Help Extract 3-D Biological Structure from Limited Data

New collaboration initiative between SLAC National Accelerator Laboratory, CAMERA, the National Energy Research Scientific Computing Center (NERSC) and Los Alamos National Laboratory as part of DOE’s Exascale Computing Project (ECP).

ANL’s Rajeev Thakur: An Exascale Software Stack

ANL's Rajeev Thakur: Breaking Down the Exascale Software Stack

Coupled Monte Carlo Neutronics and Fluid Flow Simulations of Small Modular Reactors

Exascale will allow for a new generation of nuclear that works smart on the electric grid and help maximize the efficiency and increase the lifespan of current US nuclear reactors.

Exascale Predictive Wind Plant Flow Physics Modeling

Wind is an abundant and secure energy resource and could one day supply up to 30 percent of electrical power in the United States. Scientists have made great improvements in wind turbine efficiency, but to advance wind energy and harness its full potential, they need exascale computing.

ECP Director Paul Messina Discusses the ECP’s PathForward Program on Federal News Radio

ECP Director Paul Messina Discusses the ECP's PathForward Program on Federal News Radio

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