85,346 research outputs found
Advances in molecular quantum chemistry contained in the Q-Chem 4 program package
A summary of the technical advances that are incorporated in the fourth major release of the Q-CHEM quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube
Advances in Molecular Quantum Chemistry Contained in the Q-Chem 4 Program Package
A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube
Optimizing Distributed Tensor Contractions using Node-Aware Processor Grids
We propose an algorithm that aims at minimizing the inter-node communication
volume for distributed and memory-efficient tensor contraction schemes on
modern multi-core compute nodes. The key idea is to define processor grids that
optimize intra-/inter-node communication volume in the employed contraction
algorithms. We present an implementation of the proposed node-aware
communication algorithm into the Cyclops Tensor Framework (CTF). We demonstrate
that this implementation achieves a significantly improved performance for
matrix-matrix-multiplication and tensor-contractions on up to several hundreds
modern compute nodes compared to conventional implementations without using
node-aware processor grids. Our implementation shows good performance when
compared with existing state-of-the-art parallel matrix multiplication
libraries (COSMA and ScaLAPACK). In addition to the discussion of the
performance for matrix-matrix-multiplication, we also investigate the
performance of our node-aware communication algorithm for tensor contractions
as they occur in quantum chemical coupled-cluster methods. To this end we
employ a modified version of CTF in combination with a coupled-cluster code
(Cc4s). Our findings show that the node-aware communication algorithm is also
able to improve the performance of coupled-cluster theory calculations for
real-world problems running on tens to hundreds of compute nodes.Comment: 15 pages, 4 figure
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
Enhancing Energy Production with Exascale HPC Methods
High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose
processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale
simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of
Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and
from the Brazilian Ministry of Science, Technology and Innovation through Rede
Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the
Intel Corporation, which enabled us to obtain the presented experimental results in
uncertainty quantification in seismic imagingPostprint (author's final draft
Generalized Unitary Coupled Cluster Wavefunctions for Quantum Computation
We introduce a unitary coupled-cluster (UCC) ansatz termed -UpCCGSD that
is based on a family of sparse generalized doubles (D) operators which provides
an affordable and systematically improvable unitary coupled-cluster
wavefunction suitable for implementation on a near-term quantum computer.
-UpCCGSD employs products of the exponential of pair coupled-cluster
double excitation operators (pCCD), together with generalized single (S)
excitation operators. We compare its performance in both efficiency of
implementation and accuracy with that of the generalized UCC ansatz employing
the full generalized SD excitation operators (UCCGSD), as well as with the
standard ansatz employing only SD excitations (UCCSD). -UpCCGSD is found to
show the best scaling for quantum computing applications, requiring a circuit
depth of , compared with for UCCGSD and
for UCCSD where is the number of spin
orbitals and is the number of electrons. We analyzed the accuracy of
these three ans\"atze by making classical benchmark calculations on the ground
state and the first excited state of H (STO-3G, 6-31G), HO (STO-3G),
and N (STO-3G), making additional comparisons to conventional coupled
cluster methods. The results for ground states show that -UpCCGSD offers a
good tradeoff between accuracy and cost, achieving chemical accuracy for lower
cost of implementation on quantum computers than both UCCGSD and UCCSD. Excited
states are calculated with an orthogonally constrained variational quantum
eigensolver approach. This is seen to generally yield less accurate energies
than for the corresponding ground states. We demonstrate that using a
specialized multi-determinantal reference state constructed from classical
linear response calculations allows these excited state energetics to be
improved
- …