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At least 1,585 records · Page 88

SPARTAN (Scalable Probabilistic Application Reconfigurable Tensor Autonomous Network)

The technical founder of Ludwig Computing Inc has been competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Ludwig Computing Inc, supported by the U.S. Department of Energy's Advanced Manufacturing Office through the Cyclotron Road program, has investigated the advantages of probabilistic computing for real-world compute-intensive applications. This research adds to the understanding of alternative computing paradigms by exploring a unique hardware-software co-design that integrates quantum computing methods with nature-inspired problem-solving techniques. The project's focus on areas such as combinatorial optimization, graph analytics, and machine learning demonstrates the potential for significant advancements in computational efficiency and performance. By harnessing natural randomness to streamline large circuits into fewer devices, Ludwig's approach enables massive parallelism, potentially offering higher throughput, speed, and energy efficiency compared to conventional hardware solutions. This work benefits the public by paving the way for more efficient computing solutions that could address complex real-world problems while potentially reducing energy consumption in data-intensive industries.

97 MATHEMATICS AND COMPUTING↗

A Hybrid SBR/MoM Technique for Analysis of Scattering from Small Protrusions on a Large Conducting Body

For analysis of large-scale electromagnetic scattering problems, high-frequency asymptotic methods are fast but approximate, whereas low-frequency numerical methods are accurate but slow. Neither can produce an efficient and accurate solution to scattering by large bodies containing small structures. A promising approach is to combine the best features of both types of methods to produce a hybrid technique that is sufficiently fast, reasonably accurate, and applicable to a class of unsolvable problems such as the scatterers mentioned above. There are two extremes for this type of hybridization. One is simply to superimpose solutions from asymptotic and numerical methods. While this approach is most widely used in practical applications, it neglects the interactions between the two solutions, which can be significant in many problems. The other extreme is to combine an asymptotic and a numerical method in an exact manner. In this approach, the effect of a large body is included by incorporating its diffraction into the Green's function in the integral equation for the small structures, which accounts for all interactions. While this approach is accurate, it is difficult to be implemented in a general-purpose computer code because of its complex nature. A more practical approach is to develop a technique that can include all significant interactions and neglect all trivial interactions. The resulting hybrid technique can produce sufficient accuracy and can be implemented in a general-purpose computer code. In this paper, we develop a technique that combines the shooting and- bouncing-ray (SBR) method and the method of moments (MoM) to solve for the scattering by large conducting bodies with small structures mounted on their surfaces.

Jin, J. M.↗

The effect of inflow velocity profiles on the performance of supersonic ejector nozzles

The design of supersonic nozzles is becoming increasingly complex as conflicting requirements for low noise, higher efficiency, and wider operating range are driving the designer toward more variable geometry and multiple stream flows. Analysis techniques must be modified and expanded to take into account these additional complexities and still retain the rapid computational rate necessary for optimization and design studies. A nozzle analysis must handle more flow streams, more complex geometries, and more highly distorted initial profiles. This paper discusses some modifications to a method for calculating the performance characteristics of supersonic ejector nozzles and demonstrates the improvement in results the modifications provide.

Bishop, A. R.↗

Flight computers and sequencers

At present, the most common method of increasing reliability of a system against permanent random component failures is to triplicate the entire system and use voters. This method, though it enhances the reliability, does exact a heavy toll in weight and power consumption which increase by about 225%. In the future, computers will be required to perform complex tasks under adverse conditions on surfaces of planets for long periods of time (6 months or more), without any human intervention. At the same time there will be severe limitations on the weight and power consumption of these computers. For such systems it is obvious that simple triple-redundancy will not do. A more efficient and sophisticated design in redundancy has to evolve. This study has been directed toward that goal. It is understood that the initial design of such a system will be too complex and expensive to be used in a commercial computer; but for a space computer, reduction in weight (without reducing reliability) of every ounce means a great deal.

