activity
20202026
most citedSoftware-Defined Network for End-to-end Networked Science at the Exascale

25 citations · 55 across the 12 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

physics.comp-ph2022

Snowmass 2021 Computational Frontier CompF4 Topical Group Report: Storage and Processing Resource Access

W. Bhimji, D. Carder, E. Dart +17

Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the comp…

cs.NI2022★ 5 cited

Managed Network Services for Exascale Data Movement Across Large Global Scientific Collaborations

Frank Würthwein, Jonathan Guiang, Aashay Arora +10

Unique scientific instruments designed and operated by large global collaborations are expected to produce Exabyte-scale data volumes per year by 2030. These collaborations depend…

cs.DC2022★ 2 cited

Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches

Julian Bellavita, Alex Sim, Kesheng Wu +4

The XRootD system is used to transfer, store, and cache large datasets from high-energy physics (HEP). In this study we focus on its capability as distributed on-demand storage cac…

cs.NI2022★ 4 cited

Access Trends of In-network Cache for Scientific Data

Ruize Han, Alex Sim, Kesheng Wu +6

Scientific collaborations are increasingly relying on large volumes of data for their work and many of them employ tiered systems to replicate the data to their worldwide user comm…

cs.NI2022★ 2 cited

Data Transfer and Network Services management for Domain Science Workflows

Tom Lehman, Xi Yang, Chin Guok +10

This paper describes a vision and work in progress to elevate network resources and data transfer management to the same level as compute and storage in the context of services acc…

cs.NI2022

Deploying in-network caches in support of distributed scientific data sharing

Alex Sim, Ezra Kissel, Chin Guok

The importance of intelligent data placement, management, and analysis has become apparent as scientific data volumes across the network continue to increase. To that end, we descr…