ExaStar developments transition astrophysics simulations to exascale
The ExaStar project is developing a software ecosystem for exascale architectures that will support world-leading models of the mechanisms and observ
The ExaStar project is developing a software ecosystem for exascale architectures that will support world-leading models of the mechanisms and observ
The Exascale Computing Project’s (ECP’s) Co-design Center for Particle Applications (CoPA) aims to prepare particle applications for exascale computin
A team of researchers has developed the Feature Tracking Kit (FTK), which uses simplicial spacetime meshing to simplify, scale, and deliver novel feat
A team collaborating across national laboratories, universities, and industry has developed a new approach to runtime programming that enables scalabl
Researchers at the National Energy Technology Laboratory (NETL) and Lawrence Berkeley National Laboratory (LBNL) have developed MFIX-Exa, a massively
For the ExaWind challenge problem, decomposing the linear systems for each overset mesh offers several advantages by (1) allowing the use of rigorousl
The analytical and computational methods developed in this work pave the way for future calculations in more complicated systems involving
ArborX will speed up exascale applications for computational cosmology, multiphysics data transfer, computational mechanics, wind farm simulations, an
A team of cancer researchers and computer scientists have applied machine learning (ML) ensemble techniques to reduce training time, mitigate task com
Scientists have demonstrated the value in two particle simulators of so-called rendezvous methods, which invoke a communication pattern useful when th
Researchers supported by the Exascale Computing Project (ECP) conducted the first comprehensive review of research examining the usefulness of mixed-p
This work extends the capabilities of exascale computing to fusion research and establishes the validity and scalability of the code-coupling approach
A research team funded in part by the Exascale Computing Project has produced tools for assimilating high-resolution urban terrain into weather models
Researchers have introduced ADEPT, a novel domain-independent parallelization strategy that optimizes the Smith-Waterman algorithm for DNA and protein
Exascale Computing Project (ECP)–funded researchers have demonstrated a massively parallel, scalable system for simulating physical behaviors of
A team of researchers funded by the Exascale Computing Project demonstrated the efficacy of combining DRAM and high-density, byte-addressable
Scientists funded by the Exascale Computing Project (ECP) have developed WarpX, a modern, performance-portable Particle-in-Cell code that describes
Researchers funded by the Exascale Computing Project have delivered a novel method that addresses overloaded communication processes that use MPI-IO
Scientists working on the VeloC-SZ project have optimized SZ, an error-bounded prediction-based lossy compression model. SZ reduces dataset size by one order of magnitude or more while meeting users’ speed
Researchers supported by the Exascale Computing Project have developed a Multiscale Modelling Framework (MMF) configuration of E3SM, which involves embedding a limited-area cloud resolving model into each column of the