Demo Data from EDBT 2026 / reviewers in the wild / expert
Andrzej Wozniak
dblp:235/4203
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1997
—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 · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
sequence analysis |
0.0 | 1 | 1997 | Using video-oriented instructions to speed up sequence comparison · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › sequence analysis
sequence comparison |
0.0 | 1 | 1997 | Using video-oriented instructions to speed up sequence comparison · Comput. Appl. Biosci. 1997 |
Bioinformatics and computational biology › sequence alignment › dynamic programming alignment
smith-waterman algorithm |
0.0 | 1 | 1997 | Using video-oriented instructions to speed up sequence comparison · Comput. Appl. Biosci. 1997 |
Parallel and multicore computing › data parallelism
SIMD vectorization |
0.0 | 1 | 1997 | Using video-oriented instructions to speed up sequence comparison · Comput. Appl. Biosci. 1997 |
Methods — techniques the papers use, named apart from their topics
instruction-level parallelization · 0.0SIMD instructions · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Using video-oriented instructions to speed up sequence comparisonabstractMOTIVATION: This document presents an implementation of the well-known Smith-Waterman algorithm for comparison of proteic and nucleic sequences, using specialized video instructions. These instructions, SIMD-like in their design, make possible parallelization of the algorithm at the instruction level. RESULTS: Benchmarks on an ULTRA SPARC running at 167 MHz show a speed-up factor of two compared to the same algorithm implemented with integer instructions on the same machine. Performance reaches over 18 million matrix cells per second on a single processor, giving to our knowledge the fastest implementation of the Smith-Waterman algorithm on a workstation. The accelerated procedure was introduced in LASSAP--a LArge Scale Sequence compArison Package software developed at INRIA--which handles parallelism at higher level. On a SUN Enterprise 6000 server with 12 processors, a speed of nearly 200 million matrix cells per second has been obtained. A sequence of length 300 amino acids is scanned against SWISSPROT R33 (1,8531,385 residues) in 29 s. This procedure is not restricted to databank scanning. It applies to all cases handled by LASSAP (intra- and inter-bank comparisons, Z-score computation, etc. Andrzej Wozniak |
Comput. Appl. Biosci. | 1 |