Featured Publication Summaries

ArborX speeds up, scales up spatial search for cosmology and other sciences

ArborX will speed up exascale applications for computational cosmology, multiphysics data transfer, computational mechanics, wind farm simulations, and other research areas.

Novel method combining machine learning and data partitioning benefits cancer records data extraction

A team of cancer researchers and computer scientists have applied machine learning (ML) ensemble techniques to reduce training time, mitigate task complexity, and improve accuracy and classification performance for information extraction with cancer pathology reports.

Rendezvous methods reduce performance bottlenecks in particle and grid-based simulations

Scientists have demonstrated the value in two particle simulators of so-called rendezvous methods, which invoke a communication pattern useful when the processors sending and receiving information are unknown to each other.

Technical Highlights

ECP Leads the Way to Cross-Platform Tested and Verified Compilers for HPC and Exascale Architectures

The Exascale Computing Project (ECP) is working to combine two key technologies, LLVM and continuous integration (CI), to ensure that current and future compilers are stable and performant on high-performance computing (HPC) and exascale computer systems.

A Performance Portable Domain Specific Language for Stencils on HPC Systems

Stencils are a fundamental computational pattern in many parallel distributed HPC algorithms, notably grid-based and finite element methods.

RAJA Portability Suite Enables Performance Portable CPU and GPU HPC Codes

One software tool available now and showing tremendous promise for the exascale era is the open-source RAJA Portability Suite. RAJA is part of the Exascale Computing Project (ECP) NNSA software portfolio and is also supported by the ECP Programming Models and Runtimes area.

National Nuclear Security Administration logo U.S. Department of Energy Office of Science logo