25 papers · ranked by Valyu relevance
Alex M. Ascension, Marcos J. Araúzo-Bravo
Big Data analysis is a discipline with a growing number of areas where huge amounts of data is extracted and analyzed. Parallelization in Python integrates Message Passing Interface via mpi4py module. Since mpi4py does not support parallelization of objects greater than 2^31^ bytes, we developed BigMPI4py, a Python…
Chansup Byun, William Arcand, David Bestor, Bill Bergeron + 17 more
'Vijay Gadepally' 'Michael E. Houle' 'Matthew Hubbell' 'Hayden Jananthan' 'Michael Jones' 'Kurt Keville' 'Anna Klein' 'Peter Michaleas' 'Lauren Milechin' 'Guillermo Morales' 'Julie Mullen' 'Andrew Prout' 'Albert Reuther' 'Antonio De Rosa' 'Siddharth Samsi' 'Charles Yee' 'Jeremy Kepner'] Abstract—pPython seeks to…
Pau Andrio, Adam Hospital, Cristian Ramon-Cortes, Javier Conejero + 4 more
The usage of workflows has led to progress in many fields of science, where the need to process large amounts of data is coupled with difficulty in accessing and efficiently using High Performance Computing platforms. On the one hand, scientists are focused on their problem and concerned with how to process their data.…
Navtej Singh, Lisa-Marie Browne, R. P. Butler
High performance computing has been used in various fields of astrophysical research. But most of it is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters. With the advent of multicore processors in the last decade, many serial software codes have been re-implemented in…
Chansup Byun, William Arcand, David Bestor, Bill Bergeron + 16 more
'Vijay Gadepally' 'Michael E. Houle' 'Matthew Hubbell' 'Hayden Jananthan' 'Michael Jones' 'Anna Klein' 'Peter Michaleas' 'Lauren Milechin' 'Guillermo Morales' 'Julie Mullen' 'Andrew Prout' 'Albert Reuther' 'Antonio Rosa' 'Siddharth Samsi' 'Charles Yee' 'Jeremy Kepner'] Abstract—pPython seeks to provide a parallel…
Alexandra Yang
| 1 | Introduction | | 2 | | --- | --- | --- | --- | | 2 | Related Research | | 2 | | 3 | Installation | | 3 | | 4 | Benchmarking | | 3 | | 5 | Single Processor Sorting Algorithms | | 3 | | | 5.1 Sequential Merge Sort | | 3 | | | 5.2 | Python Built-in Sort | 4 | | | 5.3 Multiprocessing Merge Sort | | 4 | | | 5.3.1 |…
Stephen D. Hudson, Jeffrey Larson, John-Luke Navarro, Stefan M. Wild
libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator– allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a…
Vladislav Skorpil, Vaclav Oujezsky, Arcangelo Castiglione, Gianni D’Angelo
'Gianni D’Angelo'] This paper presents an implementation of the parallelization of genetic algorithms. Three models of parallelized genetic algorithms are presented, namely the Master-Slave genetic algorithm, the Coarse-Grained genetic algorithm, and the Fine-Grained genetic algorithm. Furthermore, these models are…
Benjamin James Gaska, Neha Jothi, Mahdi Soltan Mohammadi, Kathryn Volk + 1 more
'Kathryn Volk' 'Michelle Mills Strout'] Abstract—Nested parallelism exists in scientific codes that are searching multi-dimensional spaces. However, implementations of nested parallelism often have overhead and load balance issues. The Orbital Analysis code we present exhibits a sparse search space, significant load…
Authors not listed
With the ever-increasing demand for atomistic structures representative of real-life systems as well as the ad-vent of exascale computers, it has now become necessary and possible to use advanced global optimization (GO) techniques to intelligently sample the potential energy surface (PES). Given the previous studies…
Fabian Woller, Lis Arend, Christian Fuchsberger, Markus List + 1 more
To demonstrate the practical applicability of NApy on a real-world dataset, all statistical tests were performed on the CHRIS study data both without any parallelization (single thread) and with heavy parallelization (64 threads). For correlations, pandas was used as comparison as it was the fastest compared to other…
Sebastian Brickel, Andrey O. Demkiv, Rory M. Crean, Gaspar P. Pinto + 1 more
The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for…
Ling-Hong Hung, Wes Lloyd, Radhika Agumbe Sridhar, Saranya Devi Athmalingam Ravishankar + 3 more
