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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unifying and benchmarking state-of-the-art quantum error mitigation techniques

Error mitigation is an essential component of achieving a practical quantum advantage in the near term, and a number of different approaches have been proposed. In this work, we recognize that many state-of-the-art error mitigation methods share a common feature: they are data-driven, employing classical data obtained from runs of different quantum circuits. For example, Zero-noise extrapolation (ZNE) uses variable noise data and Clifford-data regression (CDR) uses data from near-Clifford circuits. We show that Virtual Distillation (VD) can be viewed in a similar manner by considering classical data produced from different numbers of state preparations. Observing this fact allows us to unify these three methods under a general data-driven error mitigation framework that we call UNIfied Technique for Error mitigation with Data (UNITED). In certain situations, we find that our UNITED method can outperform the individual methods (i.e., the whole is better than the individual parts). Specifically, we employ a realistic noise model obtained from a trapped ion quantum computer to benchmark UNITED, as well as other state-of-the-art methods, in mitigating observables produced from random quantum circuits and the Quantum Alternating Operator Ansatz (QAOA) applied to Max-Cut problems with various numbers of qubits, circuit depths and total numbers of shots. We find that the performance of different techniques depends strongly on shot budgets, with more powerful methods requiring more shots for optimal performance. For our largest considered shot budget (10 10 ), we find that UNITED gives the most accurate mitigation. Hence, our work represents a benchmarking of current error mitigation methods and provides a guide for the regimes when certain methods are most useful.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

MAGNETICALLY SUSPENDED CANNED ROTOR PUMPS FOR THE INTEGRAL MOLTEN SALT REACTOR

This project developed a molten salt pump design for small modular reactors, concentrated solar, and Gen IV nuclear reactors with a magnetically levitated rotor that can operate at temperatures of up to 700 °C. This eliminates the need for rotating seals and roller element bearings which require maintenance and are prone to failure. The pump design is also more compact than existing molten salt pump designs which require long shafts to thermally isolate the electric motor. The aims of the project are to: 1) design and test the molten salt pump, 2) develop and test a high temperature position sensor needed for magnetic bearing control, and 3) develop and test high temperature coil fabrication methods for electric motor and magnetic bearing fabrication. To develop the high temperature coils, conductor materials were analyzed for oxidation, diffusion, cladding, and resistivity. Of the candidate conductor materials that met the requirements, silver was chosen. The long-term impact of radiation on silver resistivity was analyzed by developing a model of a generic molten salt fast reactor to model the conductor irradiation in worst case scenarios. The analysis showed that increased resistivity due to transmutation of silver decreases exponentially with the reactor reflector thickness. Different electrical insulation materials were tested and the final high temperature coils developed were able to withstand conductor to ground voltages up to 1800 V before insulation breakdown. Magnetic bearings require high-precision high-speed measurements of the rotor position to operate. Current commercial position sensors can only operate up to 550 °C so a novel position sensor was developed that can operate up to 800 °C. These sensors were also designed to measure the position of the metallic rotor through a thin metallic corrosion barrier that protects that coils, insulation, and magnetic cores so that the salt containment barrier does not have any penetrations. The high-temperature sensor was tested and had comparable performance to commercially available inductive position sensors. The sensor design and signal processing has led to several invention disclosures. The magnetically levitated molten salt pump design was completed and analyzed. The chloride salt test loop at Oak Ridge National Laboratory was chosen to test the pump and the pump hydraulics and power were designed for the test loop flow and pressure requirements. Classes of motor designs that do not utilize permanent magnetic were considered for the high-temperature motor. After extensive analysis of their performance, a synchronous reluctance motor was chosen for the pump. The design was refined and analyzed to optimize performance. The magnetic bearings were designed to meet the force and frequency requirements necessary to levitate the rotor and reject disturbances from rotor imbalance, motor forces, and hydraulic forces. Compliant mounts for the position sensors were designed that would not damage the ceramic sensor components and maintain sensor alignment over a wide temperature range. A thermal hydraulic analysis of the molten salt coolant flow used to cool the rotor and stator was performed to ensure that the maximum temperature in the rotor and stator will not exceed 725 °C. The corrosion barrier and casing were designed to maintain the salt fluid boundary by using compliant features to absorb large expansion mismatches due to different coefficients of thermal expansion (CTE). Finally, the salt drain and fill systems were designed along with the pump support structure, integration with the test loop, and thermal insulation and heating. Corrosion barrier fabrication experiments were performed to assess using laser cladding to apply a sub-millimeter corrosion barrier to the surface of a Fe-Co-V magnetic core material. The cladding method showed minimal mixing between materials at their interface and withstood temperature cycling without damage to the cladding. The technology commercialization is focused on the high-temperature position sensors and there has been significant interest from the nuclear industry in utilizing these sensors along with some interest from the aerospace industry. The project also led to a research collaboration with a fusion energy industrial partner to study barriers to scaling the pump design from the kW size to the MW size. This research collaboration will also study methods to create high-temperature coils that have conductor to ground breakdown voltages above 5 kV. The successful development of high-temperature electromagnetic coils and high-temperature position sensors greatly increases the temperature limits for electromagnetic devices that don’t rely on permanent magnets. This includes electric motors, magnetic bearings, linear actuators, rotary position and velocity sensing, actuated valves, and generators to name a few. This will fill a current need in molten salt reactors, concentrated solar, and fusion energy for these critical peripheral devices needed for practical reactor designs that do not currently have commercial solutions.

