A framework for genomic sequencing on clusters of multicore and manycore processors. (May 2018)

• Record Type: Journal Article
• Authors: Martínez, Héctor; Barrachina, Sergio; Castillo, Maribel; Tárraga, Joaquín; Medina, Ignacio; Dopazo, Joaquín; Quintana-Ortí, Enrique S
• Other Names: Vega-Rodríguez Miguel A guest-editor.; Rubio-Largo Álvaro guest-editor.
• Is Part Of: International journal of high performance computing applications. Volume 32:Number 3(2018)
• Page Start: 393
• Page End: 406
• Publication Date: 2018-05
• Subjects: Genomic sequencing -- DNA-seq -- RNA-seq -- high performance computing -- clusters -- multi-threaded architectures; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342016653243
• Languages: English
• ISSNs: 1094-3420

Abstract

The advances in genomic sequencing during the past few years have motivated the development of fast and reliable software for DNA/RNA sequencing on current high performance architectures. Most of these efforts target multicore processors, only a few can also exploit graphics processing units, and a much smaller set will run in clusters equipped with any of these multi-threaded architecture technologies. Furthermore, the examples that can be used on clusters today are all strongly coupled with a particular aligner. In this paper we introduce an alignment framework that can be leveraged to coordinately run any "single-node" aligner, taking advantage of the resources of a cluster without having to modify any portion of the original software. The key to our transparent migration lies in hiding the complexity associated with the multi-node execution (such as coordinating the processes running in the cluster nodes) inside the generic-aligner framework. Moreover, following the design and operation in our Message Passing Interface (MPI) version of HPG Aligner RNA BWT, we organize the framework into two stages in order to be able to execute different aligners in each one of them. With this configuration, for example, the first stage can ideally apply a fast aligner to accelerate the process, while the second one can be tuned to act as a refinement stage that further improves the global alignment process with little cost.