Featured Publication Summaries

EXAALT researchers explore speculative task methods to improve scalability

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.

HPCToolkit enhancements target improved performance analysis for exascale era

A team funded by the Exascale Computing Project is preparing to release a new version of HPCToolkit, a suite of performance analysis tools that helps developers identify and diagnose performance bottlenecks on emerging exascale systems.

Technical Highlights

ExaBiome: Gordon Bell Finalist Research Infers the Functions of Related Proteins with Exascale-Capable Homology Search

The ExaBiome project has been selected as a 2022 Gordon Bell Finalist.

PETSC/TAO: HOW TO CREATE, MAINTAIN, AND MODERNIZE A NUMERICAL TOOLKIT THROUGHOUT DECADES OF SUPERCOMPUTER INNOVATIONS

The Portable, Extensible Toolkit for Scientific Computation (PETSc) reflects a long-term investment in software infrastructure for the scientific community.

High-Accuracy, Exascale-Capable, Ab Initio Electronic Structure Calculations with QMCPACK: A Use Case of Good Software Practices

The quantum Monte Carlo methods package (QMCPACK) is a unique simulation code that can produce ab initio electronic structure solutions for a broad range of materials with an accuracy unreachable by other methods and packages.

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