Hines, J Wesley↗
DOE OSTI2014

Simultaneous recovery of vanadium and nickel from power plant fly-ash: Optimization of parameters using response surface methodology

Highlights: • Leaching of vanadium and nickel from fly ash (14.43% V and 5.19% Ni) in sulfuric acid was performed. • Optimization of leaching parameters was carried out using a response surface methodology. • Using optimum conditions, 94.28% V and 81.01% Ni “actual recovery” was obtained. - Abstract: Simultaneous recovery of vanadium (V) and nickel (Ni), which are classified as two of the most hazardous metal species from power plant heavy fuel fly-ash, was studied using a hydrometallurgical process consisting of acid leaching using sulfuric acid. Leaching parameters were investigated and optimized in order to maximize the recovery of both vanadium and nickel. The independent leaching parameters investigated were liquid to solid ratio (S/L) (5–12.5 wt.%), temperature (45–80 °C), sulfuric acid concentration (5–25 v/v%) and leaching time (1–5 h). Response surface methodology (RSM) was used to optimize the process parameters. The most effective parameter on the recovery of both elements was found to be temperature and the least effective was time for V and acid concentration for Ni. Based on the results, optimum condition for metals recovery (actual recovery of ca.94% for V and 81% for Ni) was determined to be solid to liquid ratio of 9.15 wt.%, temperature of 80 °C, sulfuric acid concentration of 19.47 v/v% and leaching time of 2 h. The maximum V and Ni predicted recovery of 91.34% and 80.26% was achieved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Design Concepts for an Optimized, Modular, and Scalable Liquid Amine Test Stand

The Air Revitalization Labs at NASA Ames Research Center (ARC) is investigating liquid amines to for their performance removing spacecraft carbon dioxide (CO2) for crewed space missions. Development of the current one-crew scale amine test stand stems from several modifications to a test stand initially built at NASA Johnson Space Center (JSC) This sub-scale system has been modified to incorporate a flow spreader for the inlet air stream, an updated contactor design for CO2 capture, a degasser to regenerate the liquid sorbent and recover the captured CO2, and a condenser to reduce water loss. Results from the existing integrated liquid amine test stand have provided valuable insight, but continued performance optimization requires design and build of a new integrated test system. New design concepts will institute a modular configuration to allow for interfacing with novel contactor and degasser architecture, parallel or series flow pathways for the air stream and liquid sorbent, and scaling up to a 4-crew CO2 removal system.

