Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “compute intensive problems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering

Abstract The SAT problem is a prototypical NP-complete problem of fundamental importance in computational complexity theory with many applications in science and engineering; as such, it has long served as an essential benchmark for classical and quantum algorithms. This study shows numerical evidence for a quadratic speedup of the Grover Quantum Approximate Optimization Algorithm (G-QAOA) over random sampling for finding all solutions to 3-SAT (All-SAT) and Max-SAT problems. G-QAOA is less resource-intensive and more adaptable for these problems than Grover’s algorithm, and it surpasses conventional QAOA in its ability to sample all solutions. We show these benefits by classical simulations of many-round G-QAOA on thousands of random 3-SAT instances. We also observe G-QAOA advantages on the IonQ Aria quantum computer for small instances, finding that current hardware suffices to determine and sample all solutions. Interestingly, a single-angle-pair constraint that uses the same pair of angles at each G-QAOA round greatly reduces the classical computational overhead of optimizing the G-QAOA angles while preserving its quadratic speedup. We also find parameter clustering of the angles. The single-angle-pair protocol and parameter clustering significantly reduce obstacles to classical optimization of the G-QAOA angles.

Zhang, Zewen (ORCID:000000032258613X)↗
DOE OSTI2015

Multi-layer Lanczos iteration approach to calculations of vibrational energies and dipole transition intensities for polyatomic molecules

We report a rigorous full dimensional quantum dynamics algorithm, the multi-layer Lanczos method, for computing vibrational energies and dipole transition intensities of polyatomic molecules without any dynamics approximation. The multi-layer Lanczos method is developed by using a few advanced techniques including the guided spectral transform Lanczos method, multi-layer Lanczos iteration approach, recursive residue generation method, and dipole-wavefunction contraction. The quantum molecular Hamiltonian at the total angular momentum J = 0 is represented in a set of orthogonal polyspherical coordinates so that the large amplitude motions of vibrations are naturally described. In particular, the algorithm is general and problem-independent. An application is illustrated by calculating the infrared vibrational dipole transition spectrum of CH{sub 4} based on the ab initio T8 potential energy surface of Schwenke and Partridge [Spectrochimica Acta, Part A 57, 887 (2001)] and the low-order truncated ab initio dipole moment surfaces of Yurchenko et al. [J. Mol. Spectrosc. 291, 69 (2013)]. A comparison with experiments is made. The algorithm is also applicable for Raman polarizability active spectra.

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

Thick diffusion limit boundary layer test problems

We develop two simple test problems that quantify the behavior of computational transport solutions in the presence of boundary layers that are not resolved by the spatial grid. In particular we study the quantitative effects of 'contamination' terms that, according to previous asymptotic analyses, may have a detrimental effect on the solutions obtained by both discontinuous finite element (DFEM) and characteristic-method (CM) spatial discretizations, at least for boundary layers caused by azimuthally asymmetric incident intensities. Few numerical results have illustrated the effects of this contamination, and none have quantified it to our knowledge. Our test problems use leading-order analytic solutions that should be equal to zero in the problem interior, which means the observed interior solution is the error introduced by the contamination terms. Results from DFEM solutions demonstrate that the contamination terms can cause error propagation into the problem interior for both orthogonal and non-orthogonal grids, and that this error is much worse for non-orthogonal grids. This behavior is consistent with the predictions of previous analyses. We conclude that these boundary layer test problems and their variants are useful tools for the study of errors that are introduced by unresolved boundary layers in diffusive transport problems. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Single-shot tomographic movies of evolving light-velocity objects

Tomography—cross-sectional imaging based on measuring radiation transmitted through an object along different directions—enables non-invasive imaging of hidden stationary objects, such as internal bodily organs, from their sequentially measured projections. Here we adapt tomographic methods to visualize—in one laser shot—the instantaneous structure and evolution of a laser-induced object propagating through a transparent Kerr medium. We reconstruct ‘movies’ of a laser pulse’s diffraction, self-focusing and filamentation from phase ‘streaks’ imprinted onto probe pulses that cross the main pulse’s path simultaneously at different angles. Multiple probes are generated and detected compactly and simply, making the system robust, easy to align and adaptable to many problems. Our technique could potentially visualize, for example, plasma wakefield accelerators, optical rogue waves or fast ignitor pulses, light-velocity objects, whose detailed space–time dynamics are known only through intensive computer simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Imaging for dismantlement verification: information management and analysis algorithms

