Search Results for "multicore"

...This tool will let the users to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset (e.g., assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters. There also exists a MapReduce counterpart of ParDRe, called MarDRe (see the link above). UPDATE: From version 2.0.5 ParDRe also provides support to remove only optical duplicates (and leave biologically interesting duplicates) as well as to work with compressed input/output with .gz format.

MPI-dot2dot is a parallel tool to accelerate the identification of Tandem Repeats on multisequence datasetes. This tool receives as input a multisequence file with FASTQ or FASTA formats. It uses MPI processes and OpenMP threads to exploit the compute capabilities of multicore clusters.

...Also, sequences in GenBank format can be downloaded directly from NCBI using the NCBI access ID. Requirements JAVA Runtime 8. It's highly recommended to have a multicore processor to process large sequences. * Currently, this version only runs in Windows x64.

...This tool allows bioinformatics to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset. MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing.

...It officially supports four technologies (Illumina, 454, ion Torrent and PacBio - experimental) and it also has a generic setup for others (old and/or new). It is released under LGPL version 3.0. MuffinEC can use multicore systems, thanks to its OpenMP implementation. We are developing the 2nd version of MuffinEC. The beta version is already available online. The changes are listed in the VERSION_HISTORY file. Please report any problem you may encounter at the email address specified in the README file. We really appreciate your help.

...This tool will let the users to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset (e.g., assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters.

codonPhyML uses Markovian codon models of evolution in phylogeny reconstruction. Given a set of species characterized by their DNA sequences as input, codonPhyML will return the phylogenetic tree that best describes their evolutionary relationship. Our paper describing codonPhyML has been published in the journal "Molecular Biology and Evolution" (MBE). For more details, follow the link: http://mbe.oxfordjournals.org/content/30/6/1270. codonPhyML is on the cover of MBE! Check this out...

A Scalable Multicore Code for RNA Secondary Structure Prediction