16 papers · ranked by Valyu relevance
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…
Gregor Mönke, Tim Schäfer, Mohsen Parto-Dezfouli, Diljit Singh Kajal + 3 more
'Stefan Fürtinger' 'Joscha Tapani Schmiedt' 'Pascal Fries'] We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes signal processing analyses across time (e.g., time-lock…
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…
Zeyi Zhang, Carlos Mora Perez, Patrick Kwon, Martin Head‐Gordon + 1 more
PARSEC.py is a Python-based real-space Kohn-Sham density functional theory (real-space KS-DFT) framework designed to provide a user- and developer-friendly platform for first-principles electronic-structure simulations. Discretization on real-space grids eliminates basis-set approximations, while enabling systematic…
Jinghan Yang, Yuyang Xu, Minhao Yao, Gao Wang + 1 more
Background Large-scale multi-ethnic DNA sequencing data is increasingly available owing to decreasing cost of modern sequencing technologies. Inference of the population structure with such sequencing data is fundamentally important. However, the ultra-dimensionality and complicated linkage disequilibrium patterns…
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…
Alvaro Estebanez, Diego R. Llanos, David Orden, Belen Palop + 1 more
'Rafael Sachetto Oliveira'] Loops are a rich source of parallelism. Unfortunately, many loops cannot be safely parallelized at compile time because the compiler is not able to guarantee that there will be no dependence violations. Thread-Level Speculation (TLS) techniques, either hardware or software-based, allow the…
Emad Alamoudi, Felipe Reck, Nils Bundgaard, Frederik Graw + 4 more
'Lutz Brusch' 'Jan Hasenauer' 'Yannik Schälte' 'Abel C.H. Chen'] Approximate Bayesian Computation (ABC) is a widely applicable and popular approach to estimating unknown parameters of mechanistic models. As ABC analyses are computationally expensive, parallelization on high-performance infrastructure is often…
Jan Janssen, Janine George, Julian Geiger, Marnik Bercx + 7 more
Numerous Workflow Management Systems (WfMS) have been developed in the field of computational materials science with different workflow formats, hindering interoperability and reproducibility of workflows in the field. To address this challenge, we introduce here the Python Workflow Definition (PWD) as a workflow…
Ashish Chapagain, Dima Abuoliem, In Ho Cho, Tongbiao Wang
Multifunctional nanosurfaces receive growing attention due to their versatile properties. Capillary force lithography (CFL) has emerged as a simple and economical method for fabricating these surfaces. In recent works, the authors proposed to leverage the evolution strategies (ES) to modify nanosurface characteristics…
Reza Rafati Bonab, Ali Akbar Jamali, Kyle Klenk, Mohammad Mahdi Moayeri + 2 more
Parallelization of the SW algorithm can be implemented on different levels: single-instruction, multiple-data (SIMD) parallelism, thread-level parallelism, process-level parallelism, and heterogeneous parallelism. SIMD parallelism, also known as vector-level parallelism, employs a controller to manage multiple…
Rick Wertenbroek, Ioannis Xenarios, Yann Thoma, Olivier Delaneau + 1 more
The sequential PBWT-based algorithms can be summarized with [vbad021-BOX3] which loops over all N genotype loci and alternates between updating the a and d arrays and running the matching algorithm or compression step. Algorithm S: Sequential PBWT-based algorithm Constants: N: #genotype loci, M: #haplotypes…
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…
Mohammed Alaa Ala’anzy, Nurdaulet Tolendi, Baizhan Baubek, Abdulmohsen Algarni + 1 more
Sorting can be approached in two main ways: sequentially and in parallel. In sequential sorting, data is processed in a single-threaded manner, which can be slow for large datasets. However, parallel sorting divides the task across multiple processing units, enabling faster results by processing data simultaneously.…
Takehiro Jimbo, Hidetoshi Matsuo, Yuya Imoto, Takumi Sodemura + 5 more
'Makoto Nishimori' 'Yoshinari Fukui' 'Takuya Hayashi' 'Tomoyuki Furuyashiki' 'Ryoichi Yokoyama'] “Preprocessing” is the first step required in brain image analysis that improves the overall quality and reliability of the results. However, it is computationally demanding and time-consuming, particularly to handle and…
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…