Tiago Faria Costa↗
DOE OSTI2018

A Strawman for an HPC PowerStack

The landscape of High-Performance Computing (HPC) is changing as we enter the exascale era and power and energy management are key design points for any next generation of supercomputers. Efficiently utilizing procured power and optimizing performance of scientific applications under power and energy constraints is challenging due to several reasons including dynamic phase behavior, processor manufacturing variability and increasing heterogeneity of node-level components. Extending the scope from the node- and application-level up to the system-level introduces further challenges on top of power-unaware job scheduling, which is known to be NP-hard on its own. While there exists several individual efforts across the community to research automatic techniques for managing power and energy better, the majority of these techniques have been specialized to meet the needs of a specific HPC center or specific optimization goals and provide little support to connect them to each other. Some projects, most notably the PowerAPI efforts [1], discuss interfaces that form a good starting point for full stack integration, but these interfaces still need to be hooked up to the wide range of software components offered by academic partners, developers or vendors. Furthermore, a recent survey conducted by the EE HPC WG concluded that the majority of such techniques have lacked the application-awareness required to achieve the best system performance and throughput. Other observations were that each technique tended to target management of power and energy for a different subset of the site or system hardware and that the different techniques tended to perform management at different (and often conflicting) granularities. Unfortunately, the existing techniques have not been designed to coexist simultaneously on one site and cooperate on management in an integrated manner [2]. The lack of application-awareness, lack of coordinated management across different granularities, and the lack of widely accepted interfaces and consequent limited connectivity between modules, can result in substantially underutilized Watts and FLOPS. To address these gaps, the HPC community needs a holistic stack for power and energy management and none currently exists. In our view, a holistic stack is one that is extensible enough to support the present and anticipated future needs of various different HPC centers, one that achieves best system performance and throughput through application-awareness, one that is designed to coordinate management at different granularities, and one that enables the seamless integration of software components from different developers and vendors. In this seminar, our goal is bring together experts from academia, research laboratories, and industry in order to take stock of existing approaches, design points and power management concepts and requirements at the various participant’s institutions, and to design concepts for a holistic power and energy management stack, which we refer to as the HPC PowerStack. Further, we hope to take steps toward defining the interfaces necessary for providing a complete prototype shared among many groups. The intention is to align development and research efforts across the community so that we may share development resources, avoid duplicating effort, agree on common interfaces and reap the rewards together as a community. The intended final outcome of this collaboration will be a holistic, flexible and extensible concept of a software stack ecosystem that allows us to combine product-grade open-source software components to enable runtime optimization of system power, energy, and performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimal experimental design using eigenvalue-based criteria with Pyomo.DoE

New developments in automated optimal experimental design within the PSE+ software ecosystem. Advancements in user experience (to reduce the time taken to perform optimal experiment design) and computational capabilities (allowing more diverse experimental design) are shown with an example relevant to critical minerals and materials. Also, a small tutorial on science-based optimal experimental design and novel contributions therein are presented.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Object-Oriented Multi-Disciplinary Design, Analysis, and Optimization Tool

An Object-Oriented Optimization (O3) tool was developed that leverages existing tools and practices, and allows the easy integration and adoption of new state-of-the-art software. At the heart of the O3 tool is the Central Executive Module (CEM), which can integrate disparate software packages in a cross platform network environment so as to quickly perform optimization and design tasks in a cohesive, streamlined manner. This object-oriented framework can integrate the analysis codes for multiple disciplines instead of relying on one code to perform the analysis for all disciplines. The CEM was written in FORTRAN and the script commands for each performance index were submitted through the use of the FORTRAN Call System command. In this CEM, the user chooses an optimization methodology, defines objective and constraint functions from performance indices, and provides starting and side constraints for continuous as well as discrete design variables. The structural analysis modules such as computations of the structural weight, stress, deflection, buckling, and flutter and divergence speeds have been developed and incorporated into the O3 tool to build an object-oriented Multidisciplinary Design, Analysis, and Optimization (MDAO) tool.

