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Sattasathuchana T, Xu P, Bertoni C, Kim YL, Leang SS, Pham BQ, Gordon MS. The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems. J Chem Theory Comput 2024; 20:2445-2461. [PMID: 38450638 DOI: 10.1021/acs.jctc.3c01309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree-Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. The accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, Rcut. Rcut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small Rcut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.
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Affiliation(s)
- Tosaporn Sattasathuchana
- Department of Chemistry, Iowa State University and Ames National Laboratory, Ames, Iowa 50011, United States
| | - Peng Xu
- Department of Chemistry, Iowa State University and Ames National Laboratory, Ames, Iowa 50011, United States
| | - Colleen Bertoni
- Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Yu Lim Kim
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Sarom S Leang
- EP Analytics, Inc., 9909 Mira Mesa Blvd Ste. 230, San Diego, California 92131, United States
| | - Buu Q Pham
- Department of Chemistry, Iowa State University and Ames National Laboratory, Ames, Iowa 50011, United States
| | - Mark S Gordon
- Department of Chemistry, Iowa State University and Ames National Laboratory, Ames, Iowa 50011, United States
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2
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Zahariev F, Xu P, Westheimer BM, Webb S, Galvez Vallejo J, Tiwari A, Sundriyal V, Sosonkina M, Shen J, Schoendorff G, Schlinsog M, Sattasathuchana T, Ruedenberg K, Roskop LB, Rendell AP, Poole D, Piecuch P, Pham BQ, Mironov V, Mato J, Leonard S, Leang SS, Ivanic J, Hayes J, Harville T, Gururangan K, Guidez E, Gerasimov IS, Friedl C, Ferreras KN, Elliott G, Datta D, Cruz DDA, Carrington L, Bertoni C, Barca GMJ, Alkan M, Gordon MS. The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures. J Chem Theory Comput 2023; 19:7031-7055. [PMID: 37793073 DOI: 10.1021/acs.jctc.3c00379] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
The primary focus of GAMESS over the last 5 years has been the development of new high-performance codes that are able to take effective and efficient advantage of the most advanced computer architectures, both CPU and accelerators. These efforts include employing density fitting and fragmentation methods to reduce the high scaling of well-correlated (e.g., coupled-cluster) methods as well as developing novel codes that can take optimal advantage of graphical processing units and other modern accelerators. Because accurate wave functions can be very complex, an important new functionality in GAMESS is the quasi-atomic orbital analysis, an unbiased approach to the understanding of covalent bonds embedded in the wave function. Best practices for the maintenance and distribution of GAMESS are also discussed.
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Affiliation(s)
- Federico Zahariev
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Peng Xu
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Bryce M Westheimer
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Simon Webb
- VeraChem LLC, 12850 Middlebrook Road, Suite 205, Germantown, Maryland 20874-5244, United States
| | - Jorge Galvez Vallejo
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Ananta Tiwari
- EP Analytics, Inc., 9909 Mira Mesa Boulevard, Suite 230, San Diego, California 92131, United States
| | - Vaibhav Sundriyal
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, United States
| | - Masha Sosonkina
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, United States
| | - Jun Shen
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - George Schoendorff
- Propellants Branch, Rocket Propulsion Division, Aerospace Systems Directorate, Air Force Research Laboratory, AFRL/RQRP, Edwards Air Force Base, California 93524, United States
| | - Megan Schlinsog
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Tosaporn Sattasathuchana
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Klaus Ruedenberg
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Luke B Roskop
- Hewlett-Packard Enterprise, 2131 Lindau Lane #1000, Bloomington, Minnesota 55425, United States
| | | | - David Poole
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
- School of Chemistry & Biochemistry, Georgia Institute of Technology, Athens, Georgia 30332, United States
| | - Piotr Piecuch
- Department of Chemistry and Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, United States
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Vladimir Mironov
- Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea
| | - Joani Mato
- Physical Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, P.O. Box 999, MS K1-83, Richland, Washington 99352, United States
| | - Sam Leonard
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Sarom S Leang
- EP Analytics, Inc., 9909 Mira Mesa Boulevard, Suite 230, San Diego, California 92131, United States
| | - Joe Ivanic
- Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, United States
| | - Jackson Hayes
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Taylor Harville
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Karthik Gururangan
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Emilie Guidez
- Department of Chemistry, University of Colorado Denver, Denver, Colorado 80217, United States
| | - Igor S Gerasimov
- Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea
| | - Christian Friedl
- Institut für Theoretische Physik, Johannes Kepler Universität Linz, Altenberger Str. 69, 4040 Linz, Austria
