Düzce University Journal of Science & Technology
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CESMIX: Center for the Exascale Simulation of Materials in Extreme Environments
CESMIX: Center for the Exascale Simulation of Materials in Extreme Environments Project Overview Youssef Marzouk MIT PSAAP-3 Team 18 August 2020 The CESMIX team • Our team integrates expertise in quantum chemistry, atomistic simulation, materials science; hypersonic flow; validation & uncertainty quantification; numerical algorithms; parallel computing, programming languages, compilers, and software performance engineering 1 Project objectives • Exascale simulation of materials in extreme environments • In particular: ultrahigh temperature ceramics in hypersonic flows – Complex materials, e.g., metal diborides – Extreme aerothermal and chemical loading – Predict materials degradation and damage (oxidation, melting, ablation), capturing the central role of surfaces and interfaces • New predictive simulation paradigms and new CS tools for the exascale 2 Broad relevance • Intense current interest in reentry vehicles and hypersonic flight – A national priority! – Materials technologies are a key limiting factor • Material properties are of cross-cutting importance: – Oxidation rates – Thermo-mechanical properties: thermal expansion, creep, fracture – Melting and ablation – Void formation • New systems being proposed and fabricated (e.g., metallic high-entropy alloys) • May have relevance to materials aging • Yet extreme environments are largely inaccessible in the laboratory – Predictive simulation is an essential path… 3 Demonstration problem: specifics • Aerosurfaces of a hypersonic vehicle… • Hafnium diboride (HfB2) promises necessary temperature -
Popular GPU-Accelerated Applications
LIFE & MATERIALS SCIENCES GPU-ACCELERATED APPLICATIONS | CATALOG | AUG 12 LIFE & MATERIALS SCIENCES APPLICATIONS CATALOG Application Description Supported Features Expected Multi-GPU Release Status Speed Up* Support Bioinformatics BarraCUDA Sequence mapping software Alignment of short sequencing 6-10x Yes Available now reads Version 0.6.2 CUDASW++ Open source software for Smith-Waterman Parallel search of Smith- 10-50x Yes Available now protein database searches on GPUs Waterman database Version 2.0.8 CUSHAW Parallelized short read aligner Parallel, accurate long read 10x Yes Available now aligner - gapped alignments to Version 1.0.40 large genomes CATALOG GPU-BLAST Local search with fast k-tuple heuristic Protein alignment according to 3-4x Single Only Available now blastp, multi cpu threads Version 2.2.26 GPU-HMMER Parallelized local and global search with Parallel local and global search 60-100x Yes Available now profile Hidden Markov models of Hidden Markov Models Version 2.3.2 mCUDA-MEME Ultrafast scalable motif discovery algorithm Scalable motif discovery 4-10x Yes Available now based on MEME algorithm based on MEME Version 3.0.12 MUMmerGPU A high-throughput DNA sequence alignment Aligns multiple query sequences 3-10x Yes Available now LIFE & MATERIALS& LIFE SCIENCES APPLICATIONS program against reference sequence in Version 2 parallel SeqNFind A GPU Accelerated Sequence Analysis Toolset HW & SW for reference 400x Yes Available now assembly, blast, SW, HMM, de novo assembly UGENE Opensource Smith-Waterman for SSE/CUDA, Fast short -
Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds
J. Comput. Chem. Jpn., Vol. 15, No. 1, pp. 13–21 (2016) ©2016 Society of Computer Chemistry, Japan Technical Paper Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds Toshihiko HANAI Health Research Foundation, Research Institute for Production Development 4F, 15 Shimogamo-morimoto-cho, Sakyo-ku, Kyoto 606-0805, Japan e-mail: [email protected] (Received: October 11, 2015; Accepted for publication: April 14, 2016; Online publication: May 6, 2016) Computational chemistry programs were evaluated as aids to teaching qualitative analytical chemistry. Compu- tational chemical calculations can predict absorption spectra, thus enabling the modeling of indicator dissociation mechanisms by different computational chemical programs using a