MADNESS

Last updated
MADNESS
Original author(s) George Fann, Robert J. Harrison
Developer(s) Oak Ridge National Laboratory, Stony Brook University, Virginia Tech, Argonne National Laboratory
Initial releaseForthcoming
Stable release
0.10 [1] / 6 July 2015;8 years ago (6 July 2015)
Repository
Type Scientific simulation software
License GNU GPL v2
Website github.com/m-a-d-n-e-s-s/madness

MADNESS (Multiresolution Adaptive Numerical Environment for Scientific Simulation) is a high-level software environment for the solution of integral and differential equations in many dimensions using adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis [2] [3] and separated representations . [4]

Contents

There are three main components to MADNESS. At the lowest level is a petascale parallel programming environment [5] that aims to increases programmer productivity and code performance/scalability while maintaining backward compatibility with current programming tools such as the message-passing interface and Global Arrays. The numerical capabilities built upon the parallel tools provide a high-level environment for composing and solving numerical problems in many (1-6+) dimensions. Finally, built upon the numerical tools are new applications with initial focus upon chemistry, [6] [7] , atomic and molecular physics, [8] material science, and nuclear structure. It is open-source, has an object-oriented design, and is designed to be a parallel processing program for computers with up to millions of cores running already on the Cray XT5 at Oak Ridge National Laboratory and the IBM Blue Gene at Argonne National Laboratory. The small matrix multiplication (relative to large, BLAS-optimized matrices) is the primary computational kernel in MADNESS; thus, an efficient implement on modern CPUs is an ongoing research effort. [9] . [10] Adapting the irregular computation in MADNESS to heterogeneous platforms is nontrivial due to the size of the kernel, which is too small to be offloaded via compiler directives (e.g. OpenACC), but has been demonstrated for CPU – GPU systems . [11] Intel has publicly stated that MADNESS is one of the codes running on the Intel MIC architecture [12] [13] but no performance data has been published yet.

MADNESS' chemistry capability includes Hartree–Fock and density functional theory in chemistry [14] [15] (including analytic derivatives, [16] response properties [17] and time-dependent density functional theory with asymptotically corrected potentials [18] ) as well as nuclear density functional theory [19] and Hartree–Fock – Bogoliubov theory. [20] [21] MADNESS and BigDFT are the two most widely known codes that perform DFT and TDDFT using wavelets . [22] Many-body wavefunctions requiring six-dimensional spatial representations are also implemented (e.g. MP2 [23] ). The parallel runtime inside of MADNESS has been used to implement a wide variety of features, including graph optimization . [24] From a mathematical perspective, MADNESS emphasizes rigorous numerical precision without loss of computational performance . [25] This is useful not only in quantum chemistry and nuclear physics, but also the modeling of partial differential equations . [26]

MADNESS was recognized by the R&D 100 Awards in 2011. [27] [28] It is an important code to Department of Energy supercomputing sites and is being used by both the leadership computing facilities at Argonne National Laboratory [29] and Oak Ridge National Laboratory [30] to evaluate the stability and performance of their latest supercomputers. It has users around the world, including the United States and Japan . [31] MADNESS has been a workhorse code for computational chemistry in the DOE INCITE program [32] at the Oak Ridge Leadership Computing Facility [33] and is noted as one of the important codes to run on the Cray Cascade architecture. [34]

See also

Related Research Articles

Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into computer programs, to calculate the structures and properties of molecules, groups of molecules, and solids. It is essential because, apart from relatively recent results concerning the hydrogen molecular ion, the quantum many-body problem cannot be solved analytically, much less in closed form. While computational results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials.

Quantum chemistry, also called molecular quantum mechanics, is a branch of physical chemistry focused on the application of quantum mechanics to chemical systems, particularly towards the quantum-mechanical calculation of electronic contributions to physical and chemical properties of molecules, materials, and solutions at the atomic level. These calculations include systematically applied approximations intended to make calculations computationally feasible while still capturing as much information about important contributions to the computed wave functions as well as to observable properties such as structures, spectra, and thermodynamic properties. Quantum chemistry is also concerned with the computation of quantum effects on molecular dynamics and chemical kinetics.

Gaussian is a general purpose computational chemistry software package initially released in 1970 by John Pople and his research group at Carnegie Mellon University as Gaussian 70. It has been continuously updated since then. The name originates from Pople's use of Gaussian orbitals to speed up molecular electronic structure calculations as opposed to using Slater-type orbitals, a choice made to improve performance on the limited computing capacities of then-current computer hardware for Hartree–Fock calculations. The current version of the program is Gaussian 16. Originally available through the Quantum Chemistry Program Exchange, it was later licensed out of Carnegie Mellon University, and since 1987 has been developed and licensed by Gaussian, Inc.

