Results 281 to 290 of about 36,225 (338)

Scaling DEPP phylogenetic placement to ultra-large reference trees: a tree-aware ensemble approach. [PDF]

Bioinformatics
Jiang Y, McDonald D, Perry D, Knight R, Mirarab S.   +4 more
europepmc   +1 more source

Algorithms to reconstruct past indels: The deletion-only parsimony problem. [PDF]

PLoS Comput Biol
Moutet J, Rivals E, Pardi F.
europepmc   +1 more source

The divide-and-conquer sequential Monte Carlo algorithm: Theoretical properties and limit theorems

Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen   +2 more
openalex   +1 more source

The packing problem : A divide and conquer algorithm on cellular automata

, 2012
Nicolas Bacquey
openalex   +1 more source

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Divide and conquer algorithm for nondiffracting beams

Journal of the Optical Society of America A, 2019
We put forward a robust technique to encode a plethora of arbitrary images as nondiffracting beams by optimizing their respective phase components. This technique works directly under the constraint of a ring of infinitesimal width in Fourier space. The procedure reported is based on a stochastic direct search and global optimization: the differential ...
Alberto F. Martínez-Herrera, Armando Céspedes-Mota, Servando Lopez-Aguayo   +2 more
openaire   +2 more sources

Architecture-cognizant divide and conquer algorithms

Proceedings of the 1999 ACM/IEEE conference on Supercomputing, 1999
Divide and conquer programs can achieve good performance on parallel computers and computers with deep memory hierarchies. We introduce architecture-cognizant divide and conquer algorithms, and explore how they can achieve even better performance. An architecture-cognizant algorithm has functionally-equivalent variants of the divide and/or combine ...
Kang Su Gatlin, Larry Carter
openaire   +1 more source

Divide-and-Conquer Algorithm for Clustalw-MPI

2006 Canadian Conference on Electrical and Computer Engineering, 2006
Multiple sequence alignment continues to be an active field of research in Computational Biology and the most widely used tool for multiple sequence alignment is ClustalW, which achieves alignment via three steps: pair wise alignment, guide tree generation and progressive alignment. ClustalW-MPI is a parallel implementation of ClustalW.
Siamak Rezaei, Md. Monwar
openaire   +1 more source

Automatic parallelization of divide and conquer algorithms

ACM SIGPLAN Notices, 1999
Divide and conquer algorithms are a good match for modern parallel machines: they tend to have large amounts of inherent parallelism and they work well with caches and deep memory hierarchies. But these algorithms pose challenging problems for parallelizing compilers.
Radu Rugina, Martin Rinard
openaire   +1 more source