activity
20162025
most citedParsl: Pervasive Parallel Programming in Python

259 citations · 1.2k across the 51 of their papers we have counts for

collaborators
Showing 2023 · cs.DCShow all

6 papers · 2 filters

cs.DC2023

Optimizing Scientific Data Transfer on Globus with Error-bounded Lossy Compression

Yuanjian Liu, Sheng Di, Kyle Chard +2

The increasing volume and velocity of science data necessitate the frequent movement of enormous data volumes as part of routine research activities. As a result, limited wide-area…

cs.DC2023★ 13 cited

PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs

Mihael Hategan-Marandiuc, Andre Merzky, Nicholson Collier +10

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective…

cs.DC2023

Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis

Nicholson Collier, Justin M. Wozniak, Abby Stevens +6

COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among domain expert…

cs.DC2023★ 1 cited

Accelerating Communications in Federated Applications with Transparent Object Proxies

J. Gregory Pauloski, Valerie Hayot-Sasson, Logan Ward +5

Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute -- such as when fast networks make it cost-effective to compute on remot…

cs.DC2023

Workflows Community Summit 2022: A Roadmap Revolution

Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala +102

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

cs.DC2023★ 11 cited

Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources

Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson +7

Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supe…