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EDBT 2026 Demo / reviewers in the wild / expert

David Pfander

dblp:194/7114 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 61% Electronic design automation · 30% Parallel and multicore computing · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing › scientific computing systems
adaptive mesh refinement		 0.412019
From piz daint to the stars: simulation of stellar mergers using high-level abstractions · SC 2019
Electronic design automation › technology computer-aided design
hydrodynamic simulation		 0.412019
From piz daint to the stars: simulation of stellar mergers using high-level abstractions · SC 2019
High-performance computing
scientific computing systems		 0.412019
From piz daint to the stars: simulation of stellar mergers using high-level abstractions · SC 2019
Parallel and multicore computing
parallel programming models		 0.112019
From piz daint to the stars: simulation of stellar mergers using high-level abstractions · SC 2019
YearPublicationVenuePosition
2019 From piz daint to the stars: simulation of stellar mergers using high-level abstractions
abstract
We study the simulation of stellar mergers, which requires complex simulations with high computational demands. We have developed Octo-Tiger, a finite volume grid-based hydrodynamics simulation code with Adaptive Mesh Refinement which is unique in conserving both linear and angular momentum to machine precision. To face the challenge of increasingly complex, diverse, and heterogeneous HPC systems, Octo-Tiger relies on high-level programming abstractions.
Gregor Daiß, Parsa Amini, John Biddiscombe, Patrick Diehl, Juhan Frank, Kevin A. Huck, Hartmut Kaiser, Dominic Marcello, David Pfander, Dirk Pflüger
 SC9