Demo Data from EDBT 2026 / reviewers in the wild / expert
Siegfried Hansen
dblp:52/4056
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1988
—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 |
Parallel and multicore computing · 81% Hardware accelerators and domain-specific architectures · 19% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel algorithms › parallel algorithm design
systolic algorithms |
0.0 | 1 | 1988 | Modified Faddeeva Algorithm for Concurrent Execution of Linear Algebraic Operations · IEEE Trans. Computers 1988 |
Parallel and multicore computing
parallel architecture |
0.0 | 1 | 1988 | Modified Faddeeva Algorithm for Concurrent Execution of Linear Algebraic Operations · IEEE Trans. Computers 1988 |
Hardware accelerators and domain-specific architectures
systolic array |
0.0 | 1 | 1988 | Modified Faddeeva Algorithm for Concurrent Execution of Linear Algebraic Operations · IEEE Trans. Computers 1988 |
Methods — techniques the papers use, named apart from their topics
givens rotations · 0.0faddeeva algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Modified Faddeeva Algorithm for Concurrent Execution of Linear Algebraic OperationsabstractAn algorithm is described that provides an architectural framework for systematic execution of a wide class of linear algebraic operations using a single systolic array and simple data flow. The algorithm has been modified to use numerically stable Given's rotations and is therefore suited to any matrix problem of full rank. When the problem size exceeds that of the hardware array, it can be partitioned in a straightforward, numerically stable way. Numerous simulations have verified the algorithm's correctness.> J. Greg Nash, Siegfried Hansen |
IEEE Trans. Computers | 2 |