For many next-generation sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner (BWA) is optimized for speed and and is often executed in parallel on the cloud. However, there are other less…
Bahman Arasteh, Seyed Salar Sefati, Huseyin Kusetogullari, Farzad Kiani + 3 more
Efficient task scheduling remains a key challenge in High-Performance Computing and Internet of Things (IoT) systems, where the sequential execution of nested loops often limits parallelism. This paper proposes a hybrid approach that dynamically parallelizes nested loops in heterogeneous IoT environments. The suggested…
Authors not listed
This paper presents GLAS (Git-based Lab Automated Scheduler or Get Lab Automation Simplified), an open-source, robust, and highly expandable Git-based architecture designed for laboratory automation. GLAS can be deployed in both partially and fully automated experimental science laboratories, enabling the development…
Julia L Turner, Scott T Kelley, James S Otto, Faramarz Valafar + 1 more
'Andrew J Bohonak'] Background The Isolation by Distance Web Service (IBDWS) is a user-friendly web interface for analyzing patterns of isolation by distance in population genetic data. IBDWS enables researchers to perform a variety of statistical tests such as Mantel tests and reduced major axis regression (RMA), and…
SPT Krishnan, Sim Sze Liang, Bharadwaj Veeravalli
Background RNA structure prediction problem is a computationally complex task, especially with pseudo-knots. The problem is well-studied in existing literature and predominantly uses highly coupled Dynamic Programming (DP) solutions. The problem scale and complexity become embarrassingly humungous to handle as sequence…
Marco D. Visser, Sean M. McMahon, Cory Merow, Philip M. Dixon + 3 more
Parallel computing divides calculations into smaller problems and solves these simultaneously, using multiple computing elements (hereafter “workers”). In the biological sciences, many computationally intensive problems are “embarrassingly parallel” , where almost all calculations can be completed in parallel. Common…
Sikao Guo, Nenad Korolija, Kent Milfeld, Adip Jhaveri + 3 more
Particle-based reaction-diffusion models offer a high-resolution alternative to the continuum reaction-diffusion approach, capturing the discrete and volume-excluding nature of molecules undergoing stochastic dynamics. These methods are thus uniquely capable of simulating explicit self-assembly of particles into…
Alejandro Santana-Bonilla, Raquel Lopez-Rios De Castro, Peike Sun, Robert Ziolek + 1 more
Machine learning methods offer the opportunity to design new functional materials on an unprecedented scale however building the large, diverse databases of molecules on which to train such methods remains a daunting task. Automated computational chemistry modelling workflows are therefore becoming essential tools in…
J Kyle Medley, Shaik Asifullah, Joseph Hellerstein, Herbert M Sauro
Mechanistic kinetic models of biological pathways are an important tool for understanding biological systems. Constructing kinetic models requires fitting the parameters to experimental data. However, parameter fitting on these models is a non–convex, non–linear optimization problem. Many algorithms have been proposed…
Pierre Carrier, Bill Long, Richard Walsh, Jef Dawson + 4 more
High Performance Computing (HPC) Best Practice offers opportunities to implement lessons learned in areas such as computational chemistry and physics in genomics workflows, specifically Next-Generation Sequencing (NGS) workflows. In this study we will briefly describe how distributed-memory parallelism can be an…
Authors not listed
Molecular Dynamics (MD) simulations are essential for studying the time evolution of molecular systems. Still, their efficiency is often bottlenecked by file-based Inter-Process Communication (IPC) between MD and Electronic Structure (ES) programs. We present a socket-based IPC implementation that dramatically…
Francois Besnier, Kevin A. Glover, Maria Anisimova
This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to…
Viacheslav Bolnykh, Jógvan Magnus Haugaard Olsen, Simone Meloni, Martin P. Bircher + 3 more
We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computation of electrostatic QM/MM interactions is parallelized exploiting…