The first chapter in this thesis describes the theoretical framework that underlies much of electronic structure theory. The second chapter provides a review of the modern state of the intersection between electronic structure theory and high-performance computing. The next four chapters describe the development and implementation of new code into the GAMESS software package that utilizes Graphics Processing Units (GPUs) to achieve optimal performance. Chapter Three discusses an initial implementation of the GPU-driven Fock build step for the Restricted Hartree-Fock (RHF) method and the subsequent performance analysis on the Summit supercomputer. Chapter Four describes further developments to the aforementioned GPU-driven RHF Fock build code. Chapter Five discusses the extension of the GPU-driven RHF Fock build algorithm to the entirety of the Self-Consistent Field (SCF) process, which enables multiple steps of the SCF process to utilize GPUs. Chapter Six discusses the development of a new, GPU-driven algorithm for the Møller-Plesset Second-Order Perturbation Theory method (MP2) using the Resolution of the Identity (RI) and a subsequent performance analysis of the new RI-MP2 algorithm on the Summit Supercomputer. The next two chapters discuss the development of JuliaChem, a new electronic structure theory software package implemented in the Julia programming language. Chapter Seven provides an initial performance assessment of the RHF SCF algorithm implemented in Julia compared to GAMESS. Chapter Eight describes further algorithmic developments to the JuliaChem RHF algorithm and provides a performance analysis compared to modern developments in the GAMESS code. Chapter Nine provides an analysis of the ethylenedione molecule and its inherently unstable nature using multiple theoretical methods. Chapter Ten, the final chapter of the dissertation, provides final concluding thoughts.
The first chapter in this thesis describes the theoretical framework that underlies much of electronic structure theory. The second chapter provides a review of the modern state of the intersection between electronic structure theory and high-performance computing. The next four chapters describe the development and implementation of new code into the GAMESS software package that utilizes Graphics Processing Units (GPUs) to achieve optimal performance. Chapter Three discusses an initial implementation of the GPU-driven Fock build step for the Restricted Hartree-Fock (RHF) method and the subsequent performance analysis on the Summit supercomputer. Chapter Four describes further developments to the aforementioned GPU-driven RHF Fock build code. Chapter Five discusses the extension of the GPU-driven RHF Fock build algorithm to the entirety of the Self-Consistent Field (SCF) process, which enables multiple steps of the SCF process to utilize GPUs. Chapter Six discusses the development of a new, GPU-driven algorithm for the Møller-Plesset Second-Order Perturbation Theory method (MP2) using the Resolution of the Identity (RI) and a subsequent performance analysis of the new RI-MP2 algorithm on the Summit Supercomputer. The next two chapters discuss the development of JuliaChem, a new electronic structure theory software package implemented in the Julia programming language. Chapter Seven provides an initial performance assessment of the RHF SCF algorithm implemented in Julia compared to GAMESS. Chapter Eight describes further algorithmic developments to the JuliaChem RHF algorithm and provides a performance analysis compared to modern developments in the GAMESS code. Chapter Nine provides an analysis of the ethylenedione molecule and its inherently unstable nature using multiple theoretical methods. Chapter Ten, the final chapter of the dissertation, provides final concluding thoughts.
In the field of electronic structure theory, many optimizations, ranging from accelerator offloading to exploitation of modern programming constructs, have been used to improve the performance of quantum chemistry software. However, one area that has remained largely unexplored is the space of novel programming languages that can provide unique benefits to quantum chemistry software development. One such programming language is Julia, an interpreted language designed to achieve the performance of high-performance, statically compiled languages. To assess the viability of Julia, the restricted Hartree-Fock method was implemented in a new quantum chemistry software package, JuliaChem. JuliaChem is a novel quantum chemistry software designed to take advantage of Julia as much as possible while achieving runtimes comparable to that of more established quantum chemistry software packages. Performance benchmarks against the popular quantum chemistry software package GAMESS, using the S22 test set of molecules, indicate that JuliaChem displays performance that is competitive with that of GAMESS. This shows that Julia could be a potentially useful tool for the field of electronic structure theory.
In this work, the density fitting (DF) approximation is added to the restricted Hartree-Fock (RHF) implementation in the JuliaChem computational chemistry code. Utilizing a DF algorithm that uses symmetry and integral screening, a significant reduction in time to compute the Fock matrix is achieved. The symmetry and screening DF-RHF techniques were adapted to be performed on graphics processing units (GPUs), which are well suited to perform the matrix multiplications that comprise the bulk of the Fock build time in DF-RHF. The JuliaChem DF-RHF GPU algorithm employs a novel approach that automatically switches between two DF-RHF algorithms depending on the number of basis functions in the calculation. The JuliaChem GPU DF-RHF implementation demonstrates up to 2× speedup for Fock build times compared to the existing best-in-class GPU DF-RHF implementation by operating directly on screened intermediate matrices. Due to the high portability of the Julia language code, the JuliaChem CPU and GPU DF-RHF implementations could be benchmarked on a variety of CPU and GPU architectures from multiple hardware vendors.
Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice. In this paper, novel algorithms and software are presented that enable extreme-scale quantum chemistry capabilities with particular emphasis on exascale calculations. This includes the development and application of the multi-Graphics Processing Unit (GPU) library LibCChem 2.0 as part of the General Atomic and Molecular Electronic Structure System package and of the standalone Extreme-scale Electronic Structure System (EXESS), designed from the ground up for scaling on thousands of GPUs to perform high-performance accurate quantum chemistry calculations at unprecedented speed and molecular scales. Among various results, we report that the EXESS implementation enables Hartree-Fock/cc-pVDZ plus RI-MP2/cc-pVDZ/cc-pVDZ-RIFIT calculations on an ionic liquid system with 623 016 electrons and 146 592 atoms in less than 45 min using 27 600 GPUs on the Summit supercomputer with a 94.6% parallel efficiency.
