Demo Data from EDBT 2026 / reviewers in the wild / expert
Liam Krauss
dblp:169/1730
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › scientific computing systems › computational fluid dynamics
blood flow simulation |
0.2 | 1 | 2015 | Massively parallel models of the human circulatory system · SC 2015 |
High-performance computing › scientific computing systems
computational fluid dynamics |
0.2 | 1 | 2015 | Massively parallel models of the human circulatory system · SC 2015 |
High-performance computing › scientific computing systems › computational fluid dynamics
lattice boltzmann method |
0.2 | 1 | 2015 | Massively parallel models of the human circulatory system · SC 2015 |
High-performance computing
scientific computing systems |
0.2 | 1 | 2015 | Massively parallel models of the human circulatory system · SC 2015 |
Methods — techniques the papers use, named apart from their topics
multiscale coupling · 0.4load balancing · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Massively parallel models of the human circulatory systemabstractThe potential impact of blood flow simulations on the diagnosis and treatment of patients suffering from vascular disease is tremendous. Empowering models of the full arterial tree can provide insight into diseases such as arterial hypertension and enables the study of the influence of local factors on global hemodynamics. We present a new, highly scalable implementation of the lattice Boltzmann method which addresses key challenges such as multiscale coupling, limited memory capacity and bandwidth, and robust load balancing in complex geometries. We demonstrate the strong scaling of a three-dimensional, high-resolution simulation of hemodynamics in the systemic arterial tree on 1,572,864 cores of Blue Gene/Q. Faster calculation of flow in full arterial networks enables unprecedented risk stratification on a perpatient basis. In pursuit of this goal, we have introduced computational advances that significantly reduce time-to-solution for biofluidic simulations. Amanda Randles, Erik W. Draeger, Tomas Oppelstrup, Liam Krauss, John A. Gunnels |
SC | 4 |