Natural Transition Orbital Calculations in the RASSI Module of Openmolcas Introduction
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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. -
Modern Quantum Chemistry with [Open]Molcas
Modern quantum chemistry with [Open]Molcas Cite as: J. Chem. Phys. 152, 214117 (2020); https://doi.org/10.1063/5.0004835 Submitted: 17 February 2020 . Accepted: 11 May 2020 . Published Online: 05 June 2020 Francesco Aquilante , Jochen Autschbach , Alberto Baiardi , Stefano Battaglia , Veniamin A. Borin , Liviu F. Chibotaru , Irene Conti , Luca De Vico , Mickaël Delcey , Ignacio Fdez. Galván , Nicolas Ferré , Leon Freitag , Marco Garavelli , Xuejun Gong , Stefan Knecht , Ernst D. Larsson , Roland Lindh , Marcus Lundberg , Per Åke Malmqvist , Artur Nenov , Jesper Norell , Michael Odelius , Massimo Olivucci , Thomas B. Pedersen , Laura Pedraza-González , Quan M. Phung , Kristine Pierloot , Markus Reiher , Igor Schapiro , Javier Segarra-Martí , Francesco Segatta , Luis Seijo , Saumik Sen , Dumitru-Claudiu Sergentu , Christopher J. Stein , Liviu Ungur , Morgane Vacher , Alessio Valentini , and Valera Veryazov J. Chem. Phys. 152, 214117 (2020); https://doi.org/10.1063/5.0004835 152, 214117 © 2020 Author(s). The Journal ARTICLE of Chemical Physics scitation.org/journal/jcp Modern quantum chemistry with [Open]Molcas Cite as: J. Chem. Phys. 152, 214117 (2020); doi: 10.1063/5.0004835 Submitted: 17 February 2020 • Accepted: 11 May 2020 • Published Online: 5 June 2020 Francesco Aquilante,1,a) Jochen Autschbach,2,b) Alberto Baiardi,3,c) Stefano Battaglia,4,d) Veniamin A. Borin,5,e) Liviu F. Chibotaru,6,f) Irene Conti,7,g) Luca De Vico,8,h) Mickaël Delcey,9,i) Ignacio Fdez. Galván,4,j) Nicolas Ferré,10,k) Leon Freitag,3,l) Marco Garavelli,7,m) Xuejun Gong,11,n) Stefan Knecht,3,o) Ernst D. Larsson,12,p) Roland Lindh,4,q) Marcus Lundberg,9,r) Per Åke Malmqvist,12,s) Artur Nenov,7,t) Jesper Norell,13,u) Michael Odelius,13,v) Massimo Olivucci,8,14,w) Thomas B. -
Arxiv:1911.06836V1 [Physics.Chem-Ph] 8 Aug 2019 A
Multireference electron correlation methods: Journeys along potential energy surfaces Jae Woo Park,1, ∗ Rachael Al-Saadon,2 Matthew K. MacLeod,3 Toru Shiozaki,2, 4 and Bess Vlaisavljevich5, y 1Department of Chemistry, Chungbuk National University, Chungdae-ro 1, Cheongju 28644, Korea. 2Department of Chemistry, Northwestern University, 2145 Sheridan Rd., Evanston, IL 60208, USA. 3Workday, 4900 Pearl Circle East, Suite 100, Boulder, CO 80301, USA. 4Quantum Simulation Technologies, Inc., 625 Massachusetts Ave., Cambridge, MA 02139, USA. 5Department of Chemistry, University of South Dakota, 414 E. Clark Street, Vermillion, SD 57069, USA. (Dated: November 19, 2019) Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way, and therefore, can yield accurate and predictive results even when single-reference methods or multicon- figurational self-consistent field (MCSCF) theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces (PES). This includes the optimization of molecular ge- ometries, such as equilibrium geometries and conical intersections, and on-the-fly photodynamics simulations; both depend heavily on the ability of the method to properly explore the PES. Since such applications require the nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly improves the utility of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. To motivate the readers, we first summarize the notable applications of multireference elec- tron correlation methods to mainstream chemistry, including geometry optimizations and on-the-fly dynamics. Subsequently, we review the analytical nuclear gradient and derivative coupling theories for these methods, and the software infrastructure that allows one to make use of these quantities in applications. -
A Tutorial for Theodore 2.0.2
