158 research outputs found
ELSI: A Unified Software Interface for Kohn-Sham Electronic Structure Solvers
Solving the electronic structure from a generalized or standard eigenproblem
is often the bottleneck in large scale calculations based on Kohn-Sham
density-functional theory. This problem must be addressed by essentially all
current electronic structure codes, based on similar matrix expressions, and by
high-performance computation. We here present a unified software interface,
ELSI, to access different strategies that address the Kohn-Sham eigenvalue
problem. Currently supported algorithms include the dense generalized
eigensolver library ELPA, the orbital minimization method implemented in
libOMM, and the pole expansion and selected inversion (PEXSI) approach with
lower computational complexity for semilocal density functionals. The ELSI
interface aims to simplify the implementation and optimal use of the different
strategies, by offering (a) a unified software framework designed for the
electronic structure solvers in Kohn-Sham density-functional theory; (b)
reasonable default parameters for a chosen solver; (c) automatic conversion
between input and internal working matrix formats, and in the future (d)
recommendation of the optimal solver depending on the specific problem.
Comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800
basis functions) on distributed memory supercomputing architectures.Comment: 55 pages, 14 figures, 2 table
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]
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
Distributed Memory, GPU Accelerated Fock Construction for Hybrid, Gaussian Basis Density Functional Theory
With the growing reliance of modern supercomputers on accelerator-based
architectures such a GPUs, the development and optimization of electronic
structure methods to exploit these massively parallel resources has become a
recent priority. While significant strides have been made in the development of
GPU accelerated, distributed memory algorithms for many-body (e.g.
coupled-cluster) and spectral single-body (e.g. planewave, real-space and
finite-element density functional theory [DFT]), the vast majority of
GPU-accelerated Gaussian atomic orbital methods have focused on shared memory
systems with only a handful of examples pursuing massive parallelism on
distributed memory GPU architectures. In the present work, we present a set of
distributed memory algorithms for the evaluation of the Coulomb and
exact-exchange matrices for hybrid Kohn-Sham DFT with Gaussian basis sets via
direct density-fitted (DF-J-Engine) and seminumerical (sn-K) methods,
respectively. The absolute performance and strong scalability of the developed
methods are demonstrated on systems ranging from a few hundred to over one
thousand atoms using up to 128 NVIDIA A100 GPUs on the Perlmutter
supercomputer.Comment: 45 pages, 9 figure
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
On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters
The predominance of Kohn-Sham density functional theory (KS-DFT) for the
theoretical treatment of large experimentally relevant systems in molecular
chemistry and materials science relies primarily on the existence of efficient
software implementations which are capable of leveraging the latest advances in
modern high performance computing (HPC). With recent trends in HPC leading
towards in increasing reliance on heterogeneous accelerator based architectures
such as graphics processing units (GPU), existing code bases must embrace these
architectural advances to maintain the high-levels of performance which have
come to be expected for these methods. In this work, we purpose a three-level
parallelism scheme for the distributed numerical integration of the
exchange-correlation (XC) potential in the Gaussian basis set discretization of
the Kohn-Sham equations on large computing clusters consisting of multiple GPUs
per compute node. In addition, we purpose and demonstrate the efficacy of the
use of batched kernels, including batched level-3 BLAS operations, in achieving
high-levels of performance on the GPU. We demonstrate the performance and
scalability of the implementation of the purposed method in the NWChemEx
software package by comparing to the existing scalable CPU XC integration in
NWChem.Comment: 26 pages, 9 figure
Development of highly efficient and accurate real-space integration methods for Hartree-Fock and hybrid density functional calculations
The central focus of molecular electronic structure theory is to find approximate solutions to the electronic Schrödinger equation for molecules, and as such represents an essential part of any theoretical (in silico) study of chemical processes. However, a steep increase of the computational cost with increasing system size often prevents the application of accurate approximations to the molecules of interest.
The main focus of the present work is the efficient evaluation of Fock-exchange contributions, which typically represents the computational bottleneck in Hartree-Fock (HF) and hybrid density functional theory (DFT) calculations. This bottleneck is addressed by means of seminumerical integration, i.e., one electronic coordinate within the 4-center-2-electron integral tensor is represented analytically and one numerically.
In this way, an asymptotically linear scaling method for computing the exchange matrix (denoted as sn-LinK) is developed, enabling fast and accurate ab-initio calculations on large molecules, comprising hundreds or even thousands of atoms, even in combination with large atomic orbital basis sets.
The novel sn-LinK method comprises improvements to the numerical integration grids, a rigorous, batch-wise integral screening scheme, the optimal utilization of modern, highly parallel compute architectures (e.g., graphics processing units; GPUs), and an efficient combination of single- and double-precision arithmetic. In total, these optimizations enable over two orders of magnitude faster evaluation of Fock-exchange contributions.
Consequently, this greatly improved performance allows to perform previously unfeasible computations, which is also demonstrated at the example of an ab initio molecular dynamics simulation (AIMD) study on the hydrogen bond strengths within double-stranded DNA. In addition to Fock-exchange, the other two computational bottlenecks in hybrid-DFT applications – the evaluation of the Coulomb potential and the numerical integration of the semilocal exchange-correlation functional – are also addressed. Finally, more efficient methods to evaluate more accurate post-HF/DFT methods, namely the random-phase approximation (RPA) and the second-order approximate coupled cluster (CC2) method, are also put forward. In this way, the highly efficient methods introduced in this thesis cover some of the most substantial computational bottlenecks in electronic-structure theory – the evaluation of the Coulomb- and the exchange-interactions, the integration of the semilocal exchange-correlation functional, and the computation of post-Hartree-Fock correlation energies.
Consequently, computational chemistry studies on large molecules (>100 atoms) are accelerated by multiple orders of magnitude, allowing for much more accurate and thorough in-silico studies than ever before
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