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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Solving Unit Commitment Problems with Demand Responsive Loads

This work focuses on using variations of the Frank-Wolfe (FW) algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the timeseries of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

demand response↗
DOE OSTI2019

Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations

The growing interest in the complexity of biological interactions is continuously driving the need to increase system size in biophysical simulations, requiring not only powerful and advanced hardware but adaptable software that can accommodate a large number of atoms interacting through complex force fields. To address this, we developed and implemented strategies in the GENESIS molecular dynamics package designed for large numbers of processors. Long–range electrostatic interactions were parallelized by minimizing the number of processes involved in communication. Here, a novel algorithm was implemented for nonbonded interactions to increase single instruction multiple data (SIMD) performance, reducing memory usage for ultra large systems. Memory usage for neighbor searches in real–space nonbonded interactions was reduced by approximately 80%, leading to significant speedup. Using experimental data describing physical 3D chromatin interactions, we constructed the first atomistic model of an entire gene locus (GATA4). Taken together, these developments enabled the first billion–atom simulation of an intact biomolecular complex, achieving scaling to 65,000 processes (130,000 processor cores) with 1 ns/day performance.

3D modeling↗
DOE OSTI2014

Effective Ion Mobility Calculations for Macromolecules by Scattering off Electron Clouds

Broad commercialization and increasing resolving power of ion mobility spectrometry/mass spectrometry (IMS/MS) platforms has engendered an explosion of IMS applications to structural characterization of gas-phase biomolecules. That has renewed interest in more accurate and rapid ion mobility calculations needed to elicit ion geometries from the measurements. An approach based on scattering off electron density isosurfaces (SEDI) that mirrors the physics of molecular collisions was proven superior to the common methods involving atomic coordinates a decade ago, but has remained impractical for large ions because of extreme computational demands. Here, we accelerate SEDI by up to ~500 times using the fragment molecular orbital (FMO) approach for surface generation and the multiplexed scattering algorithm in conjunction with the new grid extrapolation procedure for cross section evaluations. Parallelization of the code on a supercomputer has produced major further speed gains, allowing SEDI calculations for proteins (defined by over a million surface points) with the precision of <0.1% in one minute. Initial tests reveal the anticipated dependences of mobility on the ion charge state and lower cross sections in view of reduced surface roughness. Present developments are expected to lead to broad application of SEDI in IMS studies of macromolecules, enabling more accurate and reliable structural assignments.

Alexeev, Yuri↗
DOE OSTI2014

Multiscale modeling of polyisoprene on graphite

The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

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. Finally, some specific chemical examples include calculations on the strongly correlated Cr 2 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.

computational modelling↗
DOE OSTI2015

Accurate modeling and inversion of electrical resistivity data in the presence of metallic infrastructure with known location and dimension

Electrical resistivity tomography (ERT) has been widely used in environmental applications to study processes associated with subsurface contaminants and contaminant remediation. Anthropogenic alterations in subsurface electrical conductivity associated with contamination often originate from highly industrialized areas with significant amounts of buried metallic infrastructure. The deleterious influence of such infrastructure on imaging results generally limits the utility of ERT where it might otherwise prove useful for subsurface investigation and monitoring. In this manuscript we present a method of accurately modeling the effects of buried conductive infrastructure within the forward modeling algorithm, thereby removing them from the inversion results. The method is implemented in parallel using immersed interface boundary conditions, whereby the global solution is reconstructed from a series of well-conditioned partial solutions. Forward modeling accuracy is demonstrated by comparison with analytic solutions. Synthetic imaging examples are used to investigate imaging capabilities within a subsurface containing electrically conductive buried tanks, transfer piping, and well casing, using both well casings and vertical electrode arrays as current sources and potential measurement electrodes. Results show that, although accurate infrastructure modeling removes the dominating influence of buried metallic features, the presence of metallic infrastructure degrades imaging resolution compared to standard ERT imaging. However, accurate imaging results may be obtained if electrodes are appropriately located.

imaging↗
DOE OSTI2016

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed with CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Hierarchical Petascale Simulation Framework For Stress Corrosion Cracking

A number of major accomplishments resulted from the project. These include: • Data Structures, Algorithms, and Numerical Methods for Reactive Molecular Dynamics. We have developed a range of novel data structures, algorithms, and solvers (amortized ILU, Spike) for use with ReaxFF and charge equilibration. • Parallel Formulations of ReactiveMD (Purdue ReactiveMolecular Dynamics Package, PuReMD, PuReMD-GPU, and PG-PuReMD) for Messaging, GPU, and GPU Cluster Platforms. We have developed efficient serial, parallel (MPI), GPU (Cuda), and GPU Cluster (MPI/Cuda) implementations. Our implementations have been demonstrated to be significantly better than the state of the art, both in terms of performance and scalability. • Comprehensive Validation in the Context of Diverse Applications. We have demonstrated the use of our software in diverse systems, including silica-water, silicon-germanium nanorods, and as part of other projects, extended it to applications ranging from explosives (RDX) to lipid bilayers (biomembranes under oxidative stress). • Open Source Software Packages for Reactive Molecular Dynamics. All versions of our soft- ware have been released over the public domain. There are over 100 major research groups worldwide using our software. • Implementation into the Department of Energy LAMMPS Software Package. We have also integrated our software into the Department of Energy LAMMPS software package.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems.

