Modernizing the core quantum chemistry algorithms

This document covers the basics of computational chemistry and how using the modern programming techniques the theory can be efficiently implemented on digital computers. The computer implementations are developed from the core two-electron integrals to many-body and coupled cluster algorithms. A particular attention is paid to the physical constraints of he computer resources and the emergence of the novel architectures

Large-Scale MP2 Calculations on the Blue Gene Architecture Using the Fragment Molecular Orbital Method

Benchmark timings are presented for the fragment molecular orbital method on a Blue Gene/P computer. Algorithmic modifications that lead to enhanced performance on the Blue Gene/P architecture include strategies for the storage of fragment density matrices by process subgroups in the global address space. The computation of the atomic forces for a system with more than 3000 atoms and 44 000 basis functions, using second order perturbation theory and an augmented and polarized double-ζ basis set, takes ∼7 min on 131 072 cores

Recent Developments in the General Atomic and Molecular Electronic Structure System

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

A Novel Approach to Parallel Coupled Cluster Calculations: Combining Distributed and Shared Memory Techniques for Modern Cluster Based Systems

A parallel coupled cluster algorithm that combines distributed and shared memory techniques for the CCSD(T) method (singles + doubles with perturbative triples) is described. The implementation of the massively parallel CCSD(T) algorithm uses a hybrid molecular and “direct” atomic integral driven approach. Shared memory is used to minimize redundant replicated storage per compute process. The algorithm is targeted at modern cluster based architectures that are comprised of multiprocessor nodes connected by a dedicated communication network. Parallelism is achieved on two levels:  parallelism within a compute node via shared memory parallel techniques and parallelism between nodes using distributed memory techniques. The new parallel implementation is designed to allow for the routine evaluation of mid- (500−750 basis function) to large-scale (750−1000 basis function) CCSD(T) energies. Sample calculations are performed on five low-lying isomers of water hexamer using the aug-cc-pVTZ basis set

Scalable computational chemistry: new developments and applications

The computational part of the thesis is the investigation of titanium chloride (II) as a potential catalyst for the bis-silylation reaction of ethylene with hexaclorodisilane at different levels of theory. Bis-silylation is an important reaction for producing bis(silyl) compounds and new C-Si bonds, which can serve as monomers for silicon containing polymers and silicon carbides. Ab initio calculations on the steps involved in a proposed mechanism are presented. This choice of reactants allows us to study this reaction at reliable levels of theory without compromising accuracy. Our calculations indicate that this is a highly exothermic barrierless reaction. The TiCl 2 catalyst removes a 50 kcal/mol activation energy barrier required for the reaction without the catalyst. The first step is interaction of TiCl 2 with ethylene to form an intermediate that is 60 kcal/mol below the energy of the reactants. This is the driving force for the entire reaction. Dynamic correlation plays a significant role because RHF calculations indicate that the net barrier for the catalyzed reaction is 50 kcal/mol. We conclude that divalent Ti has the potential to become an important industrial catalyst for silylation reactions.;In the programming part of the thesis, parallelization of different quantum chemistry methods is presented. The parallelization of code is becoming important aspect of quantum chemistry code development. Two trends contribute to it: the overall desire to study large chemical systems and the desire to employ highly correlated methods which are usually computationally and memory expensive. In the presented distributed data algorithms computation is parallelized and the largest arrays are evenly distributed among CPUs. First, the parallelization of the Hartree-Fock self-consistent field (SCF) method is considered. SCF method is the most common starting point for more accurate calculations. The Fock build (sub step of SCF) from AO integrals is also often used to avoid MO integral computation. The presented distributed data SCF increases the size of chemical systems that can be calculated by using RHF and DFT. The important ab initio method to study bond formation and breaking as well as excited molecules is CASSCF. The presented distributed data CASSCF algorithm can significantly decrease computational time and memory requirements per node. Therefore, large CASSCF computations can be performed. The most time consuming operation to study potential energy surfaces of reactions and chemical systems is Hessian calculations. The distributed data parallelization of CPHF will allow scientists carry out large analytic Hessian calculations

Knowledge is power: Quantum chemistry on novel computer architectures

In the first chapter of this thesis, a background of fundamental quantum chemistry concepts is provided. Chapter two contains an analysis of the performance and energy efficiency of various modern computer processor architectures while performing computational chemistry calculations. In chapter three, the processor architectural study is expanded to include parallel computational chemistry algorithms executed across multiple-node computer clusters. Chapter four describes a novel computational implementation of the fundamental Hartree-Fock method which significantly reduces computer memory requirements. In chapter five, a case study of quantum chemistry two-electron integral code interoperability is described. The final chapters of this work discuss applications of quantum chemistry. In chapter six, an investigation of the esterification of acetic acid on acid-functionalized silica is presented. In chapter seven, the application of ab initio molecular dynamics to study the photoisomerization and photocyclization of stilbene is discussed. Final concluding remarks are noted in chapter eight

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.Comment: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini ([email protected]) and Danny Perez ([email protected]

Knowledge is power: Quantum chemistry on novel computer architectures

In the first chapter of this thesis, a background of fundamental quantum chemistry concepts is provided. Chapter two contains an analysis of the performance and energy efficiency of various modern computer processor architectures while performing computational chemistry calculations. In chapter three, the processor architectural study is expanded to include parallel computational chemistry algorithms executed across multiple-node computer clusters. Chapter four describes a novel computational implementation of the fundamental Hartree-Fock method which significantly reduces computer memory requirements. In chapter five, a case study of quantum chemistry two-electron integral code interoperability is described. The final chapters of this work discuss applications of quantum chemistry. In chapter six, an investigation of the esterification of acetic acid on acid-functionalized silica is presented. In chapter seven, the application of ab initio molecular dynamics to study the photoisomerization and photocyclization of stilbene is discussed. Final concluding remarks are noted in chapter eight

Drama in dynamics: boom, splash, and speed

The full nature of theoretical chemistry and physics cannot be captured by static calculations alone. The underlying goal of this thesis is the utilization of dynamics methods, appropriate to the size and type of chemical system under consideration, as well as the type of desired data obtained from the calculation. A small, potentially high-energy molecule, FN5, was studied with high level, on-the-fly ab initio (AI) methods in order study isomerization and decomposition pathways, and ultimately predict the existence (lifetime) of the species. Experimentalists confirmed these calculations. In order to study solvation processes, large numbers of molecules, as well as dynamics methods, are important. The Effective Fragment Potential (EFP) method for solvation, a method based on quantum mechanics calculations, was parallelized to facilitate these calculations within the quantum chemistry program GAMESS. The parallel algorithm employs both atom decomposition of data, as well as non-blocking communication. Speedup and scalability of the code was achieved. The EFP method has been shown to provide excellent results for small water clusters in previous calculations. In order to test the bulk behavior of the EFP method, EFP molecular dynamics simulations were performed. The resulting radial distribution functions for water are in good agreement with experimental data. Finally, one of the most fundamental aspects of a chemical reaction was investigated: the molecular potential energy surface (PES). This involved the interface of the Grow and GAMESS programs. Grow builds a PES as an interpolation of AI data, and thus requires AI calculations of energy and derivatives from GAMESS. Classical or quantum dynamics can be performed on the resulting surface. The interface also includes the capability to build multi-reference PESs; these types of calculations are applicable to a wide array of problems, including photochemistry and photobiology

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing