27 papers · ranked by Valyu relevance
Softya Sebastian, Swarup Roy
Genome-scale network inference is essential to understand comprehensive interaction patterns. Current methods are limited to the reconstruction of small to moderate-size networks. The most obvious alternative is to propose a novel method or alter existing methods that may leverage parallel computing paradigms. Very few…
Yadu Babuji, Anna Woodard, Zhuozhao Li, Daniel S. Katz + 8 more
'Ben Clifford' 'Rohan Kumar' 'Łukasz Łaciński' 'Ryan Chard' 'Justin M. Wozniak' 'Ian Foster' 'Michael Wilde' 'Kyle Chard'] High-level programming languages such as Python are increasingly used to provide intuitive interfaces to libraries written in lower-level languages and for assembling applications from various…
Jon Hill, Matthew Hambley, Thorsten Forster, Muriel Mewissen + 4 more
'Terence M Sloan' 'Florian Scharinger' 'Arthur Trew' 'Peter Ghazal'] Background Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of the resulting data tests the limits of existing bioinformatics computing…
Yann Garniron, Thomas Applencourt, Kevin Gasperich, Anouar Benali + 15 more
Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multi-reference second-order perturbation theory (PT2). The determinant-driven…
Jose L Figueroa, Richard Allen White
We now exist in the era of massive datasets from genomics, large language models, and all the known knowledge of humanity right at our fingertips. Much of this data is becoming more accessible; however, processing such data remains an ongoing issue across systems including high performance computing (HPC)…
Cristian Ramon-Cortes, Ramon Amela, Jorge Ejarque, Philippe Clauss + 1 more
'Rosa Badia'] Abstract—The last improvements in programming languages, programming models, and frameworks have focused on abstracting the users from many programming issues. Among others, recent programming frameworks include simpler syntax, automatic memory management and garbage collection, which simplifies code…
Rafael Terra, Diego Carvalho, Denis Jacob Machado, Carla Osthoff + 1 more
Advances in High-Performance Computing (HPC) have enabled increasingly complex genomic analyses, including those in phylogenomics. These analyses contribute to understanding the evolution of viruses and pathogens, improving our knowledge of disease transmission, and supporting targeted public health strategies.…
Jógvan Magnus Haugaard Olsen, Viacheslav Bolnykh, Simone Meloni, Emiliano Ippoliti + 3 more
We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through the use of MPI intercommunicators. This allows exploiting the…
Martin Werner
This paper provides an abstract analysis of parallel processing strategies for spatial and spatio-temporal data. It isolates aspects such as data locality and computational locality as well as redundancy and locally sequential access as central elements of parallel algorithm design for spatial data. Furthermore, the…
Kyle Chard, Yadu Babuji, Anna Woodard, Ben Clifford + 5 more
'Mihael Hategan' 'Ian Foster' 'Mike Wilde' 'Daniel S. Katz'] Parsl is a parallel programming library for Python that aims to make it easy to specify parallelism in programs and to realize that parallelism on arbitrary parallel and distributed computing systems. Parsl relies on developers annotating Python…
Abhishek Kulkarni, Andrew Lumsdaine
We evaluate and compare four contemporary and emerging runtimes for high-performance computing (HPC) applications: Cilk, Charm++, ParalleX and AM++. We compare along three bases: programming model, execution model and the implementation on an underlying machine model. The comparison study includes a survey of each…
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…
Nikos Vasilakis, Κωνσταντίνος Καλλάς, Konstantinos Mamouras, Achilles Benetopoulos + 1 more
'Achilles Benetopoulos' 'Lazar Cvetković'] This paper presents PaSh, a system for parallelizing POSIX shell scripts. Given a script, PaSh converts it to a dataflow graph, performs a series of semantics-preserving program transformations that expose parallelism, and then converts the dataflow graph back into a…
Paul Cardosi, Bérenger Bramas, Bilal Alatas
Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow efficient parallelization across distributed…
Moises Hernandez-Fernandez, Istvan Reguly, Saad Jbabdi, Mike Giles + 2 more
The great potential of computational diffusion MRI (dMRI) relies on indirect inference of tissue microstructure and brain connections, since modelling and tractography frameworks map diffusion measurements to neuroanatomical features. This mapping however can be computationally highly expensive, particularly given the…
M. E. James, M. J. Wilkinson, H. L North, J. Engelstädter + 1 more
The independent and repeated adaptation of populations to similar environments often results in the evolution of similar forms. This phenomenon creates a strong correlation between phenotype and environment and is referred to as ‘parallel evolution.’ However, there is ongoing debate as to when we should call a system…
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…
Zeyu Xia, Canqun Yang, Chenchen Peng, Yifei Guo + 3 more
'Tao Tang' 'Yingbo Cui'] Background The advent of Single Molecule Real-Time (SMRT) sequencing has overcome many limitations of second-generation sequencing, such as limited read lengths, PCR amplification biases. However, longer reads increase data volume exponentially and high error rates make many existing alignment…
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.…
Patrizio Dazzi
Embarrassingly parallel problems are characterised by a very small amount of information to be exchanged among the parts they are split in, during their parallel execution. As a consequence they do not require sophisticated, low-latency, high-bandwidth interconnection networks but can be efficiently computed in…
Yasset Pérez‐Riverol, Roberto Vera Alvarez
Parallel and distributed application design is a major area of interest in the domain of high performance scientific and industrial computing. Over the years, various approaches have been proposed to aid parallel program developers to modeling their applications. In this paper it will be used some concepts from agile…
Simon Boothroyd, Lee-Ping Wang, David Mobley, John Chodera + 1 more
Developing accurate classical force field representations of molecules is key to realizing the full potential of molecular simulations, both as a powerful route to gaining fundamental insight into a broad spectrum of chemical and biological phenomena, and for predicting physicochemical and mechanical properties of…
Authors not listed
Fragment-based quantum chemistry offer a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations by partitioning a large calculation into smaller subsystems, then considering the many-body interactions between them. Variants of this approach have been used to…
Brijender Kahanwal
Nowadays, we are to find out solutions to huge computing problems very rapidly. It brings the idea of parallel computing in which several machines or processors work cooperatively for computational tasks. In the past decades, there are a lot of variations in perceiving the importance of parallelism in computing…
Cristian Vidal-Silva, Vannessa Duarte, Jesennia Cárdenas-Cobo, Iván Veas
Parallel computing is a current algorithmic approach to looking for efficient solutions; that is, to define a set of processes in charge of performing at the same time the same task. Advances in hardware permit the massification of accessibility to and applications of parallel computing. Nonetheless, some algorithms…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Authors not listed
This study presents a novel application of Multi-Objective Bayesian Optimization (MOBO) to enhance the formulation of flame-retardant polypropylene (PP) composites. Our goal was to optimize the chemical composition of intumescent polypropylene (PP) formulations by maximizing the Limiting Oxygen Index (LOI) and…