DOCSLIB.ORG

D4.2 First Report on Code Profiling and Bottleneck Identification, Structured

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
D4.2 First Report on Code Profiling and Bottleneck Identification, Structured Ref. Ares(2019)5488775 - 30/08/2019 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities Carlo Cavazzoni, Fabio Affinito, Uliana Alekseeva, Claudia Cardoso, Augustin Degomme, Pietro Delugas, Andrea Ferretti, Alberto Garcia, Luigi Genovese, Paolo Giannozzi, Anton Kozhevnikov, Ivan Marri, Stephan Mohr, and Daniel Wortmann Due date of deliverable 31/08/2019 (month 9) Actual submission date 31/08/2019 Lead beneficiary CINECA (participant number 8) Dissemination level PU - Public http://www.max-centre.eu 1 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. Document information Project acronym MAX Project full title Materials Design at the Exascale Research Action Project type European Centre of Excellence in materials mod- elling, simulations and design EC Grant agreement no. 824143 Project starting/end date 01/12/2018 (month 1) / 30/11/2021 (month 36) Website http://www.max-centre.eu Deliverable no. D4.2 Authors Carlo Cavazzoni, Fabio Affinito, Uliana Alekseeva, Claudia Cardoso, Augustin Degomme, Pietro Del- ugas, Andrea Ferretti, Alberto Garcia, Luigi Gen- ovese, Paolo Giannozzi, Anton Kozhevnikov, Ivan Marri, Stephan Mohr, and Daniel Wortmann To be cited as C. Cavazzoni et al. (2019): First report on code pro- filing and bottleneck identification, structured plan of forward activities. Deliverable D4.2 of the H2020 CoE MAX (final version as of 30/08/2019). EC grant agreement no: 824143, CINECA, Bologna, Italy. Disclaimer This document’s contents are not intended to replace consultation of any applicable legal sources or the necessary advice of a legal expert, where appropriate. All information in this document is provided “as is” and no guarantee or warranty is given that the infor- mation is fit for any particular purpose. The user, therefore, uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission has no liability in respect of this document, which is merely representing the authors’ view. http://www.max-centre.eu 2 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. Contents 1 Executive Summary5 2 Introduction6 3 Scientific use cases6 3.1 List of scientific use cases..........................6 3.1.1 QUANTUM ESPRESSO......................6 3.1.2 Yambo............................... 11 3.1.3 FLEUR............................... 13 3.1.4 BigDFT............................... 14 3.1.5 CP2K................................ 15 3.1.6 SIESTA............................... 18 4 Profiling results, bottlenecks, and early actions 19 4.1 QUANTUM ESPRESSO.......................... 19 4.1.1 Profiling on pw.x ......................... 19 4.1.2 Profiling of pw.x on GPUs.................... 23 4.1.3 Profiling on cp.x ......................... 24 4.2 Yambo.................................... 29 4.2.1 Profiling on Yambo: the GW workflow.............. 29 4.2.2 Defective TiO2 structure: MPI and OpenMP scaling....... 30 4.2.3 Chevron-like polymer: MPI scaling................ 33 4.2.4 Intra-node profiling on Yambo: GPUs............... 33 4.3 FLEUR................................... 38 4.3.1 Performance of the FLEUR MAX Release 3........... 38 4.3.2 New data layout.......................... 40 4.4 BigDFT................................... 43 4.4.1 Uranium-dioxyde benchmarks - GPU............... 43 4.4.2 Bench Submission through AiiDA ................ 45 4.4.3 Uranium-dioxyde benchmarks - KNL............... 46 4.5 CP2K.................................... 48 4.5.1 RPA calculations with CP2K.................... 48 4.5.2 Linear scaling calculations..................... 49 4.5.3 Plane-wave pseudo potential calculations............. 50 4.6 SIESTA................................... 53 5 Structured plan of forward activities 59 5.1 QUANTUM ESPRESSO.......................... 59 5.2 Yambo.................................... 60 5.3 FLEUR................................... 61 5.4 BigDFT................................... 61 5.5 CP2K.................................... 63 5.6 SIESTA................................... 