Demo Data from VLDB 2026 / reviewers in the wild / expert
Milo R. Dorr
dblp:200/5509
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—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 · 67% Parallel and multicore computing · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › scientific computing systems
molecular dynamics simulation |
0.1 | 1 | 2009 | Beyond homogeneous decomposition: scaling long-range forces on Massively Parallel Systems · SC 2009 |
Parallel and multicore computing › parallelization strategies
parallel decomposition |
0.1 | 1 | 2009 | Beyond homogeneous decomposition: scaling long-range forces on Massively Parallel Systems · SC 2009 |
High-performance computing
scientific computing systems |
0.1 | 1 | 2009 | Beyond homogeneous decomposition: scaling long-range forces on Massively Parallel Systems · SC 2009 |
Computational science and engineering › computational physics
plasma physics simulation |
0.0 | 1 | 2009 | Beyond homogeneous decomposition: scaling long-range forces on Massively Parallel Systems · SC 2009 |
Methods — techniques the papers use, named apart from their topics
long-range force computation · 0.2heterogeneous decomposition · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Beyond homogeneous decomposition: scaling long-range forces on Massively Parallel SystemsabstractWith supercomputers anticipated to expand from thousands to millions of cores, one of the challenges facing scientists is how to effectively utilize this ever-increasing number. We report here an approach that creates a heterogeneous decomposition by partitioning effort according to the scaling properties of the component algorithms. We demonstrate our strategy by developing a capability to model hot dense plasma. We have performed benchmark calculations ranging from millions to billions of charged particles, including a 2.8 billion particle simulation that achieved 259.9 TFlop/s (26% of peak performance) on the 294,912 cpu JUGENE computer at the Jülich Supercomputing Centre in Germany. With this unprecedented simulation capability we have begun an investigation of plasma fusion physics under conditions where both theory and experiment are lacking--in the strongly-coupled regime as the plasma begins to burn. David F. Richards, James N. Glosli, Bor Chan, Milo R. Dorr, Erik W. Draeger, Jean-Luc Fattebert, William D. Krauss, Thomas E. Spelce, Frederick H. Streitz, Michael P. Surh, John A. Gunnels |
SC | 4 |