Q-Chem is a general-purpose electronic structure package featuring a variety of established and new methods implemented using innovative algorithms that enable fast calculations of large systems on various computer architectures, from laptops and regular lab workstations to midsize clusters and HPCC, using density functional and wave-function based approaches. It offers an integrated graphical interface and input generator; a large selection of functionals and correlation methods, including methods for electronically excited states and open-shell systems; solvation models; and wave-function analysis tools. In addition to serving the computational chemistry community, Q-Chem also provides a versatile code development platform.

Psi is an ab initio computational chemistry package originally written by the research group of Henry F. Schaefer, III. Utilizing Psi, one can perform a calculation on a molecular system with various kinds of methods such as Hartree-Fock, Post-Hartree–Fock electron correlation methods, and density functional theory. The program can compute energies, optimize molecular geometries, and compute vibrational frequencies. The major part of the program is written in C++, while Python API is also available, which allows users to perform complex computations or automate tasks easily.

NWChem is an ab initio computational chemistry software package which includes quantum chemical and molecular dynamics functionality. It was designed to run on high-performance parallel supercomputers as well as conventional workstation clusters. It aims to be scalable both in its ability to treat large problems efficiently, and in its usage of available parallel computing resources. NWChem has been developed by the Molecular Sciences Software group of the Theory, Modeling & Simulation program of the Environmental Molecular Sciences Laboratory (EMSL) at the Pacific Northwest National Laboratory (PNNL). The early implementation was funded by the EMSL Construction Project.

Møller–Plesset perturbation theory (MP) is one of several quantum chemistry post–Hartree–Fock ab initio methods in the field of computational chemistry. It improves on the Hartree–Fock method by adding electron correlation effects by means of Rayleigh–Schrödinger perturbation theory (RS-PT), usually to second (MP2), third (MP3) or fourth (MP4) order. Its main idea was published as early as 1934 by Christian Møller and Milton S. Plesset.

Per-Olov Löwdin was a Swedish physicist, professor at the University of Uppsala from 1960 to 1983, and in parallel at the University of Florida until 1993.

In computational chemistry, post–Hartree–Fock (post-HF) methods are the set of methods developed to improve on the Hartree–Fock (HF), or self-consistent field (SCF) method. They add electron correlation which is a more accurate way of including the repulsions between electrons than in the Hartree–Fock method where repulsions are only averaged.

Koopmans' theorem states that in closed-shell Hartree–Fock theory (HF), the first ionization energy of a molecular system is equal to the negative of the orbital energy of the highest occupied molecular orbital (HOMO). This theorem is named after Tjalling Koopmans, who published this result in 1934.

<span class="mw-page-title-main">Nicholas C. Handy</span> British chemist

Nicholas Charles Handy was a British theoretical chemist. He retired as Professor of quantum chemistry at the University of Cambridge in September 2004.

Jaguar is a computer software package used for ab initio quantum chemistry calculations for both gas and solution phases. It is commercial software marketed by the company Schrödinger. The program was originated in research groups of Richard Friesner and William Goddard and was initially called PS-GVB.

<span class="mw-page-title-main">Spartan (chemistry software)</span>

Spartan is a molecular modelling and computational chemistry application from Wavefunction. It contains code for molecular mechanics, semi-empirical methods, ab initio models, density functional models, post-Hartree–Fock models, and thermochemical recipes including G3(MP2) and T1. Quantum chemistry calculations in Spartan are powered by Q-Chem.

Semi-empirical quantum chemistry methods are based on the Hartree–Fock formalism, but make many approximations and obtain some parameters from empirical data. They are very important in computational chemistry for treating large molecules where the full Hartree–Fock method without the approximations is too expensive. The use of empirical parameters appears to allow some inclusion of electron correlation effects into the methods.

Ab initio quantum chemistry methods are computational chemistry methods based on quantum chemistry. The term ab initio was first used in quantum chemistry by Robert Parr and coworkers, including David Craig in a semiempirical study on the excited states of benzene. The background is described by Parr. Ab initio means "from first principles" or "from the beginning", implying that the only inputs into an ab initio calculation are physical constants. Ab initio quantum chemistry methods attempt to solve the electronic Schrödinger equation given the positions of the nuclei and the number of electrons in order to yield useful information such as electron densities, energies and other properties of the system. The ability to run these calculations has enabled theoretical chemists to solve a range of problems and their importance is highlighted by the awarding of the Nobel prize to John Pople and Walter Kohn.