The level of detail discernible in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes. An image will almost certainly contain highly sensitive information, and storing a comparison image will almost certainly violate a cardinal principle of information barriers: that no sensitive information be stored in the system. To overcome this problem, some features of the image might be reduced to a few parameters suitable for definition as an attribute. However, this process must be performed with care. Computing the perimeter, area, and intensity of an object, for example, might reveal sensitive information relating to shape, size, and material composition. This paper presents three analysis algorithms that reduce full image information to non-sensitive feature information. Ultimately, the algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We evaluate the algorithms on both their technical performance in image analysis, and their application with and without an explicitly constructed information barrier. The underlying images can be highly detailed, since they are dynamically generated behind the information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1990

Real-time fuzzy inference based robot path planning

This project addresses the problem of adaptive trajectory generation for a robot arm. Conventional trajectory generation involves computing a path in real time to minimize a performance measure such as expended energy. This method can be computationally intensive, and it may yield poor results if the trajectory is weakly constrained. Typically some implicit constraints are known, but cannot be encoded analytically. The alternative approach used here is to formulate domain-specific knowledge, including implicit and ill-defined constraints, in terms of fuzzy rules. These rules utilize linguistic terms to relate input variables to output variables. Since the fuzzy rulebase is determined off-line, only high-level, computationally light processing is required in real time. Potential applications for adaptive trajectory generation include missile guidance and various sophisticated robot control tasks, such as automotive assembly, high speed electrical parts insertion, stepper alignment, and motion control for high speed parcel transfer systems.

Pacini, Peter J.↗
NASA NTRS1992

Automating FEA programming

In this paper we briefly describe a combined symbolic and numeric approach for solving mathematical models on parallel computers. An experimental software system, PIER, is being developed in Common Lisp to synthesize computationally intensive and domain formulation dependent phases of finite element analysis (FEA) solution methods. Quantities for domain formulation like shape functions, element stiffness matrices, etc., are automatically derived using symbolic mathematical computations. The problem specific information and derived formulae are then used to generate (parallel) numerical code for FEA solution steps. A constructive approach to specify a numerical program design is taken. The code generator compiles application oriented input specifications into (parallel) FORTRAN77 routines with the help of built-in knowledge of the particular problem, numerical solution methods and the target computer.

Sharma, Naveen↗
DOE OSTI2021

Designing Energy-Efficient Quantum Computers Through Prediction and Reduction of Cooling Requirements for Cryogenic Electronics

Quantum computing has been identified as a “wild card” by the International Energy Agency in predicting future global data center energy usage. This is primarily because both uncertainty in the extent to which quantum computing will be adopted, and uncertainty in the power consumption of individual quantum data centers. Unlike the classical counterparts, quantum computers need to be maintained at near absolute zero, requiring energy-intensive cryogenic cooling systems. Therefore, as quantum computers scale up from existing 50 qubit technology demonstrations to the 10,000 to 100,000 qubit systems that will be able to solve complex problems, the energy consumption of both the electronics and the required cooling systems will also increase. To predict this scaling, this work analyzes the energy requirements for both computation and cooling of quantum hardware. We show that the energy requirements for cooling of quantum computers is determined by several computing system parameters, including the number and type of physical qubits, the operating temperature, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. The energy requirements can then be found based on thermal system parameters such as cooling efficiency and cryostat heat transfer. Analysis of these parameters shows that the energy required for cooling is significantly larger than that required for computation, a reversal from energy usage patterns seen in conventional computing. The results and discussions provide a road-map for creating energy efficient quantum computers through the selection of computer architectures and cryogenic system configurations that minimize cooling requirements.

energy efficiency↗
DOE OSTI2018

Analysis of Nonclassical Fracture Problems for Prestressed Bodies with Interacting Cracks