63 6 Conclusion and lessons learned 65 http://www.max-centre.eu 3 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. References 66 http://www.max-centre.eu 4 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. 1 Executive Summary This deliverable sets the baseline for the performance and scalability status towards ex- ascale of MAX applications, and at the same time identifies the key bottlenecks that currently preclude MAX codes from efficiently executing a set of selected scientific use cases on future European pre-exascale and exascale systems. It is important to remark that MAX community codes are complex objects that can be configured to run in many different ways, by changing several parameters. Moreover, the required computational resources (time, memory, I/O, etc) connected to different input datasets may span several orders of magnitude, thereby making the codes display very different computational be- haviours. Being practically impossible to explore the whole space of possible working conditions and parameters of MAX codes, we have decided to focus our effort on those parameters that are potentially blocking for scientific use cases of interest for future ex- ascale systems. We thus report on code profiling and bottleneck identification activities referring to such use cases. While this does not necessary imply that other scientific use cases may display the same bottlenecks or profiling patterns, the methodology and best practices adopted in this deliverable can be easily extended to all other use cases. Concerning the profiling, we have decided to consider the simulation wall-time as the main performance metric, since the timing of the whole workflow is what actually impacts the user perception and productivity. We have also decided that profiling and bottleneck identification in particular should be referred as much as possible to well identifiable kernels and modules (e.g.: "the code does not scale primarily because of eigenvectors orthogonalisation"), since this can help both code experts and scientists to review the applications. When a deeper analysis is needed –e.g., instruction or function- level profiling–, we have decided to get in contact with the PoP CoE, since these activities are at the core of their action and expertise. Given the evolution of HPC towards extreme heterogeneity, a relevant advancement of this Deliverable is the systematic inclusion of benchmarks on accelerated architectures. All above decisions were taken as a result of several discussions during the first months of activity, and finally reviewed in a three-day face-to-face meeting at CINECA (Bologna, IT on July 10-12, 2019) involving people from Work Packages 1, 2, 3, and 4. In this Deliverable, we report on the profiling and benchmarking campaign performed along the above lines during the first months of MAX on its six flagship codes, QUAN- TUM ESPRESSO, Yambo, FLEUR, BigDFT, CP2K, and SIESTA. Importantly, we have started to collect benchmark/profiling curated data (including the scientific datasets) in a MAX dedicated repository. On one side, this will allow code developers to automate the collection process (e.g. via AiiDA) and to follow the evolution of the code performance in time. On the other side it will make available the results to the broader community of code users. http://www.max-centre.eu 5 HORIZON2020 European Centre of Excellence Deliverable D4.2 First report on code profiling and bottleneck identification, structured plan of forward activities. 2 Introduction As defined in the description of work, WP4 is responsible for profiling and benchmarking releases of the MAX codes. This is done via a dedicated task, T4.4. The outcome of the activities of this task is functional to many other tasks of other work packages (WP1, WP2, WP3, and WP6) in order to provide feedback on identified code bottlenecks and progresses obtained in terms of performance enhancement with respect of the relevant metric (e.g. scalability, time to solution). In particular, this report provides the baseline results for the first release of the MAX flagship codes, to be used by all developers across the centre to measure the effectiveness of the solutions adopted to improve code performance. The