Computational Chemistry a Teaser Introduction
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Free and Open Source Software for Computational Chemistry Education
Free and Open Source Software for Computational Chemistry Education Susi Lehtola∗,y and Antti J. Karttunenz yMolecular Sciences Software Institute, Blacksburg, Virginia 24061, United States zDepartment of Chemistry and Materials Science, Aalto University, Espoo, Finland E-mail: [email protected].fi Abstract Long in the making, computational chemistry for the masses [J. Chem. Educ. 1996, 73, 104] is finally here. We point out the existence of a variety of free and open source software (FOSS) packages for computational chemistry that offer a wide range of functionality all the way from approximate semiempirical calculations with tight- binding density functional theory to sophisticated ab initio wave function methods such as coupled-cluster theory, both for molecular and for solid-state systems. By their very definition, FOSS packages allow usage for whatever purpose by anyone, meaning they can also be used in industrial applications without limitation. Also, FOSS software has no limitations to redistribution in source or binary form, allowing their easy distribution and installation by third parties. Many FOSS scientific software packages are available as part of popular Linux distributions, and other package managers such as pip and conda. Combined with the remarkable increase in the power of personal devices—which rival that of the fastest supercomputers in the world of the 1990s—a decentralized model for teaching computational chemistry is now possible, enabling students to perform reasonable modeling on their own computing devices, in the bring your own device 1 (BYOD) scheme. In addition to the programs’ use for various applications, open access to the programs’ source code also enables comprehensive teaching strategies, as actual algorithms’ implementations can be used in teaching. -
User Guide of Computational Facilities
Physical Chemistry Unit Departament de Quimica User Guide of Computational Facilities Beta Version System Manager: Marc Noguera i Julian January 20, 2009 Contents 1 Introduction 1 2 Computer resources 2 3 Some Linux tools 2 4 The Cluster 2 4.1 Frontend servers . 2 4.2 Filesystems . 3 4.3 Computational nodes . 3 4.4 User’s environment . 4 4.5 Disk space quota . 4 4.6 Data Backup . 4 4.7 Generation of SSH keys for automatic SSH login . 4 4.8 Submitting jobs to the cluster . 5 4.8.1 Typical queue system commands . 6 4.8.2 HomeMade scripts . 6 4.8.3 Create your own submit script . 6 4.8.4 Submitting Parallel Calculations . 7 5 Available Software 9 5.1 Chemisty software . 9 5.2 Development Software . 10 5.3 How to use the software . 11 5.4 Non-default environments . 11 6 Your Linux Workstation 11 6.1 Disk space on your workstation . 12 6.2 Workstation Data Backup . 12 6.3 Running virtual Windows XP . 13 6.3.1 The Windows XP Environment . 13 6.4 Submitting calculations to your dekstop . 13 6.5 Network dependent structure . 14 7 Your WindowsXP Workstation 14 7.1 Workstation Data Backup . 14 8 Frequently asked questions 14 1 Introduction This User Guide is aimed to the standard user of the computer facilities in the ”Unitat de Quimica Fisica” in the Universitat Autnoma de Barcelona. It is not assumed that you have a knowledge of UNIX/Linux. However, you are 1 encouraged to take a close look to the linux guides that will be pointed out. -
Open Babel Documentation Release 2.3.1
Open Babel Documentation Release 2.3.1 Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.) December 05, 2011 Contents 1 Introduction 3 1.1 Goals of the Open Babel project ..................................... 3 1.2 Frequently Asked Questions ....................................... 4 1.3 Thanks .................................................. 7 2 Install Open Babel 9 2.1 Install a binary package ......................................... 9 2.2 Compiling Open Babel .......................................... 9 3 obabel and babel - Convert, Filter and Manipulate Chemical Data 17 3.1 Synopsis ................................................. 17 3.2 Options .................................................. 17 3.3 Examples ................................................. 19 3.4 Differences between babel and obabel .................................. 21 3.5 Format Options .............................................. 22 3.6 Append property values to the title .................................... 22 3.7 Filtering molecules from a multimolecule file .............................. 22 3.8 Substructure and similarity searching .................................. 25 3.9 Sorting molecules ............................................ 25 3.10 Remove duplicate molecules ....................................... 25 3.11 Aliases for chemical groups ....................................... 26 4 The Open Babel GUI 29 4.1 Basic operation .............................................. 29 4.2 Options ................................................. -