A Tutorial for TheoDORE 2.0.2 Felix Plasser, Patrick Kimber Loughborough, 2019 Department of Chemistry – Loughborough University Contents 1 Before Starting3 1.1 Introduction . .3 1.2 Notation . .3 1.3 Installation . .3 2 Natural transition orbitals (Turbomole)4 2.1 Input generation . .4 2.2 Transition density matrix (1TDM) analysis . .5 2.3 Plotting of the orbitals . .6 3 Charge transfer number and exciton analysis (Turbomole)9 3.1 Input generation . .9 3.2 Transition density matrix (1TDM) analysis . 10 3.3 Electron-hole correlation plots . 11 4 Interface to the external cclib library (Gaussian 09) 12 4.1 Check the log file . 12 4.2 Input generation . 13 4.3 Transition density matrix (1TDM) analysis . 15 5 Advanced fragment input and double excitations (Columbus) 16 5.1 Fragment preparation using Avogadro . 17 5.2 Input generation . 18 5.3 Transition density matrix (1TDM) analysis . 19 6 Fragment decomposition for a transition metal complex 21 6.1 Input generation . 21 6.2 Transition density matrix analysis and decomposition . 23 7 Domain NTO and conditional density analysis 26 7.1 Input generation . 26 1 7.2 Transition density matrix analysis . 28 7.3 Plotting of the orbitals . 29 8 Attachment/detachment analysis (Molcas - natural orbitals) 31 8.1 Input generation . 31 8.2 State density matrix analysis . 32 8.3 Plotting of the orbitals . 33 9 Contact 34 TheoDORE tutorial 2 1 Before Starting 1.1 Introduction This tutorial is intended to provide an overview over the functionalities of the TheoDORE program package. Various tasks of different complexity are discussed using interfaces to dif- ferent quantum chemistry packages. -
Lawrence Berkeley National Laboratory Recent Work
Lawrence Berkeley National Laboratory Recent Work Title From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape. Permalink https://escholarship.org/uc/item/4sm897jh Journal Chemical reviews, 121(8) ISSN 0009-2665 Authors Kowalski, Karol Bair, Raymond Bauman, Nicholas P et al. Publication Date 2021-04-01 DOI 10.1021/acs.chemrev.0c00998 Peer reviewed eScholarship.org Powered by the California Digital Library University of California From NWChem to NWChemEx: Evolving with the computational chemistry landscape Karol Kowalski,y Raymond Bair,z Nicholas P. Bauman,y Jeffery S. Boschen,{ Eric J. Bylaska,y Jeff Daily,y Wibe A. de Jong,x Thom Dunning, Jr,y Niranjan Govind,y Robert J. Harrison,k Murat Keçeli,z Kristopher Keipert,? Sriram Krishnamoorthy,y Suraj Kumar,y Erdal Mutlu,y Bruce Palmer,y Ajay Panyala,y Bo Peng,y Ryan M. Richard,{ T. P. Straatsma,# Peter Sushko,y Edward F. Valeev,@ Marat Valiev,y Hubertus J. J. van Dam,4 Jonathan M. Waldrop,{ David B. Williams-Young,x Chao Yang,x Marcin Zalewski,y and Theresa L. Windus*,r yPacific Northwest National Laboratory, Richland, WA 99352 zArgonne National Laboratory, Lemont, IL 60439 {Ames Laboratory, Ames, IA 50011 xLawrence Berkeley National Laboratory, Berkeley, 94720 kInstitute for Advanced Computational Science, Stony Brook University, Stony Brook, NY 11794 ?NVIDIA Inc, previously Argonne National Laboratory, Lemont, IL 60439 #National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6373 @Department of Chemistry, Virginia Tech, Blacksburg, VA 24061 4Brookhaven National Laboratory, Upton, NY 11973 rDepartment of Chemistry, Iowa State University and Ames Laboratory, Ames, IA 50011 E-mail: [email protected] 1 Abstract Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. -
1 Advances in Electronic Structure Theory: Gamess a Decade Later Mark S. Gordon and Michael W. Schmidt Department of Chemistry A
ADVANCES IN ELECTRONIC STRUCTURE THEORY: GAMESS A DECADE LATER MARK S. GORDON AND MICHAEL W. SCHMIDT DEPARTMENT OF CHEMISTRY AND AMES LABORATORY, IOWA STATE UNIVERSITY, AMES, IA 50011 Abstract. Recent developments in advanced quantum chemistry and quantum chemistry interfaced with model potentials are discussed, with the primary focus on new implementations in the GAMESS electronic structure suite of programs. Applications to solvent effects and surface science are discussed. 1. Introduction The past decade has seen an extraordinary growth in novel new electronic structure methods and creative implementations of these methods. Concurrently, there have been important advances in “middleware”, software that enables the implementation of efficient electronic structure algorithms. Combined with continuing improvements in computer and interconnect hardware, these advances have extended both the accuracy of computations and the sizes of molecular systems to which such methods may be applied. The great majority of the new computational chemistry algorithms have found their way into one or more broadly distributed electronic structure packages. Since this work focuses on new features of the GAMESS (General Atomic and Molecular Electronic Structure System1) suite of codes, it is important at the outset to recognize the many other packages that offer both similar and complementary features. These include ACES2 CADPAC3, DALTON4, GAMESS-UK5, HYPERCHEM6, JAGUAR7, MOLCAS8 MOLPRO9, NWChem10, PQS11, PSI312, Q-Chem13, SPARTAN14, TURBOMOLE15, and UT-Chem16. Some1,3,4,10 of these packages are distributed at no cost to all, or to academic users, while others are commercial packages, but all are generally available to users without restriction or constraint. Indeed, the developers of these codes frequently collaborate to share features, a practice that clearly benefits all of their users. -
