Demo Data from EDBT 2026 / reviewers in the wild / expert
Philippe Théveny
dblp:62/9918
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—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% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization › numerical analysis
interval arithmetic |
0.2 | 1 | 2014 | Numerical Reproducibility and Parallel Computations: Issues for Interval Algorithms · IEEE Trans. Computers 2014 |
High-performance computing
parallel numerical algorithms |
0.1 | 1 | 2014 | Numerical Reproducibility and Parallel Computations: Issues for Interval Algorithms · IEEE Trans. Computers 2014 |
Methods — techniques the papers use, named apart from their topics
interval computation · 0.4floating-point analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Numerical Reproducibility and Parallel Computations: Issues for Interval AlgorithmsabstractWhat is callednumerical reproducibilityis the problem of getting the same result when the scientific computation is run several times, either on the same machine or on different machines, with different types and numbers of processing units, execution environments, computational loads, etc. This problem is especially stringent for HPC numerical simulations. In what follows, we identify the problems encountered when implementing interval routines in floating-point arithmetic. Some are well-known and common in numerical computations, some are specific to interval computations. We propose here a classification of floating-point issues by distinguishing their severity with respect to correctness and tightness of the computed interval result. In fact, interval computation can accommodate the lack of numerical reproducibility as long as it does not affect the inclusion property, which is the main property of interval arithmetic. Several ways to preserve the inclusion property are presented, on the example of the product of matrices with interval coefficients. Nathalie Revol, Philippe Théveny |
IEEE Trans. Computers | 2 |