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Special Purpose Parallel Computer for Modelling Supramolecular Systems based on the Dynamic Lattice Liquid Model

Piotr Polanowski, Jarosław Jung, Rafał Kielbik
2010 Computational Methods in Science and Technology  
We propose constructing a parallel computing system which realizes the 3D architecture and the cooperative dynamics based on the dynamic lattice liquid (DLL) model.  ...  Hierarchical, structural and dynamic complexities of such systems require new methodological developments.  ...  The authors thank Dr.Witold Zatorski for electronic circuits preparation.  ... 
doi:10.12921/cmst.2010.16.02.147-153 fatcat:qo2s7kkwezfxvef7l75jysswwa

Cellular Automaton Simulation of Polymers

M. A. Smith, Y. Bar-Yam, Y. Rabin, N. Margolus, T. Toffoli, C. H. Bennett
1991 Materials Research Society Symposium Proceedings  
A highly efficient, two-space algorithm is devised and tested on both Cellular Automata Machines (CAMs) and serial computers.  ...  Preliminary results on the static and dynamic properties of polymers in two dimensions are reported.  ...  In the CA twospace polymer model on a CAM the time scales as M ! t m /(PV p /V) and on connection machine or hypercube as M ! t m /P.  ... 
doi:10.1557/proc-248-483 fatcat:56jtf66swrem3ohdaycnlel2zu

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment

Sepideh Mazrouee, Susan J. Little, Joel O. Wertheim, Carl Herrmann
2021 PLoS Computational Biology  
Support vector machine demonstrated one order of magnitude improvement in accuracy of assigning the sequences to the correct cluster compared to dummy uniform random classifier.  ...  We use machine learning algorithms to learn the non-linear correlation patterns between patient metadata and transmissions between HIV-positive cases.  ...  Acknowledgments We would like thank the PIRC team and UCSD Red Cap team for their in providing data and technical support in duration of this project.  ... 
doi:10.1371/journal.pcbi.1009336 pmid:34550966 pmcid:PMC8457453 fatcat:ud5tezoakrfnfbudf5qm3asmui

The Mechanisms for Preferential Attachment of Nanoparticles in Liquid Determined Using Liquid Cell Electron Microscopy, Machine Learning, and Molecular Dynamics

Taylor Woehl, David Welch, Chiwoo Park, Roland Faller, James Evans, Nigel Browning
2016 Microscopy and Microanalysis  
Here we employ liquid cell scanning transmission electron microscopy (STEM), machine learning-based image analysis [4], and steered molecular dynamics (SMD) simulations to demonstrate that the experimentally  ...  The use of advanced machine learning-based image analysis algorithms [3] to interpret dynamic liquid cell electron microscopy in situ movies promises to provide insights into complex nanoparticle growth  ...  Here we employ liquid cell scanning transmission electron microscopy (STEM), machine learning-based image analysis [4] , and steered molecular dynamics (SMD) simulations to demonstrate that the experimentally  ... 
doi:10.1017/s1431927616004918 fatcat:a4ae2b4mk5hpjlngcaqku5qsz4

Parallel atomistic simulations

Grant S. Heffelfinger
2000 Computer Physics Communications  
However, systolic loop methods are designed for multi-processor machines with limited inter connectivity and have faded from the scene for use with molecular dynamics [96] [97] [98] [99] [100] [101] 4  ...  Two other similar algorithms appear in the literature, both for single instruction multiple data (SJMD) architectures, one for the Connection Machine CM-200 [74] and another for a MasPar NIP-2 [75]  ... 
doi:10.1016/s0010-4655(00)00050-3 fatcat:kj2ce3cjzvgf5khzk4t3qqyz7m

Molecular dynamics simulation on a network of workstations using a machine-independent parallel programming language

M A Shifman, A Windemuth, K Schulten, P L Miller
1991 Proceedings. Symposium on Computer Applications in Medical Care  
This paper develops a straightforward but effective algorithm for molecular dynamics simulations using the machine-independent parallel programming language, Linda.  ...  This algorithm offers a portable cost-effective alternative for molecular dynamics simulations.  ...  Acknowledgements This research was funded in part by NIH grants T15 LM07056 and RO1 LM05044 from the National Library of Medicine.  ... 
pmid:1807634 pmcid:PMC2247565 fatcat:abpixqi6rzbmvi77zrokudkpji

A high performance, low complexity algorithm for compile-time task scheduling in heterogeneous systems

T. Hagras, J. Janeček
2005 Parallel Computing  
The analysis and experiments have shown that HCPFD outperforms on average all other higher complexity algorithms.  ...  In this paper we present a simple scheduling algorithm based on list-scheduling and task-duplication on a bounded number of heterogeneous machines called Heterogeneous Critical Parents with Fast Duplicator  ...  Molecular Dynamic Code), HCPFD outperformed the other algorithms in terms of performance and complexity.  ... 
doi:10.1016/j.parco.2005.04.002 fatcat:yx6mefq3pbaqfbf5cevbappwui

Hyper-systolic parallel computing

T. Lippert, A. Seyfried, A. Bode, K. Schilling
1998 IEEE Transactions on Parallel and Distributed Systems  
A new class of parallel algorithms is introduced that can achieve a complexity of O(n 1 In molecular dynamics applications with long range forces, e. g., exact state-of-the-art calculations are restricted  ...  rôle in molecular dynamics with short range forces [8] . 3 Here we assume that the numbers of processors, p, and array elements, n, are equal.  ...  Part of our numerical results has been achieved on the 1024-node connection machine CM5 of the Advanced Computing Laboaratory at Los Alamos National Laboratory, USA.  ... 
doi:10.1109/71.663861 fatcat:jshlqyog4barzmipc2lcpkwoau

