Featured Publication Summaries
Feature extraction and visualization algorithm improves functional memory and research outcomes in multiphase flow simulation analysis
By Galen Fader Oak Ridge National Laboratory A joint research team funded by the Department of Energy’s Exascale Computing Project (ECP) has created a novel end-to-end analytics and visualization program for solving domain-specific issues in multiphase flow simulations. The program operates alongside MFIX-Exa, a massively parallel CFD-DEM (computational fluid dynamics–discrete element model) code designed to […]
A team working on the ECP’s Exascale Atomistic Capability for Accuracy, Length, and Time (EXAALT) project has developed a task-level speculative method that maximizes parallelism and computational throughput at large scales by predicting whether task-level outputs will be used in subsequent executions.
Novel algorithm delivers flexibility, efficiency for sparse linear system solvers on HPC infrastructures
Researchers funded by the Exascale Computing Project (ECP) have extended the sparse direct solver STRUMPACK to GPU frameworks, providing more flexibility and efficiency for execution of large-scale sparse linear solvers on high-performance computing infrastructures.
Alpine/ZFP Addresses Analysis, Visualization, And Data Reduction Needs For Exascale Science Applications
With the advent of the exascale supercomputing era, computational scientists can run simulations at higher resolutions, add more detailed physical phenomena, increase the size of the physical problems, and couple multiple codes spanning both physical and temporal scales.
Pagoda Updates PGAS Programming With Scalable Data Structures And Aggressively Asynchronous Communication
The Pagoda Project researches and develops software that programmers use to implement high-performance applications using the Partitioned Global Address Space (PGAS) model. The project is primarily funded by the Exascale Computing Project (ECP), and interacts with partner projects in industry, government, and academia.
By Rob Farber, contributing writer Performance, portability, and broad functionality are all key features of the AMReX software framework, which was developed by researchers at Lawrence Berkeley National Laboratory (Berkeley Lab), the National Renewable Energy Laboratory, and Argonne National Laboratory as part of the US Department of Energy’s (DOE’s) Exascale Computing Project (ECP) AMReX Co-Design […]