In computational chemistry, spin contamination is the artificial mixing of different electronic spin-states. This can occur when an approximate orbital-based wave function is represented in an unrestricted form – that is, when the spatial parts of α and β spin-orbitals are permitted to differ. Approximate wave functions with a high degree of spin contamination are undesirable. In particular, they are not eigenfunctions of the total spin-squared operator, Ŝ2, but can formally be expanded in terms of pure spin states of higher multiplicities.

<span class="mw-page-title-main">CP2K</span>

CP2K is a freely available (GPL) quantum chemistry and solid state physics program package, written in Fortran 2008, to perform atomistic simulations of solid state, liquid, molecular, periodic, material, crystal, and biological systems. It provides a general framework for different methods: density functional theory (DFT) using a mixed Gaussian and plane waves approach (GPW) via LDA, GGA, MP2, or RPA levels of theory, classical pair and many-body potentials, semi-empirical and tight-binding Hamiltonians, as well as Quantum Mechanics/Molecular Mechanics (QM/MM) hybrid schemes relying on the Gaussian Expansion of the Electrostatic Potential (GEEP). The Gaussian and Augmented Plane Waves method (GAPW) as an extension of the GPW method allows for all-electron calculations. CP2K can do simulations of molecular dynamics, metadynamics, Monte Carlo, Ehrenfest dynamics, vibrational analysis, core level spectroscopy, energy minimization, and transition state optimization using NEB or dimer method.

In computer software, FreeON is an experimental, open source (GPL) suite of programs for linear scaling quantum chemistry, formerly known as MondoSCF. It is highly modular, and has been written from scratch for N-scaling SCF theory in Fortran95 and C. Platform independent IO is supported with HDF5. FreeON should compile with most modern Linux distributions. FreeON performs Hartree–Fock, pure density functional, and hybrid HF/DFT calculations in a Cartesian-Gaussian LCAO basis. All algorithms are O(N) or O(N lg N) for non-metallic systems. Periodic boundary conditions in 1, 2 and 3 dimensions have been implemented through the Lorentz field, and an internal coordinate geometry optimizer allows full (atom+cell) relaxation using analytic derivatives. Effective core potentials for energies and forces have been implemented, but Effective Core Potential (ECP) lattice forces do not work yet. Advanced features include O(N) static and dynamic response, as well as time reversible Born Oppenheimer Molecular Dynamics (MD).

Robert J. Harrison is a distinguished expert in high-performance computing. He is a professor in the Applied Mathematics and Statistics department and founding Director of the Institute for Advanced Computational Science at Stony Brook University with a $20M endowment. Through a joint appointment with Brookhaven National Laboratory, Professor Harrison has also been named Director of the Computational Science Center and New York Center for Computational Sciences at Brookhaven. Dr. Harrison comes to Stony Brook from the University of Tennessee and Oak Ridge National Laboratory, where he was Director of the Joint Institute of Computational Science, Professor of Chemistry and Corporate Fellow. He has a prolific career in high-performance computing with over one hundred publications on the subject, as well as extensive service on national advisory committees.

