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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Runtime Techniques to Enable a Highly-Scalable Global Address Space Model for Petascale Computing

Over the past decade, the trajectory to the petascale has been built on increased complexity and scale of the underlying parallel architectures. Meanwhile, software developers have struggled to provide tools that maintain the productivity of computational science teams using these new systems. In this regard, Global Address Space (GAS) programming models provide a straightforward and easy to use addressing model, which can lead to improved productivity. However, the scalability of GAS depends directly on the design and implementation of the runtime system on the target petascale distributed-memory architecture. In this paper, we describe the design, implementation, and optimization of the Aggregate Remote Memory Copy Interface (ARMCI) runtime library on the Cray XT5 2.3 PetaFLOPs computer at Oak Ridge National Laboratory. We optimized our implementation with the flow intimation technique that we have introduced in this paper. Our optimized ARMCI implementation improves scalability of both the Global Arrays programming model and a real-world chemistry application—NWChem—from small jobs up through 180,000 cores.

Computer Science↗
DOE OSTI2012

A DISLOCATION-BASED CLEAVAGE INITIATION MODEL FOR PRESSURE VESSEL

Efforts are under way to develop a theoretical, multi-scale model for the prediction of fracture toughness of ferritic steels in the ductile-to-brittle transition temperature (DBTT) region that accounts for temperature, irradiation, strain rate, and material condition (chemistry and heat treatment) effects. This new model is intended to address difficulties associated with existing empirically-derived models of the DBTT region that cannot be extrapolated to conditions for which data are unavailable. Dislocation distribution equations, derived from the theories of Yokobori et al., are incorporated to account for the local stress state prior to and following initiation of a microcrack from a second-phase particle. The new model is the basis for the DISlocation-based FRACture (DISFRAC) computer code being developed at the Oak Ridge National Laboratory (ORNL). The purpose of this code is to permit fracture safety assessments of ferritic structures with only tensile properties required as input. The primary motivation for the code is to assist in the prediction of radiation effects on nuclear reactor pressure vessels, in parallel with the EURATOM PERFORM 60 project.

Cochran, Kristine B↗
DOE OSTI2022

Constant-potential molecular dynamics simulations of molten salt double layers for FLiBe and FLiNaK

We report the results of constant-potential molecular dynamics simulations of the double layer interface between molten 2LiF–BeF 2 (FLiBe) and 23LiF–6NaF–21KF (FLiNaK) fluoride mixtures and idealized solid electrodes. Employing methods similar to those used in studies of chloride double layers, we compute the structure and differential capacitance of molten fluoride electric double layers as a function of applied voltage. The role of molten salt structure is probed through comparisons between FLiBe and FLiNaK, which serve as models for strong and weak associate-forming salts, respectively. In FLiBe, screening involves changes in Be–F–Be angles and alignment of the oligomers parallel to the electrode, while in FLiNaK, the electric field is screened mainly by rearrangement of individual ions, predominantly the polarizable potassium cation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Computational Study of RNA Tetraloop Thermodynamics, Including Misfolded States

An important characteristic of RNA folding is the adoption of alternative configurations of similar stability, often referred to as misfolded configurations. These configurations are considered to compete with correctly folded configurations, although their rigorous thermodynamic and structural characterization remains elusive. Tetraloop motifs found in large ribozymes are ideal systems for an atomistically detailed computational quantification of folding free energy landscapes and the structural characterization of their constituent free energy basins, including nonnative states. In this work, we studied a group of closely related 10-mer tetraloops using a combined parallel tempering and metadynamics technique that allows a reliable sampling of the free energy landscapes, requiring only knowledge that the stem folds into a canonical A-RNA configuration. Here we isolated and analyzed unfolded, folded, and misfolded populations that correspond to different free energy basins. We identified a distinct misfolded state that has a stability very close to that of the correctly folded state. This misfolded state contains a predominant population that shares the same structural features across all tetraloops studied here and lacks the noncanonical A-G base pair in its loop portion. Further analysis performed with biased trajectories showed that although this competitive misfolded state is not an essential intermediate, it is visited in most of the transitions from unfolded to correctly folded states. Moreover, the tetraloops can transition from this misfolded state to the correctly folded state without requiring extensive unfolding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Computational determination of the pigment binding motif in the chlorosome protein a of green sulfur bacteria