We consider two types of nonclassical fracture mechanisms, namely, the fracture of cracked bodies with initial (residual) stresses acting along the crack planes and the fracture of solids under compression along parallel cracks. To investigate nonaxisymmetric and axisymmetric problems for infinite solids containing two parallel coaxial cracks or a periodic set of coaxial parallel cracks, we use a combined analytic-numerical method within the framework of the three-dimensional linearized mechanics of solids. The analysis involves the representation of stresses and displacements in the linearized theory via harmonic potential functions. With the use of the integral Fourier–Hankel transformations, the problems are reduced to the solution of Fredholm integral equations of the second kind. This approach allows us to investigate problems in a unified general form for compressible and noncompressible homogeneous isotropic or transversely isotropic elastic bodies with an arbitrary structure of the elastic potential, and the material specification of the model is carried out only in the stage of numerical analysis of the resolving equations obtained in the general form. The effects of initial stresses on the stress intensity factors are analyzed for highly elastic materials and layered composites (modeled as transversely isotropic elastic bodies). The “resonance-like” effects are revealed when compressive initial stresses reach the values corresponding to the local loss of stability of the material in the vicinity of cracks, which, according to the indicated combined method, allows one to determine the critical (limiting) load parameters under the conditions of compression of the body along the cracks. The conclusions concerning the dependences of the stress intensity factors and critical (limiting) parameters of compression on the geometric parameters of the problems are formulated as well as concerning the dependences on physical and mechanical characteristics of the materials.

42 ENGINEERING↗
DOE OSTI2024

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Abstract Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Queuing theory models for computer networks

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

Galant, David C.↗
DOE OSTI2013

20 petaflops simulation of proteins suspensions in crowding conditions, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

We present performance results for the simulation of proteins suspensions in crowding conditions obtained with MUPHY, a computational platform for multi-scale simulations of real-life biofluidic problems. Previous versions of MUPHY have been used in the past for the simulation of blood flow through the human coronary arteries and DNA translocation across nanopores. The simulation exhibits excellent scalability up to 18, 000 K20X Nvidia GPUs and achieves almost 20 Petaflops of aggregate sustained performance with a peak performance of 27.5 Petaflops for the most intensive computing component. Those figures demonstrate once again the flexibility of MUPHY in simulating biofluidic phenomena, exploiting at their best the features of the architecture in use. Preliminary results were obtained in the present case on a completely different platform, the IBM Blue Gene/Q. The combination of novel mathematical models, computational algorithms, hardware technology, code tuning and parallelization techniques required to achieve these results are presented.

Computer Science↗
DOE OSTI2022

Understanding Strong Scaling on GPUs Using Empirical Performance Saturation Size

The roofline model provides a concise overview of the maximum performance capabilities of a given computer system through a combination of peak memory bandwidth and compute performance rates. The increasing complexity of scheduling and cache in recent GPUs, however, has introduced complicated performance variability that is not captured by arithmetic intensity alone. This work examines the effect of problem size and GPU launch configurations on roofline performance for V100, A100, MI100, and MI250X graphics processing units. We introduce an extended roofline model that takes problem size into account, and find that strong scaling on GPUs can be characterized by saturation problem sizes as additional key metrics. Saturation problem sizes break up a plot of GPU performance vs. problem size into three distinct performance regimes– size-limited, cache-bound, and DRAM-bound. With our extended roofline model, we are able to provide a robust view of these performance regimes across recent GPU architectures.

Eberius, David↗
NASA NTRSDate not supplied

Deep Neural Network Based Unsteady Flamelet Progress Variable Approach in a Supersonic Combustor