personal computer. An updated MNDO program among 51 programs was found to be the best predictor to explain the dissociation mechanisms of isobenzofuranones and sulfonephthaleins. Unknown dissociation constants were predicted from atomic partial charges instead of Ham- mett's constants. Keywords: Quantitative analysis of dissociation mechanisms, Isobenzofuranone, Sulfonephthalein, Computational chemistry 1 Introduction the absorption wavelength and electron density changes were not well described. The dissociation mechanisms, maximum How to quantitatively teach qualitative analytical chemistry is wavelengths, and electron density maps of isobenzofuranones a very important subject for analytical chemists. Previously, a and sulfonephthaleins were, therefore, evaluated by in silico method to teach molecular interaction mechanisms in chroma- analysis despite the anticipated poor precision. The experimen- tography was quantitatively achieved using molecular mechan- tally measured dissociation of phenolphthalein is described ics and MOPAC programs [1]. Furthermore, the reaction mech- using four dissociation structures, where the ionization of two anisms of highly sensitive detections were also quantitatively phenolic hydroxyl groups converts the neutral molecular form described [2,3]. -
A Comparative Study of the Efficiency of HCV NS3/4A Protease Drugs
Life Sciences 217 (2019) 176–184 Contents lists available at ScienceDirect Life Sciences journal homepage: www.elsevier.com/locate/lifescie A comparative study of the efficiency of HCV NS3/4A protease drugs against different HCV genotypes using in silico approaches T ⁎ Ahmed A. Ezat , Wael M. Elshemey Biophysics Department, Faculty of Science, Cairo University, 12613 Giza, Egypt ARTICLE INFO ABSTRACT Keywords: Aims: To investigate the efficacy of Direct Acting Antivirals (DAAs) in the treatment of different Hepatitis C HCV Virus (HCV) genotypes. NS3/4A protease Main methods: Homology modeling is used to predict the 3D structures of different genotypes while molecular Molecular docking docking is employed to predict genotype – drug interactions (Binding Mode) and binding free energy (Docking Homology modeling Score). Key findings: Simeprevir (TMC435) and to a lesser degree MK6325 are the best drugs among the studied drugs. The predicted affinity of drugs against genotype 1a is always better than other genotypes. P2–P4 macrocyclic drugs show better performance against genotypes 2, 3 and 5. Macrocyclic drugs are better than linear drugs. Significance: HCV is one of the major health problems worldwide. Until the discovery of DAAs, HCV treatment faced many failures. DAAs target key functional machines of the virus life cycle and shut it down. NS3/4A protease is an important target and several drugs have been designed to inhibit its functions. There are several NS3/4A protease drugs approved by Food and Drug Administration (FDA). Unfortunately, the virus exhibits resistance against these drugs. This study is significant in elucidating that no one drug is able to treat different genotypes with the same efficiency. -
Kepler Gpus and NVIDIA's Life and Material Science
LIFE AND MATERIAL SCIENCES Mark Berger; [email protected] Founded 1993 Invented GPU 1999 – Computer Graphics Visual Computing, Supercomputing, Cloud & Mobile Computing NVIDIA - Core Technologies and Brands GPU Mobile Cloud ® ® GeForce Tegra GRID Quadro® , Tesla® Accelerated Computing Multi-core plus Many-cores GPU Accelerator CPU Optimized for Many Optimized for Parallel Tasks Serial Tasks 3-10X+ Comp Thruput 7X Memory Bandwidth 5x Energy Efficiency How GPU Acceleration Works Application Code Compute-Intensive Functions Rest of Sequential 5% of Code CPU Code GPU CPU + GPUs : Two Year Heart Beat 32 Volta Stacked DRAM 16 Maxwell Unified Virtual Memory 8 Kepler Dynamic Parallelism 4 Fermi 2 FP64 DP GFLOPS GFLOPS per DP Watt 1 Tesla 0.5 CUDA 2008 2010 2012 2014 Kepler Features Make GPU Coding Easier Hyper-Q Dynamic Parallelism Speedup Legacy MPI Apps Less Back-Forth, Simpler Code FERMI 1 Work Queue CPU Fermi GPU CPU Kepler GPU KEPLER 32 Concurrent Work Queues Developer Momentum Continues to