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Kevin P. Micallef

dblp:56/2071 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2001
—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 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics › genetic data simulation
quantitative genetics simulation
0.012001
Using clusters of computers for large QU-GENE simulation experiments · Bioinform. 2001

Methods — techniques the papers use, named apart from their topics

simulation automation · 0.1distributed computing · 0.1
YearPublicationVenuePosition
2001 Using clusters of computers for large QU-GENE simulation experiments
abstract
Abstract Summary: The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup. Contact: [email protected] Supplementary information: http://pig.ag.uq.edu.au/qu-gene/cluster.htm * To whom correspondence should be addressed.
Kevin P. Micallef, Mark Cooper, Dean W. Podlich
Bioinform.1