De novo genome assembly is one of the most important and challenging computational problems in modern genomics; further, it shares algorithms and communication patterns important to other graph analytic and irregular applications. Unlike simulations, it has no floating point arithmetic and is dominated by small memory transactions within and between computing nodes. In this work, we focus on the highly scalable HipMer assembler and identify the dominant algorithms and communication patterns, also using microbenchmarks to capture the workload. We evaluate HipMer on a variety of platforms from the latest HPC systems to ethernet clusters. HipMer performs well on all single node systems, including the Xeon Phi manycore architecture. Given large enough problems, it also demonstrates excellent scaling across nodes in an HPC system, but requires a high speed network with low overhead and high injection rates. Our results shed light on the architectural features that are most important for achieving good parallel efficiency on this and related problems.

Ellis, Marquita↗
DOE OSTI2013

Data communications in a parallel active messaging interface of a parallel computer

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Performance Analysis of an Optimization Algorithm for Metamaterial Design on the Integrated High-Performance Computing and Quantum Systems

Optimizing metamaterials with complex geometries is a big challenge. Although an active learning algorithm, combining machine learning (ML), quantum computing, and optical simulation, has emerged as an efficient optimization tool, it still faces difficulties in optimizing complex structures that have potentially high performance. In this work, we comprehensively analyze the performance of an optimization algorithm for metamaterial design on the integrated HPC and quantum systems. We demonstrate significant time advantages through message-passing interface (MPI) parallelization on the high-performance computing (HPC) system showing approximately 54% faster ML tasks and 67 times faster optical simulation against serial workloads. Furthermore, we analyze the performance of a quantum algorithm designed for optimization, which runs with various quantum simulators on a local computer or HPC-quantum system. Results showcase ~24 times speedup when executing the optimization algorithm on the HPC-quantum hybrid system. This study paves a way to optimize complex metamaterials using the integrated HPC-quantum system.

Kim, Seongmin↗
DOE OSTI2016

Parallel deterministic transport sweeps of structured and unstructured meshes with overloaded mesh decompositions

Here, the efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amount of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 10 5 processor cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

CAST: Contraction Algorithm for Symmetric Tensors

Tensor contractions represent the most compute-intensive core kernels in ab initio computational quantum chemistry and nuclear physics. Symmetries in these tensor contractions makes them difficult to load balance and scale to large distributed systems. In this paper, we develop an efficient and scalable algorithm to contract symmetric tensors. We introduce a novel approach that avoids data redistribution in contracting symmetric tensors while also avoiding redundant storage and maintaining load balance. We present experimental results on two parallel supercomputers for several symmetric contractions that appear in the CCSD quantum chemistry method. We also present a novel approach to tensor redistribution that can take advantage of parallel hyperplanes when the initial distribution has replicated dimensions, and use collective broadcast when the final distribution has replicated dimensions, making the algorithm very efficient.

distributed memory↗
DOE OSTI2025

Communication Lower Bounds and Optimal Algorithms for Symmetric Matrix Computations

In this article, we focus on the communication costs of three symmetric matrix computations: (i) multiplying a matrix with its transpose, known as a symmetric rank-k update (SYRK) (ii) adding the result of the multiplication of a matrix with the transpose of another matrix and the transpose of that result, known as a symmetric rank-2k update (SYR2K) (iii) performing matrix multiplication with a symmetric input matrix (SYMM). All three computations appear in the Level 3 Basic Linear Algebra Subroutines (BLAS) and have wide use in applications involving symmetric matrices. We establish communication lower bounds for these kernels using sequential and distributed-memory parallel computational models, and we show that our bounds are tight by presenting communication-optimal algorithms for each setting. Our lower bound proofs rely on applying a geometric inequality for symmetric computations and analytically solving constrained nonlinear optimization problems. As a result, the symmetric matrix and its corresponding computations are accessed and performed according to a triangular block partitioning scheme in the optimal algorithms.

Al Daas, Hussam [Rutherford Appleton Laboratory, D↗
DOE OSTI2020

Portable interactive visualization of large-scale simulations in geotechnical engineering using Unity3D

Development in large-scale geotechnical engineering simulation places tremendous demand for efficient visualization of such simulation data. This study presents a lightweight software tool, i.e. Geotechnical Interactive Visualization (GIV), as a solution to this challenge, which achieves efficient interactive visualization of large-scale simulations data in geotechnical engineering. Visualization data flow and algorithms specifically optimized for common geotechnical engineering applications are implemented in GIV. GIV can visualize geotechnical structure models with time-varying attributes attached to mesh with fixed topology, and also models with time-varying mesh topologies but no attributes attached, the two most common visualization tasks in geotechnical engineering. Furthermore, challenges for large-scale simulation data visualization, including parallel simulation data redundancy, massive data size, dynamic user interaction, and portability are overcome via specifically designed algorithms for simulation data preprocessing and optimized visualization modules using the powerful 3D rendering and interactive game engine Unity3D. Comparison of GIV with several widely used visualization tools for the visualization of large-scale idealized datasets and realistic geotechnical simulations highlights the visualization efficiency, smooth interactivity, and lightweight features of GIV.

42 ENGINEERING↗