The Impact of Density Functional Theory on Materials Research
www.mrs.org/bulletin functional. This functional (i.e., a function whose argument is another function) de- scribes the complex kinetic and energetic interactions of an electron with other elec- Toward Computational trons. Although the form of this functional that would make the reformulation of the many-body Schrödinger equation exact is Materials Design: unknown, approximate functionals have proven highly successful in describing many material properties. Efficient algorithms devised for solving The Impact of the Kohn–Sham equations have been imple- mented in increasingly sophisticated codes, tremendously boosting the application of DFT methods. New doors are opening to in- Density Functional novative research on materials across phys- ics, chemistry, materials science, surface science, and nanotechnology, and extend- ing even to earth sciences and molecular Theory on Materials biology. The impact of this fascinating de- velopment has not been restricted to aca- demia, as DFT techniques also find application in many different areas of in- Research dustrial research. The development is so fast that many current applications could Jürgen Hafner, Christopher Wolverton, and not have been realized three years ago and were hardly dreamed of five years ago. Gerbrand Ceder, Guest Editors The articles collected in this issue of MRS Bulletin present a few of these suc- cess stories. However, even if the compu- Abstract tational tools necessary for performing The development of modern materials science has led to a growing need to complex quantum-mechanical calcula- tions relevant to real materials problems understand the phenomena determining the properties of materials and processes on are now readily available, designing a an atomistic level. -
Practice: Quantum ESPRESSO I
MODULE 2: QUANTUM MECHANICS Practice: Quantum ESPRESSO I. What is Quantum ESPRESSO? 2 DFT software PW-DFT, PP, US-PP, PAW FREE http://www.quantum-espresso.org PW-DFT, PP, PAW FREE http://www.abinit.org DFT PW, PP, Car-Parrinello FREE http://www.cpmd.org DFT PP, US-PP, PAW $3000 [moderate accuracy, fast] http://www.vasp.at DFT full-potential linearized augmented $500 plane-wave (FLAPW) [accurate, slow] http://www.wien2k.at Hartree-Fock, higher order correlated $3000 electron approaches http://www.gaussian.com 3 Quantum ESPRESSO 4 Quantum ESPRESSO Quantum ESPRESSO is an integrated suite of Open- Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. Core set of codes, plugins for more advanced tasks and third party packages Open initiative coordinated by the Quantum ESPRESSO Foundation, across Italy. Contributed to by developers across the world Regular hands-on workshops in Trieste, Italy Open-source code: FREE (unlike VASP...) 5 Performance Small jobs (a few atoms) can be run on single node Includes determining convergence parameters, lattice constants Can use OpenMP parallelization on multicore machines Large jobs (~10’s to ~100’s atoms) can run in parallel using MPI to 1000’s of cores Includes molecular dynamics, large geometry relaxation, phonons Parallel performance tied to BLAS/LAPACK (linear algebra routines) and 3D FFT (fast Fourier transform) New GPU-enabled version available 6 Usability Documented online: -
In Quantum Chemistry