Protein Structured Reservoir computing for Spike-based Pattern Recognition [article]

Karolos-Alexandros Tsakalos, Georgios Ch. Sirakoulis, Andrew Adamatzky, Jim Smith
2020 arXiv   pre-print
We apply on a single readout layer various training methods in a supervised fashion to investigate whether the molecular structured Reservoir Computing (RC) system is capable to deal with machine learning  ...  Following the trend, we explore an unconventional route of implementing a reservoir computing on a single protein molecule and introduce neuromorphic connectivity with a small-world networking property  ...  VT-1 molecule, while their neuromorphic communication relies on the architecture based on both its hard molecular connectivity that is described by its chemical bonds and soft molecular connectivity described  ... 
arXiv:2008.03330v1 fatcat:fjzlh7ta65gvdpyr44xz7mik3a

A Priority-Based Task Scheduling Algorithm in Grid

Weifeng Sun, Yudan Zhu, Zhiyuan Su, Dong Jiao, Mingchu Li
2010 2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming  
Simulations are done on examples of DAG, and simulation results shown that the performance of P-TSA is better than other scheduling algorithms such as Min-min and Max-min.  ...  Task scheduling algorithms are used to improve the grid performance by minimizing the scheduling length. A priority-based task scheduling algorithm (P-TSA) in grid is proposed in this paper.  ...  The average of scheduling length of P-TSA based on DAG of molecular dynamics code is 73.3% of Max-min algorithm and 76.3% of Min-min algorithm, and the scheduling length can save 41.2% time at most.  ... 
doi:10.1109/paap.2010.24 dblp:conf/paap/SunZSJL10 fatcat:gfrdiacdv5hhlbdu3fk7shw35m

Exact Maximum Clique Algorithm for Different Graph Types Using Machine Learning

Kristjan Reba, Matej Guid, Kati Rozman, Dušanka Janežič, Janez Konc
2021 Mathematics  
In this paper, improvements based on machine learning (ML) are added to a dynamic algorithm for finding the maximum clique in a protein graph, Maximum Clique Dynamic (MaxCliqueDyn; short: MCQD).  ...  Such adaptability to graph types based on state-of-the-art machine learning is a novel approach that has not been used in most graph-theoretic algorithms.  ...  A molecular docking graph is a graph whose nodes are docked molecular fragments and in which two nodes are connected if the docked fragments can be connected with linker atoms to reconstruct the original  ... 
doi:10.3390/math10010097 fatcat:sq476pdli5b4njy3zarvwfpuci

Overcoming Communication Latency Barriers in Massively Parallel Scientific Computation

Ron Dror, J.P. Grossman, Kenneth Mackenzie, Brian Towles, Edmond Chow, John Salmon, Cliff Young, Joseph Bank, Brannon Batson, David Shaw, Jeffrey S. Kuskin, Richard H. Larson (+2 others)
2011 IEEE Micro  
Acknowledgments We thank Ed Priest, Larry Nociolo, Chester Li, and Jon Peticolas for their work on high-speed analog circuits and signal integrity in Anton's communication channels; Stan Wang for design  ...  This article describes the architectural and algorithmic approaches 7 that reduce the total communication time on Anton's critical path to less than 3 percent of that of the nextfastest molecular dynamics  ...  Shaw Research, where he works on the development of new algorithms and machine architectures for high-speed biomolecular simulations and on the application of such simulations to basic scientific research  ... 
doi:10.1109/mm.2011.38 fatcat:n5hkj2k53jforilvu23bt2bbly

Molecular simulations: past, present, and future (a Topical Issue in EPJB)

G. Ciccotti, C. Dellago, M. Ferrario, E. R. Hernández, M. E. Tuckerman
2022 European Physical Journal B : Condensed Matter Physics  
Two of the corner stones of molecular simulations were introduced then, namely the Monte Carlo (MC) sampling technique [3] and the molecular dynamics (MD) method [4] .  ...  That the two techniques appeared almost simultaneously at this  ...  Acknowledgements The authors wish to express their gratefulness for the assistance offered by Sandrine Karpe, Christiane Winter-Todorov and Isabelle Auffret-Babak during the preparation and publication  ... 
doi:10.1140/epjb/s10051-021-00249-x fatcat:nfavyrnn75egvoog57nyl6p45e

Parallel protein folding with STAPL

Shawna Thomas, Gabriel Tanase, Lucia K. Dale, Jose M. Moreira, Lawrence Rauchwerger, Nancy M. Amato
2005 Concurrency and Computation  
These include lattice models [14], energy minimization [15,16], molecular dynamics [17-20], Monte Carlo methods [21,22], and genetic algorithms [23,24].  ...  Molecular dynamics and Monte Carlo methods PARALLEL PROTEIN FOLDING WITH STAPL STAPL STAPL is a framework for parallel C++ code [10] [11] [12] .  ...  NAMD [35, 36] is a parallel molecular dynamics code designed for high-end parallel machines.  ... 
doi:10.1002/cpe.950 fatcat:is77asyxcjhgpb5aqlrlmor6da

Integrating Machine Learning with Physics-Based Modeling [article]

Weinan E, Jiequn Han, Linfeng Zhang
2020 arXiv   pre-print
Molecular dynamics and moment closure of kinetic equations are used as examples to illustrate the main issues discussed.  ...  We end with a general discussion on where this integration will lead us to, and where the new frontier will be after machine learning is successfully integrated into scientific modeling.  ...  Molecular modeling One of the most successful applications of machine learning to scientific modeling is in molecular dynamics.  ... 
arXiv:2006.02619v1 fatcat:dbaswddd7bdljjhl3can7tjzfm
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