Grow 100M 430M CUDA –Capable GPUs CUDA-Capable GPUs 150K 1.6M CUDA Downloads CUDA Downloads 1 50 Supercomputer Supercomputers 60 640 University Courses University Courses 4,000 37,000 Academic Papers Academic Papers 2008 2013 Explosive Growth of GPU Accelerated Apps # of Apps Top Scientific Apps 200 61% Increase Molecular AMBER LAMMPS CHARMM NAMD Dynamics GROMACS DL_POLY 150 Quantum QMCPACK Gaussian 40% Increase Quantum Espresso NWChem Chemistry GAMESS-US VASP CAM-SE 100 Climate & COSMO NIM GEOS-5 Weather WRF Chroma GTS 50 Physics Denovo ENZO GTC MILC ANSYS Mechanical ANSYS Fluent 0 CAE MSC Nastran OpenFOAM 2010 2011 2012 SIMULIA Abaqus LS-DYNA Accelerated, In Development NVIDIA GPU Life Science Focus Molecular Dynamics: All codes are available AMBER, CHARMM, DESMOND, DL_POLY, GROMACS, LAMMPS, NAMD Great multi-GPU performance GPU codes: ACEMD, HOOMD-Blue Focus: scaling to large numbers of GPUs Quantum Chemistry: key codes ported or optimizing Active GPU acceleration projects: VASP, NWChem, Gaussian, GAMESS, ABINIT, Quantum Espresso, BigDFT, CP2K, GPAW, etc. -
Kingston University London the Antibiotic Resistance Growth Plate
Kingston University London The Antibiotic Resistance Growth Plate (ARGP) as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli. A thesis submitted in partial fulfilment for the degree of Doctor of Philosophy By Lucky Bonnie Lucia CULLEN Faculty of Science, Engineering and Computing February 2019 Declaration This thesis entitled ‘The Antibiotic Resistance Growth Plate (ARGP)’ as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli’ is based upon the work conducted in the Faculty of Science, Engineering and Computing at Kingston University London and in collaboration with Dr Philip Aldridge at Newcastle University and Katie Hopkins and Neil Woodford from Public Health England. All the work described is the candidate’s own original work unless otherwise stated. None of the work presented has been submitted for another degree internally or externally. i Acknowledgements At the start of this PhD I had a dream, a dream which could have never been accomplished without the support of many people. Firstly, I would like to express my sincere appreciation to my director of studies Professor Mark Fielder, your provision, guidance and unconditional belief in my potential has contributed significantly to the completion of this thesis. I would also like to acknowledge the overwhelming support received from, Dr Scott Lawton, Camilla Eldridge and Ben Jones, your wealth of knowledge and expertise in the field of evolutionary biology and bioinformatics has assisted greatly in concluding the work within this PhD. I would also like to praise the incredible multidisciplinary support received at Kingston University, specifically that from Dr Gary-Forster Wilkins, Dr Adam Le Gresley, Dr Brian Rooney, Dr James Denholm-Price and Richard Giddens. -
Conformational Analysis with Scigress
CONFORMATIONAL ANALYSIS WITH SCIGRESS During this laboratory period you will use two computational chemistry methods to carry out conformational analysis experiments on butane, cyclohexanol and cis-1,3-cyclohexanediol. Mechanics is a method which uses classical Newtonian mechanics to compute the energies of molecules. Bonds are treated as springs and atoms as balls attached to these springs. MOPAC is a method which uses quantum mechanics to calculate the energies of molecules and determine their optimum geometries and other properties; MOPAC is an acronym for Molecular Orbital PACkage Conformational Energy of Butane 1. Build and beautify a molecule of butane. Save your drawing with the name "butane." 2. Highlight (select) the four carbon atoms (in order). All other atoms should be grayed out. Choose Adjust→Dihedral Angle from the menu bar. Select “Define Geometry Label” and “Search”. Apply and then click OK. The workspace containing the butane molecule will reappear with the dihedral angle written in blue across it. The letter S will appear next to the value of the dihedral angle indicating that it is a search label. Re-save the drawing 3. Choose Experiment→New from the menu bar; the experiment dialog box should appear. Choose chemical sample conformations (CAChe 5.0 experiments) from the “Property of” box. Choose optimized map in the “Property” box. Click Start (if an error appears click OK and re-try). 4. Two adjacent windows should appear presenting the results of the calculation. The left window is a plot of potential energy versus dihedral angle for the butane molecule. The graph colors represent the relative energies of the butane molecule with various dihedral angles. -