| | - Katherine N Ferreras
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - George Elliott
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Daniel Del Angel Cruz
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Laura Carrington
- EP Analytics, Inc., 9909 Mira Mesa Boulevard, Suite 230, San Diego, California 92131, United States
| | - Colleen Bertoni
- Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Giuseppe M J Barca
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Melisa Alkan
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
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Alkan M, Pham BQ, Hammond JR, Gordon MS. Enabling Fortran Standard Parallelism in GAMESS for Accelerated Quantum Chemistry Calculations. J Chem Theory Comput 2023. [PMID: 37343236 DOI: 10.1021/acs.jctc.3c00380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2023]
Abstract
The performance of Fortran 2008 DO CONCURRENT (DC) relative to OpenACC and OpenMP target offloading (OTO) with different compilers is studied for the GAMESS quantum chemistry application. Specifically, DC and OTO are used to offload the Fock build, which is a computational bottleneck in most quantum chemistry codes, to GPUs. The DC Fock build performance is studied on NVIDIA A100 and V100 accelerators and compared with the OTO versions compiled by the NVIDIA HPC, IBM XL, and Cray Fortran compilers. The results show that DC can speed up the Fock build by 3.0× compared with that of the OTO model. With similar offloading efforts, DC is a compelling programming model for offloading Fortran applications to GPUs.
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Affiliation(s)
- Melisa Alkan
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Jeff R Hammond
- NVIDIA Corporation, Porkkalankatu 1, Helsinki 00180, Finland
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
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Komarov K, Mironov V, Lee S, Pham BQ, Gordon MS, Choi CH. High-performance strategies for the recent MRSF-TDDFT in GAMESS. J Chem Phys 2023; 158:2890476. [PMID: 37184015 DOI: 10.1063/5.0148005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 05/02/2023] [Indexed: 05/16/2023] Open
Abstract
Multiple ERI (Electron Repulsion Integral) tensor contractions (METC) with several matrices are ubiquitous in quantum chemistry. In response theories, the contraction operation, rather than ERI computations, can be the major bottleneck, as its computational demands are proportional to the multiplicatively combined contributions of the number of excited states and the kernel pre-factors. This paper presents several high-performance strategies for METC. Optimal approaches involve either the data layout reformations of interim density and Fock matrices, the introduction of intermediate ERI quartet buffer, and loop-reordering optimization for a higher cache hit rate. The combined strategies remarkably improve the performance of the MRSF (mixed reference spin flip)-TDDFT (time-dependent density functional theory) by nearly 300%. The results of this study are not limited to the MRSF-TDDFT method and can be applied to other METC scenarios.
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Affiliation(s)
- Konstantin Komarov
- Center for Quantum Dynamics, Pohang University of Science and Technology, Pohang 37673, South Korea
| | - Vladimir Mironov
- Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea
| | - Seunghoon Lee
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Cheol Ho Choi
- Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea
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5
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Pham BQ, Carrington L, Tiwari A, Leang SS, Alkan M, Bertoni C, Datta D, Sattasathuchana T, Xu P, Gordon MS. Porting fragmentation methods to GPUs using an OpenMP API: Offloading the resolution-of-the-identity second-order Møller-Plesset perturbation method. J Chem Phys 2023; 158:2887208. [PMID: 37114705 DOI: 10.1063/5.0143424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Using an OpenMP Application Programming Interface, the resolution-of-the-identity second-order Møller-Plesset perturbation (RI-MP2) method has been off-loaded onto graphical processing units (GPUs), both as a standalone method in the GAMESS electronic structure program and as an electron correlation energy component in the effective fragment molecular orbital (EFMO) framework. First, a new scheme has been proposed to maximize data digestion on GPUs that subsequently linearizes data transfer from central processing units (CPUs) to GPUs. Second, the GAMESS Fortran code has been interfaced with GPU numerical libraries (e.g., NVIDIA cuBLAS and cuSOLVER) for efficient matrix operations (e.g., matrix multiplication, matrix decomposition, and matrix inversion). The standalone GPU RI-MP2 code shows an increasing speedup of up to 7.5× using one NVIDIA V100 GPU with one IBM 42-core P9 CPU for calculations on fullerenes of increasing size from 40 to 260 carbon atoms using the 6-31G(d)/cc-pVDZ-RI basis sets. A single Summit node with six V100s can compute the RI-MP2 correlation energy of a cluster of 175 water molecules using the correlation consistent basis sets cc-pVDZ/cc-pVDZ-RI containing 4375 atomic orbitals and 14 700 auxiliary basis functions in ∼0.85 h. In the EFMO framework, the GPU RI-MP2 component shows near linear scaling for a large number of V100s when computing the energy of an 1800-atom mesoporous silica nanoparticle in a bath of 4000 water molecules. The parallel efficiencies of the GPU RI-MP2 component with 2304 and 4608 V100s are 98.0% and 96.1%, respectively.