References

  1. ↑ "Release 0.10". 6 July 2015. Retrieved 14 March 2018.
  2. ↑ Beylkin, Gregory; Fann, George; Harrison, Robert J.; Kurcz, Christopher; Monzón, Lucas (2012). "Multiresolution representation of operators with boundary conditions on simple domains". Applied and Computational Harmonic Analysis. 33 (1): 109–139. doi: 10.1016/j.acha.2011.10.001 .
  3. ↑ Fann, George; Beylkin, Gregory; Harrison, Robert J.; Jordan, Kirk E. (2004). "Singular operators in multiwavelet bases". IBM Journal of Research and Development. 48 (2): 161–171. doi:10.1147/rd.482.0161. S2CID   7385463.
  4. ↑ Beylkin, Gregory; Cramer, Robert; Fann, George; Harrison, Robert J. (2007). "Multiresolution separated representations of singular and weakly singular operators". Applied and Computational Harmonic Analysis. 23 (2): 235–253. doi: 10.1016/j.acha.2007.01.001 .
  5. ↑ Thornton, W. Scott; Vence, Nicholas; Harrison, Robert E. (2009). "Introducing the MADNESS numerical framework for petascale computing" (PDF). Proceedings of the Cray User Group Conference.
  6. ↑ Fosso-Tande, Jacob; Harrison, Robert (2013). "Implicit solvation models in a multiresolution multiwavelet basis". Chemical Physics Letters. 561–562: 179–184. Bibcode:2013CPL...561..179F. doi:10.1016/j.cplett.2013.01.065.
  7. ↑ Fosso-Tande, Jacob; Harrison, Robert (2013). "Confinement effects of solvation on a molecule physisorbed on a polarizable continuum particle". Computational and Theoretical Chemistry. 1017: 22–30. doi:10.1016/j.comptc.2013.05.006.
  8. ↑ Vence, Nicholas; Harrison, Robert; Krstic, Predrag (2012). "Attosecond electron dynamics: A multiresolution approach". Physical Review A. 85 (3): 0303403. Bibcode:2012PhRvA..85c3403V. doi: 10.1103/PhysRevA.85.033403 .
  9. ↑ Stock, Kevin; Henretty, Thomas; Murugandi, I.; Sadayappan, P.; Harrison, Robert J. (2011). "Model-Driven SIMD Code Generation for a Multi-resolution Tensor Kernel". 2011 IEEE International Parallel & Distributed Processing Symposium. pp. 1058–1067. doi:10.1109/IPDPS.2011.101. ISBN   978-1-61284-372-8. S2CID   17880870.
  10. ↑ Shin, Jaewook; Hall, Mary W.; Chame, Jacqueline; Chen, Chun; Hovland, Paul D. (2009). "Autotuning and specialization: Speeding up matrix multiply for small matrices with compiler technology" (PDF). Proceedings of the Fourth International Workshop on Automatic Performance Tuning.[ permanent dead link ]
  11. ↑ Slavici, Vlad; Varier, Raghu; Cooperman, Gene; Harrison, Robert J. (September 2012). "Adapting Irregular Computations to Large CPU-GPU Clusters in the MADNESS Framework". 2012 IEEE International Conference on Cluster Computing (PDF). pp. 1–9. doi:10.1109/CLUSTER.2012.42. ISBN   978-0-7695-4807-4. S2CID   5637880.
  12. ↑ James Reinders (20 September 2012). "Intel Xeon Phi coprocessor support by software tools".
  13. ↑ Timothy Prickett Morgan (16 November 2011). "Hot Intel teraflops MIC coprocessor action in a hotel". The Register .
  14. ↑ Harrison, Robert J.; Fann, George I.; Yanai, Takeshi; Gan, Zhengting; Beylkin, Gregory (2004). "Multiresolution quantum chemistry: Basic theory and initial applications". The Journal of Chemical Physics. 121 (23): 11587–11598. Bibcode:2004JChPh.12111587H. doi:10.1063/1.1791051. PMID   15634124. Archived from the original on 2013-02-23. Retrieved 2019-05-15.
  15. ↑ Yanai, Takeshi; George I., Fann; Gan, Zhengting; Harrison, Robert J.; Beylkin, Gregory (2004). "Multiresolution quantum chemistry: Hartree-Fock exchange". The Journal of Chemical Physics. 121 (14): 6680–6688. Bibcode:2004JChPh.121.6680Y. doi:10.1063/1.1790931. PMID   15473723. Archived from the original on 2013-02-24. Retrieved 2019-05-15.
  16. ↑ Yanai, Takeshi; George I., Fann; Gan, Zhengting; Harrison, Robert J.; Beylkin, Gregory (2004). "Multiresolution quantum chemistry: Analytic derivatives for Hartree--Fock and density functional theory". The Journal of Chemical Physics. 121 (7): 2866–2876. Bibcode:2004JChPh.121.2866Y. doi:10.1063/1.1768161. PMID   15291596. Archived from the original on 2013-02-23. Retrieved 2019-05-15.
