Abstract

The increasing capability of high-performance computing (HPC), cloud computing, and edge computing systems directly translates into the ability to generate more data and execute more extended analyses, thus expanding the range of natural phenomena that scientists can study using dataflows in scientific domains such as chemistry, materials sciences, molecular biology, and drug design. At the same time, the steady growth in the complexity of these dataflows also results in new challenges in the effective composition of single data tasks into scalable dataflow pipelines. This project addresses these critical challenges by developing solutions to optimize dataflow pipelines across heterogeneous resources. This project builds a broader community of HPC experts, who will have a far-reaching impact on the efficient development of dataflow pipelines supporting scientific applications. The team of researchers …

Date

2023

Authors

Ewa Deelman

Journal

NSF Award Number 2331153. Directorate for Computer and Information Science and Engineering

Volume

23

Issue

2331153

Pages

31153