most citedGPU acceleration of the SAGECal calibration package for the SKA

7 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2020

SAGECal performance with large sky models

H. Spreeuw, S. Yatawatta, B. van Werkhoven +1

As astronomical instruments become more sensitive, the requirements for the calibration software become more stringent; without accurate calibration solutions, thermal noise levels…

cs.SE2020

ESiWACE2 Services: RSE collaborations in Weather and Climate

Gijs van den Oord, Victor Azizi, Alessio Sclocco +5

We present the collaborative model of ESiWACE2 Services, where Research Software Engineers (RSEs) from the Netherlands eScience Center (NLeSC) and Atos offer their expertise to cli…

cs.DC2020

Rocket: Efficient and Scalable All-Pairs Computations on Heterogeneous Platforms

Stijn Heldens, Pieter Hijma, Ben van Werkhoven +3

All-pairs compute problems apply a user-defined function to each combination of two items of a given data set. Although these problems present an abundance of parallelism, data reu…

cs.SE2020

Lessons learned in a decade of research software engineering GPU applications

Ben van Werkhoven, Willem Jan Palenstijn, Alessio Sclocco

After years of using Graphics Processing Units (GPUs) to accelerate scientific applications in fields as varied as tomography, computer vision, climate modeling, digital forensics,…

astro-ph.IM20197 cited

GPU acceleration of the SAGECal calibration package for the SKA

Hanno Spreeuw, Ben van Werkhoven, Sarod Yatawatta +1

SAGECal has been designed to find the most accurate calibration solutions for low radio frequency imaging observations, with minimum artefacts due to incomplete sky models. SAGECAL…