14 papers · ranked by Valyu relevance
Claudia Misale, Giulio Ferrero, Massimo Torquati, Marco Aldinucci
In this paper, we advocate high-level programming methodology for next generation sequencers (NGS) alignment tools for both productivity and absolute performance. We analyse the problem of parallel alignment and review the parallelisation strategies of the most popular alignment tools, which can all be abstracted to a…
Gianni D'Angelo, Salvatore Rampone
Background The huge quantity of data produced in Biomedical research needs sophisticated algorithmic methodologies for its storage, analysis, and processing. High Performance Computing (HPC) appears as a magic bullet in this challenge. However, several hard to solve parallelization and load balancing problems arise in…
José Colmenares, Antonella Galizia, Jesús Ortiz, Andrea Clematis + 1 more
'Walter Rocchia'] The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological…
Predrag Brođanac, Josip Novak, Ivica Boljat
Today, almost every computer has at least one multicore processor. To remain in stride with hardware developments, numerous university faculties oriented towards computer science have introduced parallel programming as an integral part of their courses. The question is, given the availability of parallel architectures…
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…
Fan Xu, Li Shen, Zhiying Wang, Bo Su + 2 more
Exploiting potential thread-level parallelism (TLP) is becoming the key factor to improving performance of programs on multicore or many-core systems. Among various kinds of parallel execution models, the software-based speculative parallel model has become a research focus due to its low cost, high efficiency…
Xiandong Meng, Yanqing Ji
This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications-hidden Markov models (HMM). We show the detailed performance…
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…
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…
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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…
Alexander S. Shved, Blake E. Ocampo, Elena S. Burlova, Casey L. Olen + 2 more
The construction, management and analysis of large in silico molecular libraries is critical in many areas of modern chemistry. Herein, we introduce the MOLecular LIibrary toolkit, "molli", which is a Python 3 cheminformatics module that provides a streamlined interface for manipulating large in silico libraries.…
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The python package ArchOnML ("Archive-On-Machine-Learning") is introduced, which can perform virtual screening projects covering up to millions of structural derivatives through the use of Kernel Ridge Regression models. It supports the full workflow of setting up calculation inputs for external quantum chemistry…
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Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…