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Affiliation(s)
- Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | | | | | | | - Melisa Alkan
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Colleen Bertoni
- Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | | | - Peng Xu
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
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6
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Fedorov DG, Pham BQ. Multi-level parallelization of quantum-chemical calculations. J Chem Phys 2023; 158:2886744. [PMID: 37098765 DOI: 10.1063/5.0144917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/09/2023] [Indexed: 04/27/2023] Open
Abstract
Strategies for multiple-level parallelizations of quantum-mechanical calculations are discussed, with an emphasis on using groups of workers for performing parallel tasks. These parallel programming models can be used for a variety ab initio quantum chemistry approaches, including the fragment molecular orbital method and replica-exchange molecular dynamics. Strategies for efficient load balancing on problems of increasing granularity are introduced and discussed. A four-level parallelization is developed based on a multi-level hierarchical grouping, and a high parallel efficiency is achieved on the Theta supercomputer using 131 072 OpenMP threads.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umenzono, Tsukuba, Ibaraki 305-8568, Japan
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, 201 Spedding Hall, Ames, Iowa 50011, USA
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7
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Pham BQ, Alkan M, Gordon MS. Porting Fragmentation Methods to Graphical Processing Units Using an OpenMP Application Programming Interface: Offloading the Fock Build for Low Angular Momentum Functions. J Chem Theory Comput 2023; 19:2213-2221. [PMID: 37011288 DOI: 10.1021/acs.jctc.2c01137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
Abstract
A framework to offload four-index two-electron repulsion integrals to graphical processing units (GPUs) using OpenMP is discussed. The method has been applied to the Fock build for low angular momentum s and p functions in both the restricted Hartree-Fock (RHF) and in the effective fragment molecular orbital (EFMO) framework. Benchmark calculations for the GPU code for the pure RHF method show an increasing speedup relative to the existing OpenMP CPU code in GAMESS from 1.04 to 52× for clusters of 70-569 water molecules. The parallel efficiency on 24 NVIDIA V100 GPU boards also increases when increasing the system size: from 75 to 94% for water clusters that contain 303-1120 molecules. In the EFMO framework, the GPU Fock build shows a high linear scalability up to 4608 V100s with a parallel efficiency of 96% for calculations on a solvated mesoporous silica nanoparticle system with ∼67,000 basis functions.
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Affiliation(s)
- Buu Q Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Melisa Alkan
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
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8
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Galvez Vallejo JL, Tow GM, Maginn EJ, Pham BQ, Datta D, Gordon MS. Quantum Chemical Modeling of Propellant Degradation. J Phys Chem A 2023; 127:1874-1882. [PMID: 36791340 DOI: 10.1021/acs.jpca.2c08722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
An ab initio quantum chemical approach for the modeling of propellant degradation is presented. Using state-of-the-art bonding analysis techniques and composite methods, a series of potential degradation reactions are devised for a sample hydroxyl-terminated-polybutadiene (HTPB) type solid fuel. By applying thermochemical procedures and isodesmic reactions, accurate thermochemical quantities are obtained using a modified G3 composite method based on the resolution of the identity. The calculated heats of formation for the different structures produced presents an ∼2 kcal/mol average error when compared against experimental values.