same information will be used by other WP4 tasks to look for co-design opportunities (e.g. a bottleneck that is linked to a specific hardware feature), or justify a proof-of-concept with a new paradigm or software technology (e.g. if one of the adopted paradigm is found to be responsible for poor performances). This deliverable is organized as follows: in the first Section we report the selected scientific use cases being used to define the performance and bottleneck baseline for the different codes. The dataset for these use cases are stored in a dedicated MAX Gitlab repository1 and made available to all MAX developers to be also used in the activities of other WPs. In the second Section we report the results of the many benchmarks we have run along
Load more

Recommended publications
  • GPAW, Gpus, and LUMI
    GPAW, GPUs, and LUMI Martti Louhivuori, CSC - IT Center for Science Jussi Enkovaara GPAW 2021: Users and Developers Meeting, 2021-06-01 Outline LUMI supercomputer Brief history of GPAW with GPUs GPUs and DFT Current status Roadmap LUMI - EuroHPC system of the North Pre-exascale system with AMD CPUs and GPUs ~ 550 Pflop/s performance Half of the resources dedicated to consortium members Programming for LUMI Finland, Belgium, Czechia, MPI between nodes / GPUs Denmark, Estonia, Iceland, HIP and OpenMP for GPUs Norway, Poland, Sweden, and how to use Python with AMD Switzerland GPUs? https://www.lumi-supercomputer.eu GPAW and GPUs: history (1/2) Early proof-of-concept implementation for NVIDIA GPUs in 2012 ground state DFT and real-time TD-DFT with finite-difference basis separate version for RPA with plane-waves Hakala et al. in "Electronic Structure Calculations on Graphics Processing Units", Wiley (2016), https://doi.org/10.1002/9781118670712 PyCUDA, cuBLAS, cuFFT, custom CUDA kernels Promising performance with factor of 4-8 speedup in best cases (CPU node vs. GPU node) GPAW and GPUs: history (2/2) Code base diverged from the main branch quite a bit proof-of-concept implementation had lots of quick and dirty hacks fixes and features were pulled from other branches and patches no proper unit tests for GPU functionality active development stopped soon after publications Before development re-started, code didn't even work anymore on modern GPUs without applying a few small patches Lesson learned: try to always get new functionality to the
    [Show full text]
  • D6.1 Report on the Deployment of the Max Demonstrators and Feedback to WP1-5
    Ref. Ares(2020)2820381 - 31/05/2020 HORIZON2020 European Centre of Excellence ​ Deliverable D6.1 Report on the deployment of the MaX Demonstrators and feedback to WP1-5 D6.1 Report on the deployment of the MaX Demonstrators and feedback to WP1-5 Pablo Ordejón, Uliana Alekseeva, Stefano Baroni, Riccardo Bertossa, Miki Bonacci, Pietro Bonfà, Claudia Cardoso, Carlo Cavazzoni, Vladimir Dikan, Stefano de Gironcoli, Andrea Ferretti, Alberto García, Luigi Genovese, Federico Grasselli, Anton Kozhevnikov, Deborah Prezzi, Davide Sangalli, Joost VandeVondele, Daniele Varsano, Daniel Wortmann Due date of deliverable: 31/05/2020 Actual submission date: 31/05/2020 Final version: 31/05/2020 Lead beneficiary: ICN2 (participant number 3) Dissemination level: PU - Public www.max-centre.eu 1 HORIZON2020 European Centre of Excellence ​ Deliverable D6.1 Report on the deployment of the MaX Demonstrators and feedback to WP1-5 Document information Project acronym: MaX Project full title: Materials Design at the Exascale Research Action Project type: European Centre of Excellence in materials modelling, simulations and design EC Grant agreement no.: 824143 Project starting / end date: 01/12/2018 (month 1) / 30/11/2021 (month 36) Website: www.max-centre.eu Deliverable No.: D6.1 Authors: P. Ordejón, U. Alekseeva, S. Baroni, R. Bertossa, M. ​ Bonacci, P. Bonfà, C. Cardoso, C. Cavazzoni, V. Dikan, S. de Gironcoli, A. Ferretti, A. García, L. Genovese, F. Grasselli, A. Kozhevnikov, D. Prezzi, D. Sangalli, J. VandeVondele, D. Varsano, D. Wortmann To be cited as: Ordejón, et al., (2020): Report on the deployment of the MaX Demonstrators and feedback to WP1-5. Deliverable D6.1 of the H2020 project MaX (final version as of 31/05/2020).
