Demo Data from VLDB 2026 / reviewers in the wild / expert
Philip Sternberg
dblp:07/3082
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 · 77% Parallel and multicore computing · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing
scientific computing |
0.1 | 1 | 2008 | Accelerating configuration interaction calculations for nuclear structure · SC 2008 |
Parallel and multicore computing › parallel algorithms
massively parallel algorithms |
0.0 | 1 | 2008 | Accelerating configuration interaction calculations for nuclear structure · SC 2008 |
Methods — techniques the papers use, named apart from their topics
sparse matrix algorithms · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Accelerating configuration interaction calculations for nuclear structureabstractOne of the emerging computational approaches in nuclear physics is the configuration interaction (CI) method for solving the many-body nuclear Hamiltonian in a sufficiently large single-particle basis space to obtain exact answers - either directly or by extrapolation. The lowest eigenvalues and corresponding eigenvectors for very large, sparse and unstructured nuclear Hamiltonian matrices are obtained and used to evaluate additional experimental quantities. These matrices pose a significant challenge to the design and implementation of efficient and scalable algorithms for obtaining solutions on massively parallel computer systems. In this paper, we describe the computational strategies employed in a state-of-the-art CI code MFDn (Many Fermion Dynamics - nuclear) as well as techniques we recently developed to enhance the computational efficiency of MFDn. We will demonstrate the current capability of MFDn and report the latest performance improvement we have achieved. We will also outline our future research directions. Philip Sternberg, Esmond G. Ng, Chao Yang 0001, Pieter Maris, James P. Vary, Masha Sosonkina, Hung Viet Le |
SC | 1 |