Pak, Chan-gi↗
DOE OSTI2017

CEED-MS8:Initial Integration of CEED Software in ECP Applications

Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone we report on the initial integration of CEED software in the selected first-wave ECP/CEED apps and the continued exploration of other ECP applications as second-wave (milestone CEED-MS23) and third-wave (milestone CEED-MS35) ECP/CEED application candidates. An extensive evaluation of various approaches for GPU acceleration of the CEED computational motives is also a major focus of the report, both in the settings of CEED’s Nekbone and Laghos miniapps, as well as versions of CEED’s bake-off problems (introduced in milestone CEED-MS6). The first-wave ECP applications targeted for coupling with CEED software include the ExaSMR and MARBL applications. We also report on near-term collaboration with the seed-funded Urban Systems project, as well as engagements with ACME, ExaAM, GEOS and the Application Assessment and Proxy App projects. The ExaSMR project involves coupled thermal-hydraulics/neutronics, with the latter based on Monte Carlo methods and the former based on high-order discretizations of the Navier-Stokes and energy equations for accurate simulation of turbulent transport. The project requires fast and efficient turbulence simulation capabilities that will scale to exascale platforms. Work within CEED will ensure that all aspects of the Nek5000 workflow scale to the target problem space, which involves > 10 10 degrees of freedom in typical production runs. CEED’s goal is to provide implementations that perform with maximum attainable efficiency and deliver low turn-around times. A deliverable for this milestone is beta-release of the GPU-based variant of Nek5000. MARBL is targeting high-energy-density physics problems, including single fluid multi-material hydrodynamics and radiation/magnetic diffusion simulation, with applications in inertial confined fusion, pulsed power experiments, and equation of state/material strength analysis. The code uses high-order methods based arbitrary Lagrangian-Eulerian, direct Eulerian, and unstructured adaptive mesh refinement. A deliverable for this milestone is collaboration with MARBL for improved performance based on partially-assembled operators. The Urban exascale project is planning to couple real-time data with high performance simulations to study particulate transport in cities. Nek5000 will be used for large eddy and RANS (Reynolds-averaged Navier-Stokes) simulations of turbulent transport in these domains. Areas where the CEED team is aiding the Urban Canyon group include creating high-order meshes for urban geometries and developing boundary conditions appropriate for simulations close to real-life urban conditions. The software artifacts delivered as part of this milestone include GPU-enabled versions of the Nekbone and Laghos miniapps, which are provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY17, including: the CEED first annual meeting and participation of CEED researchers in a variety of outreach activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Acceptor Gradient Polymer Donors for Non-Fullerene Organic Solar Cells

In organic solar cells, maximizing the open-circuit voltage ( V OC ) via minimization of the ionization energy or electron affinity offsets of the blended donor and acceptor often comes at the expense of achieving a considerable amount of short-circuit current ( J SC ). To explore a hypothesis for the design of materials that may circumvent this tradeoff, eight structurally similar polymers were synthesized consisting of a fluorinated/non-fluorinated benzothiadiazole (BTDF/BTD) strong acceptor moiety, a thiophene ester (TE) weak acceptor, and various donor units composed of bithiophene (T2), biEDOT, and benzodithiophene (BDT) to form six acceptor gradient and two nongradient polymers. The acceptor gradient motif was designed and theorized to induce more facile exciton dissociation in low driving force solar cells by creating a further separated intramolecular charge-transfer state between the strong BTD acceptor and various donor units through a bridging TE component. Solar cells were fabricated using the eight polymers blended with phenyl-C 71 -butyric-acid methyl ester (PC 71 BM) to reveal two top performing isomeric polymers, T2-BTDF-(TE2) and TE2-BTDF-(T2), which were further tested with several non-fullerene acceptors (NFAs): EH-IDTBR, ITIC, and ITIC- 4 F. In order to fabricate optimally performing solar cells, a 0.2 eV ionization energy offset was found to be essential or the short-circuit current of the NFA cells diminished dramatically. Ultimately, optimized NFA solar cells were fabricated using ITIC-4F paired with each of the top performing polymers to produce an average PCE of 7.3% for TE2-BTDF-(T2) (nongradient) and 3.6% for T2-BTDF-(TE2) (gradient). The acceptor gradient effect was not shown to reduce the amount of charge recombination in NFA solar cells mainly due to the inability to fabricate solar cells, with minimal ionization energy or electron affinity offsets along with morphological complications. This work stresses the importance of acquiring accurate ionization energies and electron affinities when characterizing solar cell energetics, as differences as small as 0.1 eV in the offsets can make a significant impact on overall charge collection.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Initial CEED API (CEED-MS10)

Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone, we initiated the development and implementation of a common CEED API consisting of two main components: low-level and high-level APIs. We accomplished the goal of having the low-level component ready for the release of CEED v1.0 in the next quarter, see CEED-MS13. In this report we also provide a highlight from CEED’s integration with the MARBL app and the corresponding Laghos miniapp. A main theme in this work has been the systematic transition of advanced algorithms, developed and tested in Laghos, to the large-scale multi-physics settings of the MARBL code. The low-level CEED API provides a set of FE kernels and components for writing new low-level kernels. Examples include: vector and sparse linear algebra, element matrix assembly over a batch of elements, partial assembly and action for efficient high-order operators like mass, diffusion, advection, etc. The main goal of the low-level API is to establish the basis for the high-level API. Also, identifying such low-level kernels and providing a reference implementation for them serves as the basis for collaboration with vendors and STs. Another goal for the low-level API is to make it easy for applications with their own discretization infrastructure, who do not want to switch directly to using the high-level CEED API, to still evaluate and use the core operations provided by the low-level API. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. Thus, another important question we tried to address while developing the low-level API is: is it possible to abstract out in a natural and efficient way the different implementations and data structures that arise when dealing with various computational device types: CPUs, GPUs, etc. Fully answering this question is beyond the scope of this particular milestone, since that requires longer time as we develop and expand the devices we support. The future high-level API will be the frontend provided by CEED consisting of high-level abstractions such as meshes, finite element spaces and solutions, bilinear forms, solvers, etc. At this high-level, an important aspect of the API will be to provide a uniform abstraction layer for writing code in a portable manner. To achieve that, we plan to utilize the MPI programming model combined with a device abstraction layer (DAL) for finite element computations that we will develop. The DAL will serve as the bridge between the low- and the high-level APIs, allowing a variety of programming models to be used for the low-level kernel implementations. The software artifacts delivered as part of this milestone include an initial CEED API software implementation (libCEED) provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q1 of FY18, including: the Nek5000 v17.0 MFEM v3.3.2 and PETSc v3.8 releases, collaborations with ECP/ST and SciDAC projects, the inaugural Nek5000 hackathon and various outreach activities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Performance of a 2-micrometer coherent Doppler lidar for wind measurements

Measurements of boundary layer winds are presented using a 2-micrometer coherent Doppler lidar and the optimal performance of the maximum likelihood estimator. The systematic error for single-shot estimates was estimated as 3.6 cm/s using measurements from a stationary hard target. The estimation error for measurements of the radial component of the wind field was determined, as well as the fraction of the estimates that are randomly distributed over the velocity search space, when the signal power is low and speckle fading is important. The results from actual data are compared with the results from ideal simulations. The first direct estimation of the spatial structure function of the radial wind field and of the energy dissipation rate is presented for both horizontal and vertical directions of propagation. The rms estimation error of the velocity estimates is found to be within 30% of ideal performance based on simulation.