Molecular Dynamics (MD) for Cancer Control Protocol
Molecular Dynamics (MD) for Cancer control Protocol Claudio Nicolini ( [email protected] ) Claudio Ando Nicolini's Lab, NanoWorld, USA; HC Professor Nanobiotechnology, Lomonosov Moscow State University, Russia; Foreign Member Russian Academy of Sciences; President NWI Fondazione EL.B.A. Nicolini; Editor-in-Chief NWJ, Santa Clara, USA Marine Bozdaganyan Claudio Ando Nicolini's Lab, NanoWorld, USA; Lomonosov Moscow State University (MSU), Moscow, Russia; Fondazione EL.B.A. Nicolini Nicola Luigi Bragazzi Claudio Ando Nicolini's Lab, NanoWorld, USA Philippe Orekhov Claudio Ando Nicolini's Lab, NanoWorld, USA Eugenia Pechkova Claudio Ando Nicolini's Lab, NanoWorld, USA Method Article Keywords: Langmuir-Blodgett (LB)-based crystallography Posted Date: March 15th, 2016 DOI: https://doi.org/10.1038/protex.2016.016 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/13 Abstract In the present protocol, we describe how molecular dynamics \(MD) can be applied for studying Langmuir-Blodgett \(LB)-based crystal proteins. MD can therefore play a major role in nanomedicine, as well as in personalized medicine. Introduction The computer simulation of dynamics in molecular systems is widely used in molecular physics, biotechnology, medicine, chemistry and material sciences to predict physical and mechanical properties of new samples of matter. In the molecular dynamics method there is a polyatomic molecular system in which all atoms are interacting like material points, and behavior of the atoms is described by the equations of classical mechanics. This method allows doing simulations of the system of the order of 106 atoms in the time range up to 1 microsecond. -
The First Berberine-Based Inhibitors of Tyrosyl-DNA Phosphodiesterase 1 (Tdp1), an Important DNA Repair Enzyme
International Journal of Molecular Sciences Article The First Berberine-Based Inhibitors of Tyrosyl-DNA Phosphodiesterase 1 (Tdp1), an Important DNA Repair Enzyme Elizaveta D. Gladkova 1,2, Ivan V. Nechepurenko 1, Roman A. Bredikhin 1, Arina A. Chepanova 3, Alexandra L. Zakharenko 3, Olga A. Luzina 1 , Ekaterina S. Ilina 3, Nadezhda S. Dyrkheeva 3, Evgeniya M. Mamontova 3, Rashid O. Anarbaev 2,3,Jóhannes Reynisson 4 , Konstantin P. Volcho 1,2,* , Nariman F. Salakhutdinov 1,2 and Olga I. Lavrik 2,3 1 N. N. Vorozhtsov Novosibirsk Institute of Organic Chemistry, Siberian Branch of the Russian Academy of Sciences, 9, Akademika Lavrentieva Ave., Novosibirsk 630090, Russia; [email protected] (E.D.G.); [email protected] (I.V.N.); [email protected] (R.A.B.); [email protected] (O.A.L.); [email protected] (N.F.S.) 2 Novosibirsk State University, Pirogova str. 1, Novosibirsk 630090, Russia; [email protected] (R.O.A.); [email protected] (O.I.L.) 3 Novosibirsk Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 8, Akademika Lavrentieva Ave., Novosibirsk 630090, Russia; [email protected] (A.A.C.); [email protected] (A.L.Z.); [email protected] (E.S.I.); [email protected] (N.S.D.); [email protected] (E.M.M.) 4 School of Pharmacy and Bioengineering, Keele University, Hornbeam Building, Staffordshire ST5 5BG, UK; [email protected] * Correspondence: [email protected] Received: 31 August 2020; Accepted: 26 September 2020; Published: 28 September 2020 Abstract: A series of berberine and tetrahydroberberine sulfonate derivatives were prepared and tested against the tyrosyl-DNA phosphodiesterase 1 (Tdp1) DNA-repair enzyme. -
POLISH SUPERCOMPUTING CENTERS (WCSS – Wrocław, ICM – Warsaw, CYFRONET - Kraków, TASK – Gdańsk, PCSS – Poznań)