Higher dimensional flamelet manifolds are essential in capturing the coupled effects of pressure gradients and unsteady chemical kinetics observed in supersonic combustion applications. Previous studies have validated the feasibility of using deep neural networks as an alternative to computation-ally intensive multidimensional flamelet table storage and lookup. This approach has demonstrated a significant reduction in memory footprint and enabled the use of larger dimensional tabulated manifolds for supersonic combustion in canonical problems. In this study, the Unsteady Flamelet Progress Variable (UFPV)-ANN model implemented in the VULCAN-CFD code is validated by the Burrows-Kurkov supersonic mixing/combustion configuration. The well characterized experimental problem consists of hydrogen injection into a supersonic vitiated crossflow that results in a lifted flame structure. The initial model consists of a 4-dimensional table where the independent variables Z, C, Xst, P are tabulated using an unsteady flamelet code with boundary conditions corresponding to the vitiated air conditions. The results show the development of a lifted flame structure and over-all acceptable agreement with finite-rate chemistry (FRC) simulation and the experimental data. Moreover, direct mapping between the independent variables and the flamelet table is replaced by a deep neural network for significant memory reduction. The results indicate that the UFPV-ANN approach can retrieve the same solution as the memory intensive lookup table approach.

Flamelet↗
DOE OSTI2016

Fourier Analysis of the Multilevel QD Method with {alpha}-Approximation For Time-Dependent Radiative Transfer Problems

Thermal radiation transfer (TRT) problems describe interaction of photon radiation with matter. They are defined by the time-dependent radiative transfer (RT) equation for the specific intensity I coupled with the energy balance (EB) equation. This class of problems is characterised by high dimensionality, multiple scales and strong nonlinearity. In this paper we analyze the multilevel quasi-diffusion (QD) method for solving TRT problems. This is a nonlinear method of moments with exact closures. The QD method enables one to reduce dimensionality of the original radiative transfer problem. It is formulated by a nonlinear system of equations consisting of (i) the high-order RT (HORT) equation for the intensity of photon radiation and (ii) low-order equations for the angular and energy moments of the intensity. The nonlinear closures are formulated by means of stable factors. The low-order problem brings the radiative transfer model to the level of multi-physics equations. The multilevel QD (MLQD) method possesses attractive features for efficient multi-physics coupling. To calculate the high-order RT solution we apply the {alpha}-approximation which assumes that the intensity changes exponentially in time over a time step. The {alpha}-approximation leads to the steady-state RT equation with a modified opacity and enables one to avoid storing the high-dimensional solution from the previous time step. The rate of change is evaluated by the solution of the time-dependent low-order QD (LOQD) equations for moments. We note that the HORT equation in the {alpha}-approximation contains an extra nonlinear term. It affects the iterative behaviour of the MLQD method. The obtained computational results indicated that the rate of convergence is slower compared to the rate when the time-dependent HORT is used to calculate the intensity. In this paper we perform an iterative stability analysis of the MLQD method in a discretized form and analyze convergence of outer (transport) iterations on a time step. We consider multigroup TRT problems in 1D slab geometry. The fully implicit scheme is used to discretize equations in time. The HORT equation is approximated with the method of step characteristics. A finite volume method is applied for spatial discretization of multigroup LOQD equations. The grey (one-group) LOQD equations are algebraically consistent with the multigroup LOQD equations. To perform Fourier analysis a model TRT problem in an infinite homogeneous medium is considered. The system of nonlinear equations of the MLQD method is linearized near an equilibrium solution at some given temperature. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Closures and Simulation for Thermal Radiation Transport in Stochastic Media with Nonlinear Temperature Dependence

Because of the practical challenge of rendering very complex realistic spatial structures for numerical work, it is common practice to resort to characterizing such media as stochastic mixtures of materials, ideally parametrized with low order statistics such as the mean, variance, and correlation functions of the now random material properties. This enables realizations of the medium to be repeatedly generated and radiation transport computations to, in principle, be performed for a large ensemble of these realizations to obtain a statistically well-characterized radiation field. Statistical post-processing yields desired quantities such as conditional and unconditional mean radiation flux and probability distributions of transmitted radiation. However, such computations prove expensive for all but the simplest stochastic geometries and are most suited for benchmarking approximate models. The most common approximations lead to homogenized media so that transport computations are required only on a single medium realization but by construct provide only limited statistical information on the radiation field. Almost all approximate approaches to this problem attempt to develop equations for low order moments of the radiation intensity (mean, second moment, correlation function) but inevitably encounter a closure problem: the equation for any statistical moment will contain terms depending on unknown higher-order moments. Thus, the challenge shifts to one of developing closure relations that relate the unknown moments to the lower order moments. Under very special conditions, an exact closure can be derived but in general closures are heuristically stated constitutive relations. Also, closure approaches depend on whether the mixing statistics are spatially and/or temporally continuous as in fluctuating turbulent fields, or discontinuous as in randomly mixed solid chunks of material. Thus, unconditional averaging is generally applied in the former case but conditional averaging is more appropriate when the mixing is discontinuous. In this work, the emphasis is on binary statistical mixtures of immiscible fluids as as such the quantities of interest are averages (flux, temperature) conditioned on the material type.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