REDUNDANCY↗

Holographic pseudoentanglement and the complexity of the AdS/CFT dictionary

The `quantum gravity in the lab' paradigm suggests that quantum computers might shed light on quantum gravity by simulating the CFT side of the AdS/CFT correspondence and mapping the results to the AdS side. This relies on the assumption that the duality map (the `dictionary') is efficient to compute. In this work, we show that the complexity of the AdS/CFT dictionary is surprisingly subtle: there might be cases in which one can efficiently apply operators to the CFT state (a task we call 'operator reconstruction') without being able to extract basic properties of the dual bulk state such as its geometry (which we call 'geometry reconstruction'). Geometry reconstruction corresponds to the setting where we want to extract properties of a completely unknown bulk dual from a simulated CFT boundary state. We demonstrate that geometry reconstruction may be generically hard due to the connection between geometry and entanglement in holography. In particular we construct ensembles of states whose entanglement approximately obey the Ryu-Takayanagi formula for arbitrary geometries, but which are nevertheless computationally indistinguishable. This suggests that even for states with the special entanglement structure of holographic CFT states, geometry reconstruction might be hard. This result should be compared with existing evidence that operator reconstruction is generically easy in AdS/CFT. A useful analogy for the difference between these two tasks is quantum fully homomorphic encryption (FHE): this encrypts quantum states in such a way that no efficient adversary can learn properties of the state, but operators can be applied efficiently to the encrypted state. We show that quantum FHE can separate the complexity of geometry reconstruction vs operator reconstruction, which raises the question whether FHE could be a useful lens through which to view AdS/CFT.

FOS: Physical sciences↗

Hidden-line removal at 20 pictures/second through hybrid techniques.

A real-time computer image generation method is presented that is designed to operate in a parallel-computing environment. It can provide good quality pictures of limited complexity if implemented on a general purpose hybrid computing system. Such a hybrid approach can generate a new image every 50 milliseconds. These results have been demonstrated by a feasibility test program which impelements the hybrid concepts described. This hybrid-picture generation capability is shown to represent a significant contribution to the area of real-time hidden-line removal.

Brown, R. M.↗

Unsteady airloads due to separated flow on airfoils and wings

Experimental and computational studies of airloads due to separated flows over airfoils and wings conducted at the NASA Langley Research Center are surveyed. Results are presented for cases involving local flow separation such as shock-induced separation, for the initiation of leading-edge vortex flows, and for cases involving unsteady airloads due to flows separating over remote aircraft components. Good correlation is obtained between experiment and computation for cases of locally separating flow and steady computations of vortex flow over delta wings and complex forebody geometries are shown. Physical flow modeling issues and computational requirements for the case of vertical tail buffeting are developed.

Edwards, John W.↗

Unsteady airloads due to separated flow on airfoils and wings

Experimental and computational studies of airloads due to separated flows over airfoils and wings conducted at the NASA Langley Research Center are surveyed. Results are presented for cases involving local flow separation such as shock-induced separation, for the initiation of leading-edge vortex flows, and for cases involving unsteady airloads due to flows separating over remote aircraft components. Good correlation is obtained between experiment and computation for cases of locally separating flow and steady computations of vortex flow over delta wings and complex forebody geometries are shown. Physical flow modeling issues and computational requirements for the case of vertical tail buffeting are developed.

Edwards, John W.↗

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

Gupta, Kajal K.↗

The effect of initial imperfections on shell stability: An updated review

The development of the Delft Interactive Shell Design Code (DISDECO) is described. The purpose is to make the accumulated theoretical, numerical, and practical knowledge of the last years readily accessible to users interested in the analysis of buckling sensitive structures. With this open ended, hierarchical, interactive computer code, the user can access workstation programs of increasing complexity. As a first update of DISDECO, the computational modules of the initial level were modified so as to handle combined loads consisting of axial compression, internal and external pressure, and clockwise or counter clockwise torque. The applied load is assumed to have a uniform spatial distribution and is divided into a fixed and a variable part. The magnitude of the variable part is allowed to vary in proportion to a load parameter Lambda. This leads to an eigenvalue problem for the critical lambda sub C.

