Demo Data from EDBT 2026 / reviewers in the wild / expert
David R. Mathog
dblp:99/6192
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 50% High-performance computing · 50% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence alignment › heuristic alignment
BLAST |
0.0 | 1 | 2003 | Parallel BLAST on split databases · Bioinform. 2003 |
Bioinformatics and computational biology
sequence alignment |
0.0 | 1 | 2003 | Parallel BLAST on split databases · Bioinform. 2003 |
High-performance computing
cluster computing |
0.0 | 1 | 2003 | Parallel BLAST on split databases · Bioinform. 2003 |
Parallel and multicore computing
parallel computing |
0.0 | 1 | 2003 | Parallel BLAST on split databases · Bioinform. 2003 |
Methods — techniques the papers use, named apart from their topics
parallel execution · 0.1database splitting · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Parallel BLAST on split databasesabstractSUMMARY: BLAST programs often run on large SMP machines where multiple threads can work simultaneously and there is enough memory to cache the databases between program runs. A group of programs is described which allows comparable performance to be achieved with a Beowulf configuration in which no node has enough memory to cache a database but the cluster as an aggregate does. To achieve this result, databases are split into equal sized pieces and stored locally on each node. Each query is run on all nodes in parallel and the resultant BLAST output files from all nodes merged to yield the final output. AVAILABILITY: Source code is available from ftp://saf.bio.caltech.edu/ David R. Mathog |
Bioinform. | 1 |