We present a molecular-scale model of Bacteriochlorophyll a (BChl a) binding to the chlorosome protein A (CsmA) of Chlorobaculum tepidum, and the aggregated pigment–protein dimer, as determined from protein–ligand docking and quantum chemistry calculations. Our calculations provide strong evidence that the BChl a molecule is coordinated to the His25 residue of CsmA, with the magnesium center of the bacteriochlorin ring situated <3 Å from the imidazole nitrogen atom of the histidine sidechain, and the phytyl tail aligned along the nonpolar residues of the α-helix of CsmA. We also confirm that the Q y band in the absorption spectra of BChl a experiences a large (+16 to +43 nm) redshift when aggregated with another BChl a molecule in the CsmA dimer, compared to the BChl a in solvent; this redshift has been previously established by experimental researchers. We propose that our model of the BChl a–CsmA binding motif, where the dimer contains parallel aligned N-terminal regions, serves as the smallest repeating unit in a larger model of the para-crystalline chlorosome baseplate protein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The hydrogen tunneling splitting in malonaldehyde: A full-dimensional time-independent quantum mechanical method

The accurate time-independent quantum dynamics calculations on the ground-state tunneling splitting of malonaldehyde in full dimensionality are reported for the first time. This is achieved with an efficient method developed by us. In our method, the basis functions are customized for the hydrogen transfer process which has the effect of greatly reducing the size of the final Hamiltonian matrix, and the Lanczos method and parallel strategy are used to further overcome the memory and central processing unit time bottlenecks. The obtained ground-state tunneling splitting of 24.5 cm{sup −1} is in excellent agreement with the benchmark value of 23.8 cm{sup −1} computed with the full-dimensional, multi-configurational time-dependent Hartree approach on the same potential energy surface, and we estimate that our reported value has an uncertainty of less than 0.5 cm{sup −1}. Moreover, the role of various vibrational modes strongly coupled to the hydrogen transfer process is revealed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Fine-Tuning the Activity of Metal–Organic Framework Supported Cobalt Catalysts for the Oxidative Dehydrogenation of Propane

Few-atom cobalt-oxide clusters, when dispersed on a Zr-based metal–organic framework (MOF) NU-1000, have previously been shown to be active for the oxidative dehydrogenation (ODH) of propane at low temperatures (< 230 °C), affording a selective and stable propene production catalyst. In our current work, a series of promoter ions with varying Lewis acidity, including Ni(II), Zn(II), Al(III), Ti(IV) and Mo(VI), are anchored as metal-oxide,hydroxide clusters to NU-1000 via SIM (solvothermal deposition within MOFs–specifically the nodes) followed by incorporation of Co(II) ions via vapor-phase AIM (atomic layer deposition (ALD) in MOFs). This process yields a series of NU-1000-supported bimetallic-oxo,hydroxo,aqua clusters. Using difference envelope density (DED) analyses, the spatial locations of the promoter ions and catalytic cobalt ions are determined. For all samples the SIM-anchored promoter ions are sited between pairs of Zr 6 nodes along the MOF c-axis (channel-aligned axis) whereas the location of the AIM-anchored cobalt ions varies depending on the identity of promoter metal ion. With Ni(II)-, Al(III)-, or Ti(IV)-containing clusters as promoters, the oxy-cobalt species are sited atop the promoter sites; with Mo(VI) they grow exclusively on the MOF nodes sites (hexa-Zr(IV)- oxo,hydroxo,aqua units); with Zn(II) they grow on both the node and promoter. The NU-1000- supported bimetallic-oxide clusters are active for propane ODH after thermal activation under O 2 to open a cobalt coordination site and to oxidize Co(II) to Co(III), as evidenced by operando Xray absorption spectroscopy at the Co K-edge. The cobalt component is exclusively responsible for the observed catalysis. In accord with the decreasing Lewis acidity of the promoter ion, catalytic activity increases in the order: Mo(VI)<Ti(IV)<Al(III)<Zn(II)<Ni(II). The finding is attributed to increasing ease of formation Co(III)-O• species and stabilization of a cobalt(III)- oxyl/propane transition state as the Lewis acidity of the promoter ions decreases. (The promoterfree catalyst is sited on the oxy-Zr(IV) node of the MOF and is inferior catalytically to the strongly promoted versions of the catalyst.) The relative Lewis acidities of the promoters are inferred from the initial pKa values of aqua complexes of the corresponding single metal ions. Departures from the (ODH-rate)/(promoter-pKa) correlation are paralleled by differences in cobalt catalyst siting or structure. The combined results point to an increasing ability to fine-tune, with close to atomic specificity, the structure-dependent activity of MOF-supported heterogeneous catalysts for gas phase chemical reactions. When coupled with mechanistic studies–computational or experimental–this ability may translate into informed prediction of improved catalysts for propane ODH and other chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Graph-based linear scaling electronic structure theory

We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broad range of electronic structure methods and materials, including challenging systems such as biomolecules. The methodology combines well-controlled accuracy, low computational cost, and natural low-communication parallelism. This combination addresses substantial shortcomings of linear scaling electronic structure theory, in particular with respect to quantum-based molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, in the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