    [Show full text]
  • 5 Jul 2020 (finite Non-Periodic Vs
    ELSI | An Open Infrastructure for Electronic Structure Solvers Victor Wen-zhe Yua, Carmen Camposb, William Dawsonc, Alberto Garc´ıad, Ville Havue, Ben Hourahinef, William P. Huhna, Mathias Jacqueling, Weile Jiag,h, Murat Ke¸celii, Raul Laasnera, Yingzhou Lij, Lin Ling,h, Jianfeng Luj,k,l, Jonathan Moussam, Jose E. Romanb, Alvaro´ V´azquez-Mayagoitiai, Chao Yangg, Volker Bluma,l,∗ aDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA bDepartament de Sistemes Inform`aticsi Computaci´o,Universitat Polit`ecnica de Val`encia,Val`encia,Spain cRIKEN Center for Computational Science, Kobe 650-0047, Japan dInstitut de Ci`enciade Materials de Barcelona (ICMAB-CSIC), Bellaterra E-08193, Spain eDepartment of Applied Physics, Aalto University, Aalto FI-00076, Finland fSUPA, University of Strathclyde, Glasgow G4 0NG, UK gComputational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA hDepartment of Mathematics, University of California, Berkeley, CA 94720, USA iComputational Science Division, Argonne National Laboratory, Argonne, IL 60439, USA jDepartment of Mathematics, Duke University, Durham, NC 27708, USA kDepartment of Physics, Duke University, Durham, NC 27708, USA lDepartment of Chemistry, Duke University, Durham, NC 27708, USA mMolecular Sciences Software Institute, Blacksburg, VA 24060, USA Abstract Routine applications of electronic structure theory to molecules and peri- odic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries arXiv:1912.13403v3 [physics.comp-ph] 5 Jul 2020 (finite non-periodic vs.
    [Show full text]
  • D7.2 Second Report on the Activity of the High-Level Support Services (Second Year)
    Ref. Ares(2020)7219471 - 30/11/2020 HORIZON2020 European Centre of Excellence ​ ​ Deliverable D7.2 Second report on the activity of the High-Level Support services (second year) D7.2 Second report on the activity of the High-Level Support services (second year) Mariella Ippolito, Francisco Ramirez, Giovanni Pizzi, and Elsa Passaro ​ ​ Due date of deliverable: 30/11/2020 Actual submission date: 30/11/2020 Final version: 30/11/2020 Lead beneficiary: CINECA (participant number 8) Dissemination level: PU - Public www.max-centre.eu 1 HORIZON2020 European Centre of Excellence ​ ​ Deliverable D7.2 Second report on the activity of the High-Level Support services (second year) Document information Project acronym: MaX Project full title: Materials Design at the Exascale Research Action Project type: European Centre of Excellence in materials modelling, simulations and design EC Grant agreement no.: 824143 Project starting / end date: 01/12/2018 (month 1) / 30/11/2021 (month 36) Website: www.max-centre.eu Deliverable No.: D7.2 Authors: M. Ippolito, F. Ramirez, G. Pizzi, and E. Passaro To be cited as: M. Ippolito et al., (2020): Second report on the activity of the High-Level Support services (second year). Deliverable D7.2 of the H2020 project MaX (final version as of 30/11/2020). EC grant agreement no: 824143, CINECA, Bologna, Italy. Disclaimer: This document’s contents are not intended to replace consultation of any applicable legal sources or the necessary advice of a legal expert, where appropriate. All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.
    [Show full text]
  • 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.
