Search results for "High Performance Computing"
showing 9 items of 9 documents
GekkoFS - A Temporary Distributed File System for HPC Applications
2018
We present GekkoFS, a temporary, highly-scalable burst buffer file system which has been specifically optimized for new access patterns of data-intensive High-Performance Computing (HPC) applications. The file system provides relaxed POSIX semantics, only offering features which are actually required by most (not all) applications. It is able to provide scalable I/O performance and reaches millions of metadata operations already for a small number of nodes, significantly outperforming the capabilities of general-purpose parallel file systems. The work has been funded by the German Research Foundation (DFG) through the ADA-FS project as part of the Priority Programme 1648. It is also support…
Fourth Workshop on using Emerging Parallel Architectures
2012
AbstractThe Fourth Workshop on Using Emerging Parallel Architectures (WEPA), held in conjunction with ICCS 2012, provides a forum for exploring the capabilities of emerging parallel architectures such as GPUs, FPGAs, Cell B.E., Intel M.I.C. and multicores to accelerate computational science applications.
Parallel and scalable short-read alignment on multi-core clusters using UPC++
2016
[Abstract]: The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown to obtain high quality mappings at the expense of long execution times. Finding fast yet accurate software solutions is of high importance to research, since availability and size of NGS datasets continue to increase. In this work we present an efficient parallelization approach for NGS short-read alignment on multi-core clusters. Our approach takes advantage of a distributed shared memory programming model based on the new UPC++ language. Experimental results using the …
Implementation techniques for the lattice Boltzmann method
2010
Alignment-free Genomic Analysis via a Big Data Spark Platform
2021
Abstract Motivation Alignment-free distance and similarity functions (AF functions, for short) are a well-established alternative to pairwise and multiple sequence alignments for many genomic, metagenomic and epigenomic tasks. Due to data-intensive applications, the computation of AF functions is a Big Data problem, with the recent literature indicating that the development of fast and scalable algorithms computing AF functions is a high-priority task. Somewhat surprisingly, despite the increasing popularity of Big Data technologies in computational biology, the development of a Big Data platform for those tasks has not been pursued, possibly due to its complexity. Results We fill this impo…
High Performance Computing on the COMETA Grid Infrastructure
2008
We present the High Performance Computing (HPC) projects jointly developed at the INAF - Osservatorio Astronomico di Palermo and at the DSFA - Universita` di Palermo which benefits of the Grid infrastructure of COMETA. We have contributed to setup the infrastructure in order to run HPC applications on the Grid. We report on our experience regarding to porting HPC applications to the Grid and to the first HPC simulations performed. The most demanding simulations describe the interaction of a magnetized supernova shock wave with an interstellar gas cloud. We discuss the resources required for the simulations, the performance and the scalability of our code on the Grid, and present first resul…
Programming languages for data-Intensive HPC applications: A systematic mapping study
2020
This work is a result of activities from COST Action 10406 High -Performance Modelling and Simulation for Big Data Applications (cHiPSet), funded by the European Cooperation in Science and Technology. FCT, Portugal for grants: NOVA LINCS Research Laboratory Ref. UID/ CEC/ 04516/ 2019); INESC-ID Ref. UID/CEC/50021/2019; BioISI Ref. UID/MULTI/04046/2103; LASIGE Research Unit Ref. UID/CEC/00408/ 2019. A major challenge in modelling and simulation is the need to combine expertise in both software technologies and a given scientific domain. When High-Performance Computing (HPC) is required to solve a scientific problem, software development becomes a problematic issue. Considering the complexity…
GekkoFS — A Temporary Burst Buffer File System for HPC Applications
2020
Many scientific fields increasingly use high-performance computing (HPC) to process and analyze massive amounts of experimental data while storage systems in today’s HPC environments have to cope with new access patterns. These patterns include many metadata operations, small I/O requests, or randomized file I/O, while general-purpose parallel file systems have been optimized for sequential shared access to large files. Burst buffer file systems create a separate file system that applications can use to store temporary data. They aggregate node-local storage available within the compute nodes or use dedicated SSD clusters and offer a peak bandwidth higher than that of the backend parallel f…
A new parallel pipeline for DNA methylation analysis of long reads datasets
2017
Background DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. Results In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while…