Multiscale modeling has a long history of use in structural biology, as computational
biologists strive to overcome the time-and length-scale limits of atomistic molecular …

Scientific workflows have become integral tools in broad scientific computing use cases.
Science discovery is increasingly dependent on workflows to orchestrate large and complex …

Python has become the de facto language for scientific computing. Programming in Python
is highly productive, mainly due to its rich science-oriented software ecosystem built around …

We address the increasing complexity of scientific workflows in the context of high-
performance computing (HPC) and their associated need for robust, adaptable, and flexible …

The advancement of machine learning techniques and the heterogeneous architectures of
most current supercomputers are propelling the demand for large multiscale simulations that …

We present Jobflow, a domain-agnostic Python package for writing computational workflows
tailored for high-throughput computing applications. With its simple decorator-based …

We explore the performance and portability of the high-level programming models: the
LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) …

Earth system models are developed with a tight coupling to target hardware, often
containing specialized code predicated on processor characteristics. This coupling stems …

The Julia programming language has evolved into a modern alternative to fill existing gaps
in scientific computing and data science applications. Julia leverages a unified and …

Porting a scientific data analysis workflow (DAW) to a cluster infrastructure, a new software
stack, or even only a new dataset with some notably different properties is often challenging …