Abstract The PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Chemistry↗
DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Composite Behavior of Nanopore Array Large Memristors

Synthetic nanopores were recently demonstrated with memristive and nonlinear voltage-current behaviors, akin to ion channels in a cell membrane. Such ionic devices are considered a promising candidate for the development of brain-inspired neuromorphic computing techniques. In this work, we show the composite behavior of nanopore-array large memristors, formed with different membrane materials, pore sizes, electrolytes, and device arrangements. Anodic aluminum oxide (AAO) membranes with 5 nm and 20 nm diameter pores and track-etched polycarbonate (PCTE) membranes with 10 nm diameter pores are tested and shown to demonstrate memristive and nonlinear behaviors with approximately 107–1010 pores in parallel when electrolyte concentration across the membranes is asymmetric. Ion diffusion through the large number of channels induces time-dependent electrolyte asymmetry that drives the system through different memristive states. The behaviors of series composite memristors with different configurations are also presented. In addition to helping understand fluidic devices and circuits for neuromorphic computing, the results also shed light on the development of field-assisted ion-selection-membrane filtration techniques as well as the investigations of large neurons and giant synapses. Further work is needed to de-embed parasitic components of the measurement setup to obtain intrinsic large memristor properties.

Chemistry↗
DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗
DOE OSTI2020

The Generality of the GUGA MRCI Approach in COLUMBUS for Treating Complex Quantum Chemistry

The core part of the program system COLUMBUS allows highly efficient calculations using variational multireference (MR) methods in the framework of configuration interaction with single and double excitations (MR-CISD) and averaged quadratic coupled-cluster calculations (MR-AQCC), based on uncontracted sets of configurations and the graphical unitary group approach (GUGA). The availability of analytic MR-CISD and MR-AQCC energy gradients and analytic nonadiabatic couplings for MR-CISD enables exciting applications including, e.g., investigations of π-conjugated biradicaloid compounds, calculations of multitudes of excited states, development of diabatization procedures, and furnishing the electronic structure information for on-the-fly surface nonadiabatic dynamics. With fully variational uncontracted spin-orbit MRCI, COLUMBUS provides a unique possibility of performing high-level calculations on compounds containing heavy atoms up to lanthanides and actinides. Crucial for carrying out all of these calculations effectively is the availability of an efficient parallel code for the CI step. Configuration spaces of several billion in size now can be treated quite routinely on standard parallel computer clusters. Emerging developments in COLUMBUS, including the all configuration mean energy multiconfiguration self-consistent field method and the graphically contracted function method, promise to allow practically unlimited configuration space dimensions. Spin density based on the GUGA approach, analytic spin-orbit energy gradients, possibilities for local electron correlation MR calculations, development of general interfaces for nonadiabatic dynamics, and MRCI linear vibronic coupling models conclude this overview.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Accurate quantum dynamics calculations using symmetrized Gaussians on a doubly dense Von Neumann lattice

In a series of earlier articles [B. Poirier, J. Theor. Comput. Chem. 2, 65 (2003); B. Poirier and A. Salam, J. Chem. Phys. 121, 1690 (2004); and ibid. 121, 1704 (2004)], a new method was introduced for performing exact quantum dynamics calculations. The method uses a 'weylet' basis set (orthogonalized Weyl-Heisenberg wavelets) combined with phase space truncation, to defeat the exponential scaling of CPU effort with system dimensionality-the first method ever able to achieve this long-standing goal. Here, we develop another such method, which uses a much more convenient basis of momentum-symmetrized Gaussians. Despite being non-orthogonal, symmetrized Gaussians are collectively local, allowing for effective phase space truncation. A dimension-independent code for computing energy eigenstates of both coupled and uncoupled systems has been created, exploiting massively parallel algorithms. Results are presented for model isotropic uncoupled harmonic oscillators and coupled anharmonic oscillators up to 27 dimensions. These are compared with the previous weylet calculations (uncoupled harmonic oscillators up to 15 dimensions), and found to be essentially just as efficient. Coupled system results are also compared to corresponding exact results obtained using a harmonic oscillator basis, and also to approximate results obtained using first-order perturbation theory up to the maximum dimensionality for which the latter may be feasibly obtained (four dimensions).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Energy-Screened Many-Body Expansion: A Practical Yet Accurate Fragmentation Method for Quantum Chemistry