  17. ↑ Sekino, Hideo; Maeda, Yasuyuki; Yanai, Takeshi; Harrison, Robert J. (2008). "Basis set limit Hartree--Fock and density functional theory response property evaluation by multiresolution multiwavelet basis". The Journal of Chemical Physics. 129 (3): 034111–034117. Bibcode:2008JChPh.129c4111S. doi:10.1063/1.2955730. PMID   18647020. Archived from the original on 2013-02-23. Retrieved 2019-05-15.
  18. ↑ Yanai, Takeshi; Harrison, Robert J.; Handy, Nicholas C. (2005). "Multiresolution quantum chemistry in multiwavelet bases: time-dependent density functional theory with asymptotically corrected potentials in local density and generalized gradient approximations". Molecular Physics. 103 (2–3): 413–424. Bibcode:2005MolPh.103..413Y. doi:10.1080/00268970412331319236. S2CID   96910088.
  19. ↑ "UNEDF SciDAC Collaboration Universal Nuclear Energy Density Functional". Archived from the original on 2013-04-03. Retrieved 2012-11-19.
  20. ↑ Pei, J.C.; Fann, G.I.; Harrison, R.J.; Nazarewicz, W.; Hill, J.; Galindo, D.; Jia, J. (2012). "Coordinate-Space Hartree-Fock-Bogoliubov Solvers for Superfluid Fermi Systems in Large Boxes". Journal of Physics: Conference Series. 402 (1): 012035. arXiv: 1204.5254 . Bibcode:2012JPhCS.402a2035P. doi:10.1088/1742-6596/402/1/012035. S2CID   119215739.
  21. ↑ Pei, J. C.; Stoitsov, M. V.; Fann, G. I.; Nazarewicz, W.; Schunck, N.; Xu, F. R. (December 2008). "Deformed coordinate-space Hartree-Fock-Bogoliubov approach to weakly bound nuclei and large deformations". Physical Review C. 78 (6): 064306–064317. arXiv: 0807.3036 . Bibcode:2008PhRvC..78f4306P. doi:10.1103/PhysRevC.78.064306. S2CID   119281109.
  22. ↑ Natarajan, Bhaarathi; Genovese, Luigi; Casida, Mark E.; Deutsch, Thierry; Burchak, Olga N.; Philouze, Christian; Balakirev, Maxim Y. (2012). "Wavelet-based linear-response time-dependent density-functional theory". Chemical Physics. 402: 29–40. arXiv: 1108.3475 . Bibcode:2012CP....402...29N. doi:10.1016/j.chemphys.2012.03.024. S2CID   96589229.
  23. ↑ Bischoff, Florian A.; Harrison, Robert J.; Valeev, Edward F. (2012). "Computing many-body wave functions with guaranteed precision: The first-order Moller-Plesset wave function for the ground state of helium atom". The Journal of Chemical Physics. 137 (10): 104103–104112. Bibcode:2012JChPh.137j4103B. doi:10.1063/1.4747538. PMID   22979846. Archived from the original on 2013-02-23. Retrieved 2019-05-15.
  24. ↑ Sullivan, Blair D.; Weerapurage, Dinesh P.; Groer, Christopher S. (2012). Parallel Algorithms for Graph Optimization using Tree Decompositions (Technical report). doi:10.2172/1042920.
  25. ↑ Harrison, Robert J.; Fann, George I. (2007). "SPEED and PRECISION in QUANTUM CHEMISTRY". SciDAC Review. 1 (3): 54–65. Archived from the original on 2012-08-03. Retrieved 2012-11-19.
  26. ↑ Reuter, Matthew G.; Hill, Judith C.; Harrison, Robert J. (2012). "Solving PDEs in irregular geometries with multiresolution methods I: Embedded Dirichlet boundary conditions". Computer Physics Communications. 183 (1): 1–7. Bibcode:2012CoPhC.183....1R. doi:10.1016/j.cpc.2011.07.001.
  27. ↑ "Free framework for scientific simulation". R&D Magazine . 14 August 2011. Retrieved November 26, 2012.
  28. ↑ "MADNESS Named R&D 100 Winner".
  29. ↑ "Accurate Numerical Simulations Of Chemical Phenomena Involved in Energy Production and Storage with MADNESS and MPQC".
  30. ↑ "Application Readiness at ORNL" (PDF).
  31. ↑ "Far from home - Japanese graduate student journeys to UT to study computational chemistry". Archived from the original on 2012-12-15.
  32. ↑ "Chemistry and Materials Simulations Speed Clean Energy Production and Storage". 1 June 2011. Archived from the original on 6 August 2011.
  33. ↑ Bland, A.; Kendall, R.; Kothe, D.; Rogers, J.; Shipman, G. (2010). "Jaguar: The world's most powerful computer" (PDF). Proceedings of the Cray User Group Conference. Archived from the original (PDF) on 2012-12-24.
  34. ↑ "Cray unveils 100 petaflop XC30 supercomputer". 8 November 2012.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.