    [Show full text]
  • Improvements of Bigdft Code in Modern HPC Architectures
    Available on-line at www.prace-ri.eu Partnership for Advanced Computing in Europe Improvements of BigDFT code in modern HPC architectures Luigi Genovesea;b;∗, Brice Videaua, Thierry Deutscha, Huan Tranc, Stefan Goedeckerc aLaboratoire de Simulation Atomistique, SP2M/INAC/CEA, 17 Av. des Martyrs, 38054 Grenoble, France bEuropean Synchrotron Radiation Facility, 6 rue Horowitz, BP 220, 38043 Grenoble, France cInstitut f¨urPhysik, Universit¨atBasel, Klingelbergstr.82, 4056 Basel, Switzerland Abstract Electronic structure calculations (DFT codes) are certainly among the disciplines for which an increasing of the computa- tional power correspond to an advancement in the scientific results. In this report, we present the ongoing advancements of DFT code that can run on massively parallel, hybrid and heterogeneous CPU-GPU clusters. This DFT code, named BigDFT, is delivered within the GNU-GPL license either in a stand-alone version or integrated in the ABINIT software package. Hybrid BigDFT routines were initially ported with NVidia's CUDA language, and recently more functionalities have been added with new routines writeen within Kronos' OpenCL standard. The formalism of this code is based on Daubechies wavelets, which is a systematic real-space based basis set. The properties of this basis set are well suited for an extension on a GPU-accelerated environment. In addition to focusing on the performances of the MPI and OpenMP parallelisation the BigDFT code, this presentation also relies of the usage of the GPU resources in a complex code with different kinds of operations. A discussion on the interest of present and expected performances of Hybrid architectures computation in the framework of electronic structure calculations is also adressed.
    [Show full text]
  • 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.
    [Show full text]
  • Introduction to DFT and the Plane-Wave Pseudopotential Method
    Introduction to DFT and the plane-wave pseudopotential method Keith Refson STFC Rutherford Appleton Laboratory Chilton, Didcot, OXON OX11 0QX 23 Apr 2014 Parallel Materials Modelling Packages @ EPCC 1 / 55 Introduction Synopsis Motivation Some ab initio codes Quantum-mechanical approaches Density Functional Theory Electronic Structure of Condensed Phases Total-energy calculations Introduction Basis sets Plane-waves and Pseudopotentials How to solve the equations Parallel Materials Modelling Packages @ EPCC 2 / 55 Synopsis Introduction A guided tour inside the “black box” of ab-initio simulation. Synopsis • Motivation • The rise of quantum-mechanical simulations. Some ab initio codes Wavefunction-based theory • Density-functional theory (DFT) Quantum-mechanical • approaches Quantum theory in periodic boundaries • Plane-wave and other basis sets Density Functional • Theory SCF solvers • Molecular Dynamics Electronic Structure of Condensed Phases Recommended Reading and Further Study Total-energy calculations • Basis sets Jorge Kohanoff Electronic Structure Calculations for Solids and Molecules, Plane-waves and Theory and Computational Methods, Cambridge, ISBN-13: 9780521815918 Pseudopotentials • Dominik Marx, J¨urg Hutter Ab Initio Molecular Dynamics: Basic Theory and How to solve the Advanced Methods Cambridge University Press, ISBN: 0521898633 equations • Richard M. Martin Electronic Structure: Basic Theory and Practical Methods: Basic Theory and Practical Density Functional Approaches Vol 1 Cambridge University Press, ISBN: 0521782856
    [Show full text]
  • 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 SoftwareESS2020 This paper was selected as Featured This paper was selected as Scilight 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 Electronic structure software The Journal of Chemical Physics 153, 070401 (2020); https://doi.org/10.1063/5.0023185 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.