http://www.cca-forum.org Computational Quality of Service (CQoS) in Quantum Chemistry Joseph Kenny1, Kevin Huck2, Li Li3, Lois Curfman McInnes3, Heather Netzloff4, Boyana Norris3, Meng-Shiou Wu4, Alexander Gaenko4 , and Hirotoshi Mori5 1Sandia National Laboratories, 2University of Oregon, 3Argonne National Laboratory, 4Ames Laboratory, 5Ochanomizu University, Japan This work is a collaboration among participants in the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS), Performance Engineering Research Institute (PERI), Quantum Chemistry Science Application Partnership (QCSAP), and the Tuning and Analysis Utilities (TAU) group at the University of Oregon. Quantum Chemistry and the CQoS in Quantum Chemistry: Motivation and Approach Common Component Architecture (CCA) Motivation: CQoS Approach: CCA Overview: • QCSAP Challenges: How, during runtime, can we make the best choices • Overall: Develop infrastructure for dynamic component adaptivity, i.e., • The CCA Forum provides a specification and software tools for the for reliability, accuracy, and performance of interoperable quantum composing, substituting, and reconfiguring running CCA component development of high-performance components. chemistry components based on NWChem, MPQC, and GAMESS? applications in response to changing conditions – Performance, accuracy, mathematical consistency, reliability, etc. • Components = Composition – When several QC components provide the same functionality, what • Approach: Develop CQoS tools for – A component is a unit -
3D-Printing Models for Chemistry
3D-Printing Models for Chemistry: A Step-by-Step Open-Source Guide for Hobbyists, Corporate ProfessionAls, and Educators and Student in K-12 and Higher Education Poster Elisabeth Grace Billman-Benveniste+, Jacob Franz++, Loredana Valenzano-Slough+* +Department of Chemistry, Michigan Technological University, ++Department of Mechanical Engineering, Michigan Technological University *Corresponding Author References 1. “LulzBot TAZ 5.” LulzBot, 14 Aug. 2018, www.lulzbot.com/store/printers/lulzbot-taz-5 2. Gaussian 16, Revision B.01, Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A. V.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams-Young, D.; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; ZakrzeWski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; HasegaWa, J.; Ishida, M.; NakaJima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J. J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Keith, T. A.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian, Inc., Wallingford CT, 2016. 3. -
The CECAM Electronic Structure Library and the Modular Software Development Paradigm
The CECAM electronic structure library and the modular software development paradigm Cite as: J. Chem. Phys. 153, 024117 (2020); https://doi.org/10.1063/5.0012901 Submitted: 06 May 2020 . Accepted: 08 June 2020 . Published Online: 13 July 2020 Micael J. T. Oliveira , Nick Papior , Yann Pouillon , Volker Blum , Emilio Artacho , Damien Caliste , Fabiano Corsetti , Stefano de Gironcoli , Alin M. Elena , Alberto García , Víctor M. García-Suárez , Luigi Genovese , William P. Huhn , Georg Huhs , Sebastian Kokott , Emine Küçükbenli , Ask H. Larsen , Alfio Lazzaro , Irina V. Lebedeva , Yingzhou Li , David López- Durán , Pablo López-Tarifa , Martin Lüders , Miguel A. L. Marques , Jan Minar , Stephan Mohr , Arash A. Mostofi , Alan O’Cais , Mike C. Payne, Thomas Ruh, Daniel G. A. Smith , José M. Soler , David A. Strubbe , Nicolas Tancogne-Dejean , Dominic Tildesley, Marc Torrent , and Victor Wen-zhe Yu COLLECTIONS Paper published as part of the special topic on Electronic Structure Software Note: This article is part of the JCP Special Topic on Electronic Structure Software. This paper was selected as Featured ARTICLES YOU MAY BE INTERESTED IN Recent developments in the PySCF program package The Journal of Chemical Physics 153, 024109 (2020); https://doi.org/10.1063/5.0006074 An open-source coding paradigm for electronic structure calculations Scilight 2020, 291101 (2020); https://doi.org/10.1063/10.0001593 Siesta: Recent developments and applications The Journal of Chemical Physics 152, 204108 (2020); https://doi.org/10.1063/5.0005077 J. Chem. Phys. 153, 024117 (2020); https://doi.org/10.1063/5.0012901 153, 024117 © 2020 Author(s). The Journal ARTICLE of Chemical Physics scitation.org/journal/jcp The CECAM electronic structure library and the modular software development paradigm Cite as: J. -
Application Profiling at the HPCAC High Performance Center Pak Lui 157 Applications Best Practices Published