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Affiliation(s)
- Jorge L Galvez Vallejo
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Garrett M Tow
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Edward J Maginn
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50014, United States
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Pham BQ, Datta D, Gordon MS. PDG: A Composite Method Based on the Resolution of the Identity. J Phys Chem A 2021; 125:9421-9429. [PMID: 34658243 DOI: 10.1021/acs.jpca.1c06186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The Gaussian-3 (G3) composite approach for thermochemical properties is revisited in light of the enhanced computational efficiency and reduced memory costs by applying the resolution-of-the-identity (RI) approximation for two-electron repulsion integrals (ERIs) to the computationally demanding component methods in the G3 model: the energy and gradient computations via the second-order Møller-Plesset perturbation theory (MP2) and the energy computations using the coupled-cluster singles-doubles method augmented with noniterative triples corrections [CCSD(T)]. Efficient implementation of the RI-based methods is achieved by employing a hybrid distributed/shared memory model based on MPI and OpenMP. The new variant of the G3 composite approach based on the RI approximation is termed the RI-G3 scheme, or alternatively the PDG method. The accuracy of the new RI-G3/PDG scheme is compared to the "standard" G3 composite approach that employs the memory-expensive four-center ERIs in the MP2 and CCSD(T) calculations. Taking the computation of the heats of formation of the closed-shell molecules in the G3/99 test set as a test case, it is demonstrated that the RI approximation introduces negligible changes to the mean absolute errors relative to the standard G3 model (less than 0.1 kcal/mol), while the standard deviations remain unaltered. The efficiency and memory requirements for the RI-MP2 and RI-CCSD(T) methods are compared to the standard MP2 and CCSD(T) approaches, respectively. The hybrid MPI/OpenMP-based RI-MP2 energy plus gradient computation is found to attain a 7.5× speedup over the standard MP2 calculations. For the most demanding CCSD(T) calculations, the application of the RI approximation is found to nearly halve the memory demand, confer about a 4-5× speedup for the CCSD iterations, and reduce the computational time for the compute-intensive triples correction step by several hours.
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Barca GMJ, Bertoni C, Carrington L, Datta D, De Silva N, Deustua JE, Fedorov DG, Gour JR, Gunina AO, Guidez E, Harville T, Irle S, Ivanic J, Kowalski K, Leang SS, Li H, Li W, Lutz JJ, Magoulas I, Mato J, Mironov V, Nakata H, Pham BQ, Piecuch P, Poole D, Pruitt SR, Rendell AP, Roskop LB, Ruedenberg K, Sattasathuchana T, Schmidt MW, Shen J, Slipchenko L, Sosonkina M, Sundriyal V, Tiwari A, Galvez Vallejo JL, Westheimer B, Włoch M, Xu P, Zahariev F, Gordon MS. Recent developments in the general atomic and molecular electronic structure system. J Chem Phys 2020; 152:154102. [PMID: 32321259 DOI: 10.1063/5.0005188] [Citation(s) in RCA: 482] [Impact Index Per Article: 120.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as it is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite such as GAMESS is maintained and developed is considered. Future developments are briefly summarized.
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Affiliation(s)
- Giuseppe M J Barca
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Colleen Bertoni
- Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - Laura Carrington
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Nuwan De Silva
- Department of Physical and Biological Sciences, Western New England University, Springfield, Massachusetts 01119, USA
| | - J Emiliano Deustua
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Jeffrey R Gour
- Microsoft, 15590 NE 31st St., Redmond, Washington 98052, USA
| | - Anastasia O Gunina
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Emilie Guidez
- Department of Chemistry, University of Colorado Denver, Denver, Colorado 80217, USA
| | - Taylor Harville
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Stephan Irle
- Computational Science and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
| | - Joe Ivanic
- Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, USA
| | - Karol Kowalski
- Physical Sciences Division, Battelle, Pacific Northwest National Laboratory, K8-91, P.O. Box 999, Richland, Washington 99352, USA
| | - Sarom S Leang
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Hui Li
- Department of Chemistry, University of Nebraska, Lincoln, Nebraska 68588, USA
| | - Wei Li
- School of Chemistry and Chemical Engineering, Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, Nanjing University, Nanjing 210023, People's Republic of China
| | - Jesse J Lutz
- Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA
| | - Ilias Magoulas
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Joani Mato
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Vladimir Mironov
- Department of Chemistry, Lomonosov Moscow State University, Leninskie Gory 1/3, Moscow 119991, Russian Federation
| | - Hiroya Nakata
- Kyocera Corporation, Research Institute for Advanced Materials and Devices, 3-5-3 Hikaridai Seika-cho, Souraku-gun, Kyoto 619-0237, Japan
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Piotr Piecuch
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - David Poole
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Spencer R Pruitt