POLISH SUPERCOMPUTING CENTERS (WCSS – Wrocław, ICM – Warsaw, CYFRONET - Kraków, TASK – Gdańsk, PCSS – Poznań) Provide free access to supercomputers and licensed software for all academic users in form of computational grants. In order to obtain access Your supervisor has to write grant application and acknowledge use of supercomputer resources in published papers. 1) Wrocław Networking and Supercomputing Center Wrocławskie Centrum Sieciowo-Superkomputerowe https://www.wcss.pl/ • Klaster Bem - najnowszy superkomputer WCSS, posiadający 22 tyś. rdzeni obliczeniowych o łącznej mocy 860 TFLOPS. Klaster liczy 720 węzłów obliczeniowych 24-rdzeniowych (Intel Xeon E5-2670 v3 2.3 GHz, Haswell) oraz 192 węzły obliczeniowe 28-rdzeniowe (Intel Xeon E5- 2697 v3 2.6 GHz, Haswell). Posiada 74,6 TB pamięci RAM (64, 128 lub 512 GB/węzeł) (złóż wniosek o grant) • Klaster kampusowy - klaster włączony w struktury projektu PLATON U3, świadczący usługi aplikacji na żądanie. Klaster liczy 48 węzłów, w tym 16 wyposażonych w karty NVIDIA Quadro FX 580. 8688 rdzeni obliczeniowych 46 TB pamięci RAM 8 PB przestrzeni dyskowej • Available software Abaqus ⋅ ABINIT ⋅ ADF ⋅ Amber ⋅ ANSYS [ ANSYS CFD: Fluent, CFX, ICEM; Mechanical ] ⋅ AutoDock ⋅ BAGEL ⋅ Beast ⋅ Biovia [ Materials Studio, Discovery Studio ] ⋅ Cfour ⋅ Comsol ⋅ CP2K ⋅ CPMD ⋅ CRYSTAL09 ⋅ Dalton ⋅ DIRAC ⋅ FDS-SMV ⋅ GAMESS ⋅ Gaussian ⋅ Gromacs ⋅ IDL ⋅ Lumerical [ FDTD, MODE ] ⋅ Maple ⋅ Mathcad ⋅ Mathematica⋅ Matlab ⋅ Molcas ⋅ Molden ⋅ Molpro ⋅ MOPAC ⋅ NAMD ⋅ NBO ⋅ NWChem ⋅ OpenFOAM ⋅ OpenMolcas ⋅ Orca ⋅ Quantum -
Software and Techniques for Bio-Molecular Modelling
Software and Techniques for Bio-Molecular Modelling Azat Mukhametov Published by Austin Publications LLC Published Date: December 01, 2016 Online Edition available at http://austinpublishinggroup.com/ebooks For reprints, please contact us at [email protected] All book chapters are Open Access distributed under the Creative Commons Attribution 4.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of the publication. Upon publication of the eBook, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work, identifying the original source. Statements and opinions expressed in the book are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Software and Techniques for Bio-Molecular Modelling | www.austinpublishinggroup.com/ebooks 1 Copyright Mukhametov A.This book chapter is open access distributed under the Creative Commons Attribution 4.0 International License, which allows users to download, copy and build upon published articles even for com- mercial purposes, as long as the author and publisher are properly credited. We consider to publish more books on the topics of drug design, molecular modelling, and structure-activity relationships. -
Openmolcas: from Source Code to Insight Ignacio Fdez
Article Cite This: J. Chem. Theory Comput. XXXX, XXX, XXX−XXX pubs.acs.org/JCTC OpenMolcas: From Source Code to Insight Ignacio Fdez. Galvan,́ 1,2 Morgane Vacher,1 Ali Alavi,3 Celestino Angeli,4 Francesco Aquilante,5 Jochen Autschbach,6 Jie J. Bao,7 Sergey I. Bokarev,8 Nikolay A. Bogdanov,3 Rebecca K. Carlson,7,9 Liviu F. Chibotaru,10 Joel Creutzberg,11,12 Nike Dattani,13 Mickael̈ G. Delcey,1 Sijia S. Dong,7,14 Andreas Dreuw,15 Leon Freitag,16 Luis Manuel Frutos,17 Laura Gagliardi,7 Fredé rić Gendron,6 Angelo Giussani,18,19 Leticia Gonzalez,́ 20 Gilbert Grell,8 Meiyuan Guo,1,21 Chad E. Hoyer,7,22 Marcus Johansson,12 Sebastian Keller,16 Stefan Knecht,16 Goran Kovacevič ,́ 23 Erik Kallman,̈ 1 Giovanni Li Manni,3 Marcus Lundberg,1 Yingjin Ma,16 Sebastian Mai,20 Joaõ Pedro Malhado,24 Per Åke Malmqvist,12 Philipp Marquetand,20 Stefanie A. Mewes,15,25 Jesper Norell,11 Massimo Olivucci,26,27,28 Markus Oppel,20 Quan Manh Phung,29 Kristine Pierloot,29 Felix Plasser,30 Markus Reiher,16 Andrew M. Sand,7,31 Igor Schapiro,32 Prachi Sharma,7 Christopher J. Stein,16,33 Lasse Kragh Sørensen,1,34 Donald G. Truhlar,7 Mihkel Ugandi,1,35 Liviu Ungur,36 Alessio Valentini,37 Steven Vancoillie,12 Valera Veryazov,12 Oskar Weser,3 Tomasz A. Wesołowski,5 Per-Olof Widmark,12 Sebastian Wouters,38 Alexander Zech,5 J. Patrick Zobel,12 and Roland Lindh*,2,39 1Department of Chemistry − Ångström Laboratory, Uppsala University, P.O.