Best Practices: Application Profiling at the HPCAC High Performance Center Pak Lui 157 Applications Best Practices Published • Abaqus • COSMO • HPCC • Nekbone • RFD tNavigator • ABySS • CP2K • HPCG • NEMO • SNAP • AcuSolve • CPMD • HYCOM • NWChem • SPECFEM3D • Amber • Dacapo • ICON • Octopus • STAR-CCM+ • AMG • Desmond • Lattice QCD • OpenAtom • STAR-CD • AMR • DL-POLY • LAMMPS • OpenFOAM • VASP • ANSYS CFX • Eclipse • LS-DYNA • OpenMX • WRF • ANSYS Fluent • FLOW-3D • miniFE • OptiStruct • ANSYS Mechanical• GADGET-2 • MILC • PAM-CRASH / VPS • BQCD • Graph500 • MSC Nastran • PARATEC • BSMBench • GROMACS • MR Bayes • Pretty Fast Analysis • CAM-SE • Himeno • MM5 • PFLOTRAN • CCSM 4.0 • HIT3D • MPQC • Quantum ESPRESSO • CESM • HOOMD-blue • NAMD • RADIOSS For more information, visit: http://www.hpcadvisorycouncil.com/best_practices.php 2 35 Applications Installation Best Practices Published • Adaptive Mesh Refinement (AMR) • ESI PAM-CRASH / VPS 2013.1 • NEMO • Amber (for GPU/CUDA) • GADGET-2 • NWChem • Amber (for CPU) • GROMACS 5.1.2 • Octopus • ANSYS Fluent 15.0.7 • GROMACS 4.5.4 • OpenFOAM • ANSYS Fluent 17.1 • GROMACS 5.0.4 (GPU/CUDA) • OpenMX • BQCD • Himeno • PyFR • CASTEP 16.1 • HOOMD Blue • Quantum ESPRESSO 4.1.2 • CESM • LAMMPS • Quantum ESPRESSO 5.1.1 • CP2K • LAMMPS-KOKKOS • Quantum ESPRESSO 5.3.0 • CPMD • LS-DYNA • WRF 3.2.1 • DL-POLY 4 • MrBayes • WRF 3.8 • ESI PAM-CRASH 2015.1 • NAMD For more information, visit: http://www.hpcadvisorycouncil.com/subgroups_hpc_works.php 3 HPC Advisory Council HPC Center HPE Apollo 6000 HPE ProLiant -
High-Performance Algorithms and Software for Large-Scale Molecular Simulation
HIGH-PERFORMANCE ALGORITHMS AND SOFTWARE FOR LARGE-SCALE MOLECULAR SIMULATION A Thesis Presented to The Academic Faculty by Xing Liu In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the School of Computational Science and Engineering Georgia Institute of Technology May 2015 Copyright ⃝c 2015 by Xing Liu HIGH-PERFORMANCE ALGORITHMS AND SOFTWARE FOR LARGE-SCALE MOLECULAR SIMULATION Approved by: Professor Edmond Chow, Professor Richard Vuduc Committee Chair School of Computational Science and School of Computational Science and Engineering Engineering Georgia Institute of Technology Georgia Institute of Technology Professor Edmond Chow, Advisor Professor C. David Sherrill School of Computational Science and School of Chemistry and Biochemistry Engineering Georgia Institute of Technology Georgia Institute of Technology Professor David A. Bader Professor Jeffrey Skolnick School of Computational Science and Center for the Study of Systems Biology Engineering Georgia Institute of Technology Georgia Institute of Technology Date Approved: 10 December 2014 To my wife, Ying Huang the woman of my life. iii ACKNOWLEDGEMENTS I would like to first extend my deepest gratitude to my advisor, Dr. Edmond Chow, for his expertise, valuable time and unwavering support throughout my PhD study. I would also like to sincerely thank Dr. David A. Bader for recruiting me into Georgia Tech and inviting me to join in this interesting research area. My appreciation is extended to my committee members, Dr. Richard Vuduc, Dr. C. David Sherrill and Dr. Jeffrey Skolnick, for their advice and helpful discussions during my research. Similarly, I want to thank all of the faculty and staff in the School of Compu- tational Science and Engineering at Georgia Tech. -
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. -
Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program
Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program Start: Sunday, May 7, 2017 afternoon. Resort check-in at 4:00 pm. Finish: Wednesday, May 10, noon Lectures are in Scripps, posters are in Heather. Sunday 6:00-7:00: Dinner 7:30-9:00 Opening session 7:30–7:45 Anna Krylov (USC): “MolSSI and some lessons from previous workshop, goals of the workshop” 7:45-8:00 Theresa Windus (Iowa): “Mission of the Molecular Science Consortium” 8:00-9:00 Introduction of participants: 2 min presentation, can have one slide (send in advance) 9:00-10:30 Reception and posters Monday Breakfast: 7:30-9:00 9:00-11:45 Session I: Overview of tensors projects and current developments (moderator Daniel Smith) 9:00-9:10 Daniel Smith (MolSSI): Overview of tensor projects 9:10-9:30 Evgeny Epifanovsky (Q-Chem): Overview of Libtensor 9:30-9:50 Ed Solomonik: "An Overview of Cyclops Tensor Framework" 9:50-10:10 Ed Valeev (VT): "TiledArray: A composable massively parallel block-sparse tensor framework" 10:10-10:30 Coffee break 10:30-10:50 Devin Matthews (UT Austin): "Aquarius and TBLIS: Orthogonal Axes in Multilinear Algebra" 10:50-11:10 Karol Kowalskii (PNNL, NWChem): "NWChem, NWChemEX , and new tensor algebra systems for many-body methods" 11:10-11:30 Peng Chong (VT): "Many-body toolkit in re-designed Massively Parallel Quantum Chemistry package" 11:30-11:55 Moderated discussion: "What problems are we *still* solving?” Lunch: 12:00-1:00 Free time for unstructured discussions 5:00 Posters (coffee/tea) Dinner: 6-7:00 7:15-9:00 Session II: Computer