Computational Chemistry: a Practical Guide for Applying Techniques to Real-World Problems
Computational Chemistry: A Practical Guide for Applying Techniques to Real-World Problems. David C. Young Copyright ( 2001 John Wiley & Sons, Inc. ISBNs: 0-471-33368-9 (Hardback); 0-471-22065-5 (Electronic) COMPUTATIONAL CHEMISTRY COMPUTATIONAL CHEMISTRY A Practical Guide for Applying Techniques to Real-World Problems David C. Young Cytoclonal Pharmaceutics Inc. A JOHN WILEY & SONS, INC., PUBLICATION New York . Chichester . Weinheim . Brisbane . Singapore . Toronto Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or all capital letters. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. Copyright ( 2001 by John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including uploading, downloading, printing, decompiling, recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 605 Third Avenue, New York, NY 10158-0012, (212) 850-6011, fax (212) 850-6008, E-Mail: PERMREQ @ WILEY.COM. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional person should be sought. -
Computational Chemistry at the Petascale: Tools in the Tool Box
Computational chemistry at the petascale: tools in the tool box Robert J. Harrison [email protected] [email protected] The DOE funding • This work is funded by the U.S. Department of Energy, the division of Basic Energy Science, Office of Science, under contract DE-AC05-00OR22725 with Oak Ridge National Laboratory. This research was performed in part using – resources of the National Energy Scientific Computing Center which is supported by the Office of Energy Research of the U.S. Department of Energy under contract DE-AC03-76SF0098, – and the Center for Computational Sciences at Oak Ridge National Laboratory under contract DE-AC05-00OR22725 . Chemical Computations on Future High-end Computers Award #CHE 0626354, NSF Cyber Chemistry • NCSA (T. Dunning, PI) • U. Tennessee (Chemistry, EE/CS) • U. Illinois UC (Chemistry) • U. Pennsylvania (Chemistry) • Conventional single processor performance no longer increasing exponentially – Multi-core • Many “corners” of chemistry will increasingly be best served by non-conventional technologies – GP-GPU, FPGA, MD Grape/Wine Award No: NSF CNS-0509410 Project Title: Collaborative research: CAS-AES: An integrated framework for compile-time/run-time support for multi-scale applications on high-end systems Investigators: P. Sadayappan (PI) G. Baumgartner, D. Bernholdt, R.J. Harrison, J. Nieplocha, J. Ramanujam and A. Rountev Institution: The Ohio State University Louisiana State University University of Tennessee, Knoxville Website: Description of Graphic Image: http://www.cse.ohio-state.edu/~saday/ A tree-based algorithm (here in 1D, but in actuality in 3-12D) is naturally implemented via recursion. The data in subtrees is managed in chunks and the computation expressed very compactly. -
Modern Quantum Chemistry with [Open]Molcas
Research Collection Journal Article Modern quantum chemistry with [Open]Molcas Author(s): Aquilante, Francesco; Baiardi, Alberto; Freitag, Leon; Knecht, Stefan; Reiher, Markus; Stein, Christopher J.; et al. Publication Date: 2020-06-07 Permanent Link: https://doi.org/10.3929/ethz-b-000420242 Originally published in: The Journal of Chemical Physics 152(21), http://doi.org/10.1063/5.0004835 Rights / License: Creative Commons Attribution 4.0 International This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Modern quantum chemistry with [Open]Molcas Cite as: J. Chem. Phys. 152, 214117 (2020); https://doi.org/10.1063/5.0004835 Submitted: 17 February 2020 . Accepted: 11 May 2020 . Published Online: 05 June 2020 Francesco Aquilante , Jochen Autschbach , Alberto Baiardi , Stefano Battaglia , Veniamin A. Borin , Liviu F. Chibotaru , Irene Conti , Luca De Vico , Mickaël Delcey , Ignacio Fdez. Galván , Nicolas Ferré , Leon Freitag , Marco Garavelli , Xuejun Gong , Stefan Knecht , Ernst D. Larsson , Roland Lindh , Marcus Lundberg , Per Åke Malmqvist , Artur Nenov , Jesper Norell , Michael Odelius , Massimo Olivucci , Thomas B. Pedersen , Laura Pedraza-González , Quan M. Phung , Kristine Pierloot , Markus Reiher , Igor Schapiro , Javier Segarra-Martí , Francesco Segatta , Luis Seijo , Saumik Sen , Dumitru-Claudiu Sergentu , Christopher J. Stein , Liviu Ungur , Morgane Vacher , Alessio Valentini , and Valera Veryazov COLLECTIONS Paper published -