Arbocz, J.↗

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

A Study of Parallel Scalability and Dynamic Workload Balancing in GlennICE

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries. It utilizes user-supplied computational fluid dynamics solutions for the geometry of interest. Key developments include advancements in convergence of collection efficiency, trajectory optimization, and refinement methodology. These improvements have significantly enhanced GlennICE’s efficiency for practical engineering applications. A recent study focused on benchmarking GlennICE’s scalability in a parallel environment using static scheduling. Findings indicated a potential twofold increase in efficiency through workload balance enhancements. This paper presents an analysis of the solver’s new workload balancing improvements, incorporating shared memory and dynamic scheduling routines. Results demonstrate a highly efficient and consistent algorithm across high-performance computing clusters.

Computational Icing↗

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Shishir, Pandya↗

A novel VLSI processor architecture for supercomputing arrays

Design of the processor element for general purpose massively parallel supercomputing arrays is highly complex and cost ineffective. To overcome this, the architecture and organization of the functional units of the processor element should be such as to suit the diverse computational structures and simplify mapping of complex communication structures of different classes of algorithms. This demands that the computation and communication structures of different class of algorithms be unified. While unifying the different communication structures is a difficult process, analysis of a wide class of algorithms reveals that their computation structures can be expressed in terms of basic IP,IP,OP,CM,R,SM, and MAA operations. The execution of these operations is unified on the PAcube macro-cell array. Based on this PAcube macro-cell array, we present a novel processor element called the GIPOP processor, which has dedicated functional units to perform the above operations. The architecture and organization of these functional units are such to satisfy the two important criteria mentioned above. The structure of the macro-cell and the unification process has led to a very regular and simpler design of the GIPOP processor. The production cost of the GIPOP processor is drastically reduced as it is designed on high performance mask programmable PAcube arrays.

Venkateswaran, N.↗

Scrutinizing formally Ni IV centers through the lenses of core spectroscopy, molecular orbital theory, and valence bond theory

Nickel K- and L 2,3 -edge X-ray absorption spectra (XAS) are discussed for 16 complexes and complex ions with nickel centers spanning a range of formal oxidation states from II to IV. K-edge XAS alone is shown to be an ambiguous metric of physical oxidation state for these Ni complexes. Meanwhile, L 2,3 -edge XAS reveals that the physical d-counts of the formally Ni IV compounds measured lie well above the d 6 count implied by the oxidation state formalism. The generality of this phenomenon is explored computationally by scrutinizing 8 additional complexes. The extreme case of NiF 6 2- is considered using high-level molecular orbital approaches as well as advanced valence bond methods. The emergent electronic structure picture reveals that even highly electronegative F-donors are incapable of supporting a physical d 6 Ni IV center. The reactivity of Ni IV complexes is then discussed, highlighting the dominant role of the ligands in this chemistry over that of the metal centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single expansion ramp nozzle simulations

The single-expansion-ramp-nozzle (SERN) experiment underway at NASA Ames Research Center simulates the National Aerospace Plane propulsive jet-plume flow. Recently, limited experimental data has become available from an experiment with a generic nozzle/afterbody model in a hypersonic wind tunnel. The present paper presents full three-dimensional solutions obtained with the implicit Navier-Stokes solver, FL3D, for the baseline model and a version of the model with side extensions. Analysis of the computed flow clearly shows the complex 3-D nature of the flow, critical flow features, and the effect of side extensions on the plume flow development. Flow schematics appropriate for the conditions tested are presented for the baseline model and the model with side extensions. The computed results show excellent agreement with experimental shadowgraph and with surface pressure measurements. The computed and experimental surface oil-flows show the same features but may be improved by appropriate turbulence modeling.

Ruffin, Stephen M.↗

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials↗