Zobrazeno 1 - 10
of 124
pro vyhledávání: '"van Nieuwpoort, Rob"'
In Function-as-a-Service (FaaS) serverless, large applications are split into short-lived stateless functions. Deploying functions is mutually profitable: users need not be concerned with resource management, while providers can keep their servers at
Externí odkaz:
http://arxiv.org/abs/2411.08448
Autor:
Deekshitha, Farshidi, Siamak, Maassen, Jason, Bakhshi, Rena, van Nieuwpoort, Rob, Jansen, Slinger
The growing usage of research software in the research community has highlighted the need to recognize and acknowledge the contributions made not only by researchers but also by Research Software Engineers. However, the existing methods for crediting
Externí odkaz:
http://arxiv.org/abs/2406.02412
Autor:
Deekshitha, Bakhshi, Rena, Maassen, Jason, Ortiz, Carlos Martinez, van Nieuwpoort, Rob, Jansen, Slinger
The organizations and researchers producing research software face a common problem of making their software sustainable beyond funding provided by a single research project. This is addressed by research software engineers through building communiti
Externí odkaz:
http://arxiv.org/abs/2406.01788
Autor:
Mesarcik, Michael, Boonstra, Albert-Jan, Iacobelli, Marco, Ranguelova, Elena, de Laat, Cees, van Nieuwpoort, Rob
Publikováno v:
A&A 680, A74 (2023)
As radio telescopes increase in sensitivity and flexibility, so do their complexity and data-rates. For this reason automated system health management approaches are becoming increasingly critical to ensure nominal telescope operations. We propose a
Externí odkaz:
http://arxiv.org/abs/2307.01054
Radio Frequency Interference (RFI) corrupts astronomical measurements, thus affecting the performance of radio telescopes. To address this problem, supervised segmentation models have been proposed as candidate solutions to RFI detection. However, th
Externí odkaz:
http://arxiv.org/abs/2207.00351
Autor:
Willemsen, Floris-Jan, Schoonhoven, Richard, Filipovič, Jiří, Tørring, Jacob O., van Nieuwpoort, Rob, van Werkhoven, Ben
Publikováno v:
In Future Generation Computer Systems October 2024 159:489-504
The GPU programming model is primarily aimed at the development of applications that run one GPU. However, this limits the scalability of GPU code to the capabilities of a single GPU in terms of compute power and memory capacity. To scale GPU applica
Externí odkaz:
http://arxiv.org/abs/2202.05549
Finding optimal parameter configurations for tunable GPU kernels is a non-trivial exercise for large search spaces, even when automated. This poses an optimization task on a non-convex search space, using an expensive to evaluate function with unknow
Externí odkaz:
http://arxiv.org/abs/2111.14991
We show that using nearest neighbours in the latent space of autoencoders (AE) significantly improves performance of semi-supervised novelty detection in both single and multi-class contexts. Autoencoding methods detect novelty by learning to differe
Externí odkaz:
http://arxiv.org/abs/2111.06150
Autor:
Heldens, Stijn, Hijma, Pieter, van Werkhoven, Ben, Maassen, Jason, Bal, Henri, van Nieuwpoort, Rob
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 reuse must be exploited to achieve good performance. Several researchers
Externí odkaz:
http://arxiv.org/abs/2009.04755