We introduce an implementation of the truncated many-body expansion, MBE(n), in which the n-body corrections are screened using the effective fragment potential force field, and only those that exceed a specified energy threshold are computed at a quantum-mechanical level of theory. This energy-screened MBE(n) approach is tested at the n = 3 level for a sequence of water clusters, (H2O) N=6–34 . A threshold of 0.25 kJ/mol eliminates more than 80% of the subsystem electronic structure calculations and is even more efficacious in that respect than is distance-based screening. Even so, the energy-screened MBE(3) method is faithful to a full-system quantum chemistry calculation to within 1–2 kJ/mol/monomer, even in good quality basis sets such as aug-cc-pVTZ. These errors can be reduced by means of a two-layer approach that involves a Hartree–Fock calculation for the entire cluster. Such a correction proves to be necessary in order to obtain accurate relative energies for conformational isomers of (H2O)20, but the cost of a full-system Hartree–Fock calculation remains smaller than the cost of three-body subsystem calculations at correlated levels of theory. At the level of second-order Møller–Plesset perturbation theory (MP2), a screened MBE(3) calculation plus a full-system Hartree–Fock calculation is less expensive than a full-system MP2 calculation starting at N = 12 water molecules. This is true even if all MBE(3) subsystem calculations are performed on a single 40-core compute node, i.e., without significant parallelization. Energy-screened MBE(n) thus provides a fragment-based method that is accurate, stable in large basis sets, and low in cost, even when the latter is measured in aggregate computer time.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Electronic Structure and Properties of Berkelium Iodates

The reaction of 249 Bk(OH) 4 with iodate under hydrothermal conditions results in the formation of Bk(IO 3 ) 3 as the major product with trace amounts of Bk(IO 3 ) 4 also crystallizing from the reaction mixture. The structure of Bk(IO 3 ) 3 consists of nine-coordinate Bk III cations that are bridged by iodate anions to yield layers that are isomorphous with those found for Am III , Cf III , and with lanthanides that possess similar ionic radii. Bk(IO 3 ) 4 was expected to adopt the same structure as M(IO 3 ) 4 (M = Ce, Np, Pu), but instead parallels the structural chemistry of the smaller Zr IV cation. Bk III –O and Bk IV –O bond lengths are shorter than anticipated and provide further support for a postcurium break in the actinide series. Photoluminescence and absorption spectra collected from single crystals of Bk(IO 3 ) 4 show evidence for doping with Bk III in these crystals. In addition to luminescence from Bk III in the Bk(IO 3 ) 4 crystals, a broad-band absorption feature is initially present that is similar to features observed in systems with intervalence charge transfer. However, the high-specific activity of 249 Bk ( t 1/2 = 320 d) causes oxidation of Bk III and only Bk IV is present after a few days with concomitant loss of both the BkIII luminescence and the broadband feature. The electronic structure of Bk(IO 3 ) 3 and Bk(IO 3 ) 4 were examined using a range of computational methods that include density functional theory both on clusters and on periodic structures, relativistic ab initio wave function calculations that incorporate spin–orbit coupling (CASSCF), and by a full-model Hamiltonian with spin–orbit coupling and Slater–Condon parameters (CONDON). Some of these methods provide evidence for an asymmetric ground state present in Bk IV that does not strictly adhere to Russel–Saunders coupling and Hund’s Rule even though it possesses a half-filled 5 f 7 shell. Multiple factors contribute to the asymmetry that include 5 f electrons being present in microstates that are not solely spin up, spin–orbit coupling induced mixing of low-lying excited states with the ground state, and covalency in the Bk IV –O bonds that distributes the 5f electrons onto the ligands. These factors are absent or diminished in other f 7 ions such as Gd III or Cm III .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Subspace recursive Fermi-operator expansion strategies for large-scale DFT eigenvalue problems on HPC architectures

Quantum mechanical calculations for material modeling using Kohn–Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for N smallest eigenvector-eigenvalue pairs, with N proportional to the number of electrons in the material system. Here, these calculations are computationally demanding and have asymptotic cubic scaling complexity with the number of electrons. Large-scale matrix eigenvalue problems arising from the discretization of the Kohn–Sham DFT equations employing a systematically convergent basis traditionally rely on iterative orthogonal projection methods, which are shown to be computationally efficient and scalable on massively parallel computing architectures. However, as the size of the material system increases, these methods are known to incur dominant computational costs through the Rayleigh–Ritz projection step of the discretized Kohn–Sham Hamiltonian matrix and the subsequent subspace diagonalization of the projected matrix. This work explores the potential of polynomial expansion approaches based on recursive Fermi-operator expansion as an alternative to the subspace diagonalization of the projected Hamiltonian matrix to reduce the computational cost. Subsequently, we perform a detailed comparison of various recursive polynomial expansion approaches to the traditional approach of explicit diagonalization on both multi-node central processing unit and graphics processing unit architectures and assess their relative performance in terms of accuracy, computational efficiency, scaling behavior, and energy efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