bibtex

BibTeX

@inproceedings{DAPFDCOPTB03,
	author	 = {Alexandros Stamatakis and Markus Lindermeier and Michael Ott and Thomas Ludwig and Harald Meier},
	title	 = {{DAxML: A Program for Distributed Computation of Phylogenetic Trees Based on Load Managed CORBA}},
	year	 = {2003},
	booktitle	 = {{Parallel Computing Technologies}},
	editor	 = {Victor Malyshkin},
	publisher	 = {Springer},
	address	 = {Berlin / Heidelberg, Germany},
	series	 = {Lecture Notes in Computer Science},
	number	 = {2763},
	pages	 = {538--548},
	conference	 = {PaCT-03},
	organization	 = {Nizhni Novgorod State University and Russian Academy of Sciences (Academgorodok, Novosibirsk)},
	location	 = {Nizhni Novgorod, Russia},
	doi	 = {http://dx.doi.org/10.1007/978-3-540-45145-7_51},
	abstract	 = {High performance computing in bioinformatics has led to important progress in the field of genome analysis. Due to the huge amount of data and the complexity of the underlying algorithms many problems can only be solved by using supercomputers. In this paper we present DAxML, a program for the distributed computation of evolutionary trees. In contrast to prior approaches DAxML runs on a cluster of workstations instead of an expensive supercomputer. For this purpose we transformed PAxML, a fast parallel phylogeny program incorporating novel algorithmic optimizations, into a distributed application. DAxML  uses modern object-oriented middleware instead of message-passing communication in order to reduce the development and maintenance costs. Our goal is to provide DAxML to a broad range of users, in particular those who do not have supercomputers at their disposal. We ensure high performance and scalability by applying a high-level load management service called LMC (Load Managed CORBA). LMC  provides transparent system level load management by integrating the load management functionality directly into the ORB. In this paper we demonstrate the simplicity of integrating LMC into a real-world application and how it enhances the performance and scalability of DAxML},
	url	 = {http://www.springerlink.com/content/9gm483003eujhpe5/fulltext.pdf},
}

bibtex.txt · Last modified: 2018-01-24 17:13 (external edit)