Post-Hartree-Fock methods are wavefunction-based quantum chemistry approaches that explicitly account for the electron correlation beyond the mean-field approximation, allowing accurate determination of electron orbitals and energies in a given system. However, their computational cost scales as the fourth power or higher with respect to the number of atoms, severely limiting their practical applications. This paper proposes an efficient GPU implementation of the Møller-Plesset method, a post-Hartree-Fock approach based on perturbation theory. We focus on the computation of second- and thirdorder perturbation energies (MP2 and MP3) for closed-shell systems, which incorporate electron correlation on top of the Hartree-Fock energy. To accelerate the extensive contraction operations arising in the Møller-Plesset method, our implementation employs a formulation that maximizes the use of highly optimized matrix multiplication routines. Furthermore, we effectively utilize computational capabilities of GPU architecture through a hierarchical reduction using warp-level primitives and shared memory, as well as contiguous coalesced access to matrix elements. Performance evaluation on an NVIDIA A100 GPU shows up to 255.5 and 71.1 times speedups for the MP2 correlation energy computation, compared with the widely used quantum chemistry software package PySCF and its GPU plugin GPU4PySCF, respectively. In the MP3 calculations, our DGEMM-based implementation achieves a maximum speedup of 96.2 times over PySCF.
Graphical Processing Units (GPUs) are highly parallel, programmable accelerators boasting high peak floating point performance. Over the last couple of years the use of GPUs for general purpose computing have revolutionized quantum chemistry. The computational bottleneck in an ab-initio quantum method is the calculation of a large number of twoelectron integrals. To date, a number of GPU accelerated two-electron integral implementations have been developed significantly improving the performance of a static quantum mechanical (QM) calculation. However, when performing an ab-initio QM gradient calculation, optimization, QM or Hybrid Quantum Mechanical/Molecular Mechanical (QM/MM) dynamics simulation the twoelectron integral derivatives arise as an additional bottleneck. Hybrid QM/MM methods particularly dynamics methods are commonly used to study large chemical/biological systems. These methods are a popular choice used for studying reaction mechanisms, conformational and configurational structures important in glycobiology. Usually a semiempirical QM method is used however, these have shown variable accuracy for the study of carbohydrate conformation and prevents an analytical investigation of electronic structure. The use of a higher level of theory, such as an ab initio method, is desirable however this comes at a much greater computational cost. Together with the bottlenecks above this cost results from the polarization of the QM region within an electrostatic embedding scheme, which requires the calculation of a large number of one-electron integral derivatives. Thus for QM/MM calculations the one-electron integral derivatives becomes a third bottleneck together with the two mentioned above. Recently, the above bottlenecks have become popular GPU acceleration targets. This thesis describes an extension of the GPU based Quantum Supercharger Library (QSL) to perform the above calculations/simulations. In contrast to GPU packages developed from the ground up, the QSL is a library of routines aimed at accelerating legacy codes, such as GAMESS-UK, GAMESS-US and NWChem, used in electronic structure calculations. Algorithms are presented for accelerating the one- and two-electron integral derivatives on a GPU. In addition to the derivatives, the one-electron integral calculation was ported to the GPU in order to remove a small additional cost arising for large QM/MM systems. Furthermore, the use of automatic code generation for generating GPU kernels was explored and compared to the original approach. Using the QSL library implemented in GAMESS-UK several benchmark calculations and simulations were performed. These were performed in double precision on a single GPU (Kepler K20) and compared to a single CPU using the 6-31G basis set. A speedup of up to 9.3X is achieved for an ab initio gradient calculation compared to the CPU running an optimized serial version of GAMESS-UK using the Schlegel method. For a single point QM/MM calculation of cellobiose in different sized water spheres (3267-24843 point charges) speedups of between 13X and 34X is achieved. QSL/GAMESS-UK coupled to the CHARMM molecular dynamics package was then used in order to perform accelerated molecular dynamics simulations. Benchmark QM and QM/MM molecular dynamics simulations were performed on cellobiose in vacuo and in a water sphere (45 QM atoms and 24843 point charges respectively). The QSL is able to perform 9.7 ps/day of ab initio QM dynamics and 6.4 ps/day of QM/MM dynamics. Testing of the auto-generated version of the QSL showed better performance for lower angular momentum classes but reduced performance for higher angular momentum classes. The efficiency of the integral and derivative routines within the QSL library was tested on a computationally intense realistic glycobiological condensed phase free energy computation. Ab-initio pucker free energy surfaces/volumes of !-Ribofuranose and !-Glucopyranose in vacuum and in water were computed. These are the first converged Hartree-Fock/MM free energy simulations for these carbohydrates performed in solution. The value of the ab initio Free energy surfaces/volumes was demonstrated through an analysis of solvent polarization effects that are evident through a comparison of the vacuum and solution minimum free energy pathways. In particular the water structure around the pucker conformers, analysis of the primary alcohol distribution as well as analysis of the electronic structure of these conformers reveals that water significantly affects the free energy pathways, primary alcohol distribution and the barriers for inter-conversion between pucker conformers.