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Alistair P Rendell
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Luke B Roskop
- Cray Inc., a Hewlett Packard Enterprise Company, 2131 Lindau Ln #1000, Bloomington, Minnesota 55425, USA
| | - Klaus Ruedenberg
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | | | - Michael W Schmidt
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Jun Shen
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Lyudmila Slipchenko
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA
| | - Masha Sosonkina
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, USA
| | - Vaibhav Sundriyal
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, USA
| | - Ananta Tiwari
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Jorge L Galvez Vallejo
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Bryce Westheimer
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Marta Włoch
- 530 Charlesina Dr., Rochester, Michigan 48306, USA
| | - Peng Xu
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Federico Zahariev
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
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11
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Pham BQ, Gordon MS. Development of the FMO/RI-MP2 Fully Analytic Gradient Using a Hybrid-Distributed/Shared Memory Programming Model. J Chem Theory Comput 2020; 16:1039-1054. [PMID: 31899632 DOI: 10.1021/acs.jctc.9b01082] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The fully analytic gradient of the second-order Møller-Plesset perturbation theory (MP2) with the resolution-of-the-identity (RI) approximation in the fragment molecular orbital (FMO) framework is derived and implemented using a hybrid multilevel parallel programming model, a combination of the general distributed data interface (GDDI) and the OpenMP API. The FMO/MP2 analytic gradient contains three parts, i.e., the internal fragment component, the electrostatic potential (ESP) component, and the response terms. The RI approximation is applied to the internal fragment MP2 gradient term, whose MP2 densities and monomer MP2 Lagrangians are shared with the ESP and the response terms. The FMO/RI-MP2 analytic gradient implementation is validated against the numerical gradient (with errors ∼10-6-10-5 Hartree/Bohr) and the energy conservation in molecular dynamics (MD) simulations using NVE ensembles. The RI approximation introduces an error of ∼10-5 Hartree/Bohr with a speedup of 4.0-8.0× compared with the currently available GDDI FMO/MP2 gradient. The node linear scaling of the fragmentation framework due to multilevel parallelism is well-preserved and is demonstrated in single-point gradient calculations of large water clusters (e.g., 1120 and 2165 molecules) using 300-800 KNL compute nodes with a parallel efficiency of more than 90%.
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Affiliation(s)
- Buu Q Pham
- Department of Chemistry and Ames Laboratory , Iowa State University , Ames , Iowa 50011 , United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory , Iowa State University , Ames , Iowa 50011 , United States
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12
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Pham BQ, Gordon MS. Hybrid Distributed/Shared Memory Model for the RI-MP2 Method in the Fragment Molecular Orbital Framework. J Chem Theory Comput 2019; 15:5252-5258. [DOI: 10.1021/acs.jctc.9b00409] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Buu Q. Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S. Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
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Pham BQ, Gordon MS. Compressing the Four-Index Two-Electron Repulsion Integral Matrix using the Resolution-of-the-Identity Approximation Combined with the Rank Factorization Approximation. J Chem Theory Comput 2019; 15:2254-2264. [DOI: 10.1021/acs.jctc.8b01256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Buu Q. Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S. Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
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14
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Affiliation(s)
- Buu Q. Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S. Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
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15
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Abstract
The thermodynamic and kinetic controls of graphene chemistry are studied computationally using a graphene hydrogenation reaction and polyaromatic hydrocarbons to represent the graphene surface. Hydrogen atoms are concertedly chemisorped onto the surface of graphene models of different shapes (i.e., all-zigzag, all-armchair, zigzag-armchair mixed edges) and sizes (i.e., from 16-42 carbon atoms). The second-order Z-averaged perturbation theory (ZAPT2) method combined with Pople double and triple zeta basis sets are used for all calculations. It is found that both the net enthalpy change and the barrier height of graphene hydrogenation at graphene edges are lower than at their interior surfaces. While the thermodynamic product distribution is mainly determined by the remaining π-islands of functionalized graphenes (Phys. Chem. Chem. Phys., 2013, 15, 3725-3735), the kinetics of the reaction is primarily correlated with the localization of the electrostatic potential of the graphene surface.
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Affiliation(s)
- Buu Q Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, USA.
| | - Mark S Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, USA.