Clusters and Grids in Chemistry and Reinsurance Calculations
Clusters and Grids in Chemistry and Reinsurance Calculations Dr. Wibke Sudholt Project Leader, Grid Computing Team, Baldridge Group, Institute of Organic Chemistry, University of Zurich, Switzerland [email protected] http://ocikbws.uzh.ch/grid/ W. Sudholt, SOS12 12.03.2008 / 1 Overview “Average user” utilization of clusters and grids for scientific and business applications • Infrastructure building • Software porting and application • User interfaces • Focus on computation Two example domains • Quantum chemical calculations • Reinsurance natural catastrophe calculations Presentation structure • Cluster and grid infrastructures • Example background • User / application requirements • Domain-specific issues and solutions • Conclusions for HPC http://www.swissre.com/pws/research%20publications/risk%20and%20expertise/risk%20perception/natural%20catastrophes%20and%20reinsurance.html W. Sudholt, SOS12 12.03.2008 / 2 Infrastructure Characteristics Frontend node Super- Work- computers stations Clusters PCs Compute nodes Clusters / supercomputers Grids • Homogenous hardware and software • Heterogeneous hardware and software • Tightly-coupled machines • Loosely-coupled machines • Usually reliable high-speed network • Potentially unreliable low-speed network • One central location • Several distributed locations • One administrative domain • Several administrative domains • Usually secure • Potentially insecure • Resource management system (SGE, PBS, etc.) • Grid middleware (Globus, UNICORE, etc.) • Fast communication between parallel jobs • Best -
Acronyms Used in Theoretical Chemistry
Pure & Appl. Chem., Vol. 68, No. 2, pp. 387-456, 1996. Printed in Great Britain. INTERNATIONAL UNION OF PURE AND APPLIED CHEMISTRY PHYSICAL CHEMISTRY DIVISION WORKING PARTY ON THEORETICAL AND COMPUTATIONAL CHEMISTRY ACRONYMS USED IN THEORETICAL CHEMISTRY Prepared for publication by the Working Party consisting of R. D. BROWN* (Australia, Chiman);J. E. BOWS (USA); R. HILDERBRANDT (USA); K. LIM (Australia); I. M. MILLS (UK); E. NIKITIN (Russia); M. H. PALMER (UK). The focal point to which to send comments and suggestions is the coordinator of the project: RONALD D. BROWN Chemistry Department, Monash University, Clayton, Victoria 3 168, Australia. Responses by e-mail would be particularly appreciated, the number being: rdbrown @ vaxc.cc .monash.edu.au another alternative is fax at: +61 3 9905 4597 Acronyms used in theoretical chemistry synogsis An alphabetic list of acronyms used in theoretical chemistry is presented. Some explanatory references have been added to make acronyms better understandable but still more are needed. Critical comments, additional references, etc. are requested. INTRODUC'IION The IUPAC Working Party on Theoretical Chemistry was persuaded, by discussion with colleagues, that the compilation of a list of acronyms used in theoretical chemistry would be a useful contribution. Initial lists of acronyms drawn up by several members of the working party have been augmented by the provision of a substantial list by Chemical Abstract Service (see footnote below). The working party is particularly grateful to CAS for this generous help. It soon became apparent that many of the acron ms needed more than mere spelling out to make them understandable and so we have added expr anatory references to many of them. -
Openmolcas: from Source Code to Insight Ignacio Fdez
Article Cite This: J. Chem. Theory Comput. 2019, 15, 5925−5964 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 Fredérić 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. Box 538, SE-751 21 Uppsala, Sweden 2Department of Chemistry − BMC, Uppsala University, P.O.