An algorithm to correct saturated mass spectrometry ion abundances for enhanced quantitation and mass accuracy in omic studies

The mass accuracy and peak intensity of ions detected by mass spectrometry (MS) measurements are essential to facilitate compound identification and quantitation. However, high concentration species can easily cause problems if their ion intensities reach beyond the limits of the detection system, leading to distorted and non-ideal detector response (e.g. saturation), and largely precluding the calculation of accurate m/z and intensity values. Here we present an open source computational method to correct peaks above a defined intensity (saturated) threshold determined by the MS instrumentation such as the analog-to-digital converters or time-to-digital converters used in conjunction with time-of-flight MS. In this method, the isotopic envelope for each observed ion above the saturation threshold is compared to its expected theoretical isotopic distribution. The most intense isotopic peak for which saturation does not occur is then utilized to re-calculate the precursor m/z and correct the intensity, resulting in both higher mass accuracy and greater dynamic range. The benefits of this approach were evaluated with proteomic and lipidomic datasets of varying complexities. After correcting the high concentration species, reduced mass errors and enhanced dynamic range were observed for both simple and complex omic samples. Specifically, the mass error dropped by more than 50% in most cases with highly saturated species and dynamic range increased by 1-2 orders of magnitude for peptides in a blood serum sample.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2010

2009 ALCF annual report.

This year the Argonne Leadership Computing Facility (ALCF) delivered nearly 900 million core hours of science. The research conducted at their leadership class facility touched our lives in both minute and massive ways - whether it was studying the catalytic properties of gold nanoparticles, predicting protein structures, or unearthing the secrets of exploding stars. The authors remained true to their vision to act as the forefront computational center in extending science frontiers by solving pressing problems for our nation. Our success in this endeavor was due mainly to the Department of Energy's (DOE) INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program. The program awards significant amounts of computing time to computationally intensive, unclassified research projects that can make high-impact scientific advances. This year, DOE allocated 400 million hours of time to 28 research projects at the ALCF. Scientists from around the world conducted the research, representing such esteemed institutions as the Princeton Plasma Physics Laboratory, National Institute of Standards and Technology, and European Center for Research and Advanced Training in Scientific Computation. Argonne also provided Director's Discretionary allocations for research challenges, addressing such issues as reducing aerodynamic noise, critical for next-generation 'green' energy systems. Intrepid - the ALCF's 557-teraflops IBM Blue/Gene P supercomputer - enabled astounding scientific solutions and discoveries. Intrepid went into full production five months ahead of schedule. As a result, the ALCF nearly doubled the days of production computing available to the DOE Office of Science, INCITE awardees, and Argonne projects. One of the fastest supercomputers in the world for open science, the energy-efficient system uses about one-third as much electricity as a machine of comparable size built with more conventional parts. In October 2009, President Barack Obama recognized the excellence of the entire Blue Gene series by awarding it to the National Medal of Technology and Innovation. Other noteworthy achievements included the ALCF's collaboration with the National Energy Research Scientific Computing Center (NERSC) to examine cloud computing as a potential new computing paradigm for scientists. Named Magellan, the DOE-funded initiative will explore which science application programming models work well within the cloud, as well as evaluate the challenges that come with this new paradigm. The ALCF obtained approval for its next-generation machine, a 10-petaflops system to be delivered in 2012. This system will allow us to resolve ever more pressing problems, even more expeditiously through breakthrough science in the years to come.

59 BASIC BIOLOGICAL SCIENCES↗