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16
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Pham MP, Pham BQ, Huynh LK, Pham HQ, Marks MJ, Truong TN. Density functional theory study on mechanisms of epoxy-phenol curing reaction. J Comput Chem 2014; 35:1630-40. [DOI: 10.1002/jcc.23658] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Revised: 05/09/2014] [Accepted: 05/25/2014] [Indexed: 11/09/2022]
Affiliation(s)
- My-Phuong Pham
- Institute for Computational Science and Technology; Ho-Chi-Minh City Vietnam
| | - Buu Q. Pham
- Institute for Computational Science and Technology; Ho-Chi-Minh City Vietnam
| | - Lam K. Huynh
- Institute for Computational Science and Technology; Ho-Chi-Minh City Vietnam
| | - Ha Q. Pham
- The Dow Chemical Company; Building B-1226 Freeport Texas 77541
| | | | - Thanh N. Truong
- Institute for Computational Science and Technology; Ho-Chi-Minh City Vietnam
- Department of Chemistry; University of Utah; 315 South 1400 East, Rm 2020 Salt Lake City Utah 84112
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Page AJ, Chou CP, Pham BQ, Witek HA, Irle S, Morokuma K. Quantum chemical investigation of epoxide and ether groups in graphene oxide and their vibrational spectra. Phys Chem Chem Phys 2013; 15:3725-35. [PMID: 23388654 DOI: 10.1039/c3cp00094j] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We present a detailed analysis of the factors influencing the formation of epoxide and ether groups in graphene nanoflakes using conventional density functional theory (DFT), the density-functional tight-binding (DFTB) method, π-Hückel theory, and graph theoretical invariants. The relative thermodynamic stability associated with the chemisorption of oxygen atoms at various positions on hexagonal graphene flakes (HGFs) of D(6h)-symmetry is determined by two factors - viz. the disruption of the π-conjugation of the HGF and the geometrical deformation of the HGF structure. The thermodynamically most stable structure is achieved when the former factor is minimized, and the latter factor is simultaneously maximized. Infrared (IR) spectra computed using DFT and DFTB reveal a close correlation between the relative thermodynamic stabilities of the oxidized HGF structures and their IR spectral activities. The most stable oxidized structures exhibit significant IR activity between 600 and 1800 cm(-1), whereas less stable oxidized structures exhibit little to no activity in this region. In contrast, Raman spectra are found to be less informative in this respect.
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Affiliation(s)
- Alister J Page
- Fukui Institute for Fundamental Chemistry, Kyoto University, Kyoto 606-8103, Japan
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Mohan R, Sivak J, Ashton P, Russo LA, Pham BQ, Kasahara N, Raizman MB, Fini ME. Curcuminoids inhibit the angiogenic response stimulated by fibroblast growth factor-2, including expression of matrix metalloproteinase gelatinase B. J Biol Chem 2000; 275:10405-12. [PMID: 10744729 DOI: 10.1074/jbc.275.14.10405] [Citation(s) in RCA: 193] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
We have studied mechanisms controlling activation of the gelatinase B gene (matrix metalloproteinase-9) by fibroblast growth factor-2 (FGF-2) during angiogenesis, and the effects of the natural product curcuminoids on this process. Using a transgenic mouse (line 3445) harboring a gelatinase B promoter/lacZ fusion gene, we demonstrate FGF-2 stimulation of reporter gene expression in endothelial cells of invading neocapillaries in the corneal micropocket assay. Using cultured corneal cells, we show that FGF-2 stimulates DNA binding activity of transcription factor AP-1 but not NF-kappaB and that AP-1 stimulation is inhibited by curcuminoids. We further show that induction of gelatinase B transcriptional promoter activity in response to FGF-2 is dependent on AP-1 but not NF-kappaB response elements and that promoter activity is also inhibited by curcuminoids. In rabbit corneas, the angiogenic response induced by implantation of an FGF-2 pellet is inhibited by the co-implantation of a curcuminoid pellet, and this correlates with inhibition of endogenous gelatinase B expression induced by FGF-2. Angiostatic efficacy in the cornea is also observed when curcuminoids are provided to mice in the diet. Our findings provide evidence that curcuminoids target the FGF-2 angiogenic signaling pathway and inhibit expression of gelatinase B in the angiogenic process.
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Affiliation(s)
- R Mohan
- Vision Research Laboratories of New England Eye Center and the Department of Ophthalmology, Tufts University School of Medicine, Boston, Massachusetts 02111, USA
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