    [Show full text]
  • Arxiv:2005.05756V2
    “This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Oliveira, M.J.T. [et al.]. The CECAM electronic structure library and the modular software development paradigm. "The Journal of Chemical Physics", 12020, vol. 153, núm. 2, and may be found at https://aip.scitation.org/doi/10.1063/5.0012901. The CECAM Electronic Structure Library and the modular software development paradigm Micael J. T. Oliveira,1, a) Nick Papior,2, b) Yann Pouillon,3, 4, c) Volker Blum,5, 6 Emilio Artacho,7, 8, 9 Damien Caliste,10 Fabiano Corsetti,11, 12 Stefano de Gironcoli,13 Alin M. Elena,14 Alberto Garc´ıa,15 V´ıctor M. Garc´ıa-Su´arez,16 Luigi Genovese,10 William P. Huhn,5 Georg Huhs,17 Sebastian Kokott,18 Emine K¨u¸c¨ukbenli,13, 19 Ask H. Larsen,20, 4 Alfio Lazzaro,21 Irina V. Lebedeva,22 Yingzhou Li,23 David L´opez-Dur´an,22 Pablo L´opez-Tarifa,24 Martin L¨uders,1, 14 Miguel A. L. Marques,25 Jan Minar,26 Stephan Mohr,17 Arash A. Mostofi,11 Alan O'Cais,27 Mike C. Payne,9 Thomas Ruh,28 Daniel G. A. Smith,29 Jos´eM. Soler,30 David A. Strubbe,31 Nicolas Tancogne-Dejean,1 Dominic Tildesley,32 Marc Torrent,33, 34 and Victor Wen-zhe Yu5 1)Max Planck Institute for the Structure and Dynamics of Matter, D-22761 Hamburg, Germany 2)DTU Computing Center, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark 3)Departamento CITIMAC, Universidad de Cantabria, Santander, Spain 4)Simune Atomistics, 20018 San Sebasti´an,Spain 5)Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA 6)Department of Chemistry, Duke University, Durham, NC 27708, USA 7)CIC Nanogune BRTA and DIPC, 20018 San Sebasti´an,Spain 8)Ikerbasque, Basque Foundation for Science, 48011 Bilbao, Spain 9)Theory of Condensed Matter, Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE, United Kingdom 10)Department of Physics, IRIG, Univ.
    [Show full text]
  • (DFT) and Its Application to Defects in Semiconductors
    Introduction to DFT and its Application to Defects in Semiconductors Noa Marom Physics and Engineering Physics Tulane University New Orleans The Future: Computer-Aided Materials Design • Can access the space of materials not experimentally known • Can scan through structures and compositions faster than is possible experimentally • Unbiased search can yield unintuitive solutions • Can accelerate the discovery and deployment of new materials Accurate electronic structure methods Efficient search algorithms Dirac’s Challenge “The underlying physical laws necessary for the mathematical theory of a large part of physics and the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble. It therefore becomes desirable that approximate practical methods of applying quantum mechanics should be developed, which can lead to an P. A. M. Dirac explanation of the main features of Physics Nobel complex atomic systems ... ” Prize, 1933 -P. A. M. Dirac, 1929 The Many (Many, Many) Body Problem Schrödinger’s Equation: The physical laws are completely known But… There are as many electrons in a penny as stars in the known universe! Electronic Structure Methods for Materials Properties Structure Ionization potential (IP) Absorption Mechanical Electron Affinity (EA) spectrum properties Fundamental gap Optical gap Vibrational Defect/dopant charge Exciton binding spectrum transition levels energy Ground State Charged Excitation Neutral Excitation DFT
    [Show full text]
  • Package Name Software Description Project
    A S T 1 Package Name Software Description Project URL 2 Autoconf An extensible package of M4 macros that produce shell scripts to automatically configure software source code packages https://www.gnu.org/software/autoconf/ 3 Automake www.gnu.org/software/automake 4 Libtool www.gnu.org/software/libtool 5 bamtools BamTools: a C++ API for reading/writing BAM files. https://github.com/pezmaster31/bamtools 6 Biopython (Python module) Biopython is a set of freely available tools for biological computation written in Python by an international team of developers www.biopython.org/ 7 blas The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. http://www.netlib.org/blas/ 8 boost Boost provides free peer-reviewed portable C++ source libraries. http://www.boost.org 9 CMake Cross-platform, open-source build system. CMake is a family of tools designed to build, test and package software http://www.cmake.org/ 10 Cython (Python module) The Cython compiler for writing C extensions for the Python language https://www.python.org/ 11 Doxygen http://www.doxygen.org/ FFmpeg is the leading multimedia framework, able to decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. It supports the most obscure ancient formats up to the cutting edge. No matter if they were designed by some standards 12 ffmpeg committee, the community or a corporation. https://www.ffmpeg.org FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and 13 fftw complex data (as well as of even/odd data, i.e.
    [Show full text]