The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures

Zahariev, Federico; Xu, Peng; Westheimer, Bryce M.; Webb, Simon; Galvez Vallejo, Jorge; Tiwari, Ananta; Sundriyal, Vaibhav; Sosonkina, Masha; Shen, Jun; Schoendorff, George; Schlinsog, Megan; Sattasathuchana, Tosaporn; Ruedenberg, Klaus; Roskop, Luke B.; Rendell, Alistair P.; Poole, David; Piecuch, Piotr; Pham, Buu Q.; Mironov, Vladimir; Mato, Joani; Leonard, Sam; Leang, Sarom S.; Ivanic, Joe; Hayes, Jackson; Harville, Taylor; Gururangan, Karthik; Guidez, Emilie; Gerasimov, Igor S.; Friedl, Christian; Ferreras, Katherine N.; Elliott, George; Datta, Dipayan; Cruz, Daniel Del Angel; Carrington, Laura; Bertoni, Colleen; Barca, Giuseppe M. J.; Alkan, Melisa; Gordon, Mark S.

doi:10.1021/acs.jctc.3c00379

Cited by 20 publications

(11 citation statements)

References 157 publications

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“…State-specific SF-MRMP2 and MC-PDFT energies with a minimal active space are also shown in Table . The available experimental excitation energies and CASPT2 energies are obtained from the literature . Generally, the SF-ORMAS method predicts excitation energies that are too high by about ∼1 eV.…”

Section: Resultsmentioning

confidence: 99%

A Merger of the Spin-Flip ORMAS Approach and the MC-PDFT Method

Ferreras,

Gordon

2024

J. Chem. Theory Comput.

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Section: Resultsmentioning

confidence: 99%

A Merger of the Spin-Flip ORMAS Approach and the MC-PDFT Method

Ferreras,

Gordon

2024

J. Chem. Theory Comput.

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“…All calculations in the present work have been carried out using either MPI or hybrid MPI/OpenMP codes implemented in the GAMESS software package. − The generation of EFP parameters in the MAKEFP procedure can be performed as a standalone calculation or as part of an EFMO calculation. To verify the correctness of the new MAKEFP code, the interaction energies of the S22 data set, a set of 22 molecular dimers bound by noncovalent forces, are compared between the new memory-based implementation and the existing I/O-based one.…”

Section: Computational Detailsmentioning

confidence: 99%

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

Sattasathuchana,

Xu,

Bertoni

et al. 2024

J. Chem. Theory Comput.

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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 twolevel 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 timedependent 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, R cut . R cut 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 R cut 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 R cut 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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“…The many-core architecture of the GPU is specially designed for compute-bound and memory-bound tasks such as matrix–matrix multiplication (GEMM) and fast Fourier transformation (FFT), respectively. As a result, GPU has been widely adopted in computational chemistry and physics packages, e.g., TeraChem, , GAMESS, FermiONs++, VASP, , PWmat, , Quantum Espresso, BerkeleyGW, etc. In addition, recent developments of Tensor Cores have significantly improved the computational capability of GPUs; in particular, GEMM in double precision can be further accelerated on NVIDIA A100 or H100 GPUs.…”

Section: Introductionmentioning

confidence: 99%

Distributed Multi-GPU Ab Initio Density Matrix Renormalization Group Algorithm with Applications to the P-Cluster of Nitrogenase

Xiang,

Jia,

Fang

et al. 2024

J. Chem. Theory Comput.

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The presence of many degenerate d/f orbitals makes polynuclear transition-metal compounds, such as iron−sulfur clusters in nitrogenase, challenging for state-of-the-art quantum chemistry methods. To address this challenge, we present the first distributed multi-graphics processing unit (GPU) ab initio density matrix renormalization group (DMRG) algorithm suitable for modern high-performance computing (HPC) infrastructures. The central idea is to parallelize the most computationally intensive part�the multiplication of O(K 2 ) operators with a trial wave function, where K is the number of spatial orbitals, by combining operator parallelism for distributing the workload with a batched algorithm for performing contractions on GPU. With this new implementation, we are able to reach an unprecedentedly large bond dimension D = 14,000 on 48 GPUs (NVIDIA A100 80 GB SXM) for an active space model (114 electrons in 73 active orbitals) of the P-cluster, which is nearly 3 times larger than the bond dimensions reported in previous DMRG calculations for the same system using only central processing units (CPUs).

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The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures

Cited by 20 publications

References 157 publications

A Merger of the Spin-Flip ORMAS Approach and the MC-PDFT Method

A Merger of the Spin-Flip ORMAS Approach and the MC-PDFT Method

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

Distributed Multi-GPU Ab Initio Density Matrix Renormalization Group Algorithm with Applications to the P-Cluster of Nitrogenase

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