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Emmet Caulfield

dblp:34/7970 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2010
0000-0001-8884-5232ORCID · reported

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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 77% Hardware accelerators and domain-specific architectures · 23%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering › numerical simulation
stochastic simulation algorithm		 0.112010
CellMC - a multiplatform model compiler for the Cell Broadband Engine and x86 · Bioinform. 2010
Parallel and multicore computing
parallel computing		 0.112010
CellMC - a multiplatform model compiler for the Cell Broadband Engine and x86 · Bioinform. 2010
Hardware accelerators and domain-specific architectures › many-core accelerator
cell broadband engine		 0.012010
CellMC - a multiplatform model compiler for the Cell Broadband Engine and x86 · Bioinform. 2010

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

vectorization · 0.2SBML model compilation · 0.2
YearPublicationVenuePosition
2010 CellMC - a multiplatform model compiler for the Cell Broadband Engine and x86
abstract
MOTIVATION: Gillespie's stochastic simulation algorithm (SSA) is often the most tractable method to study stochastic models of biochemical systems. The algorithm itself is very simple and a natural target for implementation on specialized architectures such as the Cell Broadband Engine (Cell/BE). We have developed CellMC, a multiplatform SBML model compiler implementing a vectorized version of SSA for use on Cell/BE or x86 PCs. AVAILABILITY: The code is freely available from http://www.cellmc.org. It will run on a wide variety of x86 computers running Linux/MacOSX (Darwin) and on Cell/BE computers such as the Sony PlayStation3 (PS3) and the IBM BladeCenter QS22. CellMC requires gcc, libxml2 and libxslt, all of which are installed by default on most of the supported platforms. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Emmet Caulfield, Andreas Hellander
 Bioinform.1