Frehlich, Rod↗
DOE OSTI2017

Pseudo-spectral control of a novel oscillating surge wave energy converter in regular waves for power optimization including load reduction

The aim of this study is to describe a procedure to maximize the power-to-load ratio of a novel wave energy converter (WEC) that combines an oscillating surge wave energy converter with variable structural components. The control of the power-take-off torque will be on a wave-to-wave timescale, whereas the structure will be controlled statically such that the geometry remains the same throughout the wave period. Linear hydrodynamic theory is used to calculate the upper and lower bounds for the time-averaged absorbed power and surge foundation loads while assuming that the WEC motion remains sinusoidal. Previous work using pseudo-spectral techniques to solve the optimal control problem focused solely on maximizing absorbed energy. This work extends the optimal control problem to include a measure of the surge foundation force in the optimization. The objective function includes two competing terms that force the optimizer to maximize power capture while minimizing structural loads. A penalty weight was included with the surge foundation force that allows control of the optimizer performance based on whether emphasis should be placed on power absorption or load shedding. Results from pseudo-spectral optimal control indicate that a unit reduction in time-averaged power can be accompanied by a greater reduction in surge-foundation force.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Toward Automated Tools for Characterization of Molecular Porosity

The emerging advanced porous materials, e.g. extended framework materials and porous molecular materials, offer an unprecedented level of control of their structure and function. The enormous possibilities for tuning these materials by changing their building blocks mean that, in principle, optimally performing materials for a variety of applications can be systematically designed. However, the process of finding a set of optimal structures for a given application requires computational high-throughput tools to analyze and sieve through many candidate materials. In particular, in the case of porous molecular materials, the analysis and selection of a molecule is one of the key aspects as the structure of the molecule determines the structure of the resulting material, and very often the porosity of the molecule significantly contributes to the porous properties of the resulting material. In this work, we introduce definitions and algorithms to characterize porosity at the molecular level, along with a software implementation of these algorithms. We demonstrate applications of the software tool in the discovery and characterization of porous molecules among ca. 94 million molecules currently enlisted in the PubChem database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗
DOE OSTI2018

DARMA-MPI Interoperability WBS 2.3.1.04 Milestone 15 (ECP Milestone Report)

DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library developed as part of the the Sandia ATDM (Advanced Technology Development and Mitigation) program. DARMA supports applications within 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes a number of applications featuring dynamic physics which requires load balancing and asynchronous communication for high performance. We have implemented a modern C++ programming model that can enable dynamic, asynchronous communication on top of existing data structures from a serial or MPI code. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA will impact ATDM by enabling the performance benefits of a dynamic runtime through only incremental changes to existing verified MPI codes. The results presented here demonstrate the DARMA development process for an MPI mini-app, showing a 3-4x improvement in performance for a challenging problem relative to the parent MPI code and coming within 25 percent of the theoretically optimal performance achievable from a perfect, fine-grained load balancer for most cases.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

Bole, Brian↗
DOE OSTI2016

Optimizing Dirac Wilson Operator and linear solvers for Intel KNL

Lattice Quantumchromodynamics (QCD) is a powerful tool to numerically access the low energy regime of QCD in a straightforward way with quantifyable uncertainties. In this approach, QCD is discretized on a four dimensional, euclidian space-time grid with millions of degrees of freedom. In modern lattice calculations, most of the work is still spent in solving large, sparse linear systems. This part has two challenges, i.e. optimizing the sparse matrix application as well as BLAS-like kernels used in the linear solver. We are going to present performance optimizations of the Dirac operator (dslash) with and without clover term for recent Intel architectures, including Knights Landing (KNL). Using only a single right hand side, we were able to achieve a good fraction of peak performance for slash, CG and BiCGStab. We will also present a series of experiments we performed on KNL, i.e. running MCDRAM in different modes, enabling or disabling hardware prefetching, using different SoA lengths as well as different sub-NUMA-clustering modes.

Joó, Bálint↗
DOE OSTI2021

Investigating the relationship between radial pre-stress magnitude and ballistic projectile dwell in heavy confined ceramic targets

A series of bare silicon carbide ceramic armour disks were manufactured with high-strength steel containment to induce varying magnitudes of radial pre-stress. The induced radial stresses, ranging from 0 to 900 MPa, were measured via neutron diffraction and verified by comparison with numerical calculations. Four targets of each configuration, referred to as slip-fit, moderate pre-stress, and high pre-stress, were subject to ballistic testing with hemispherical-nose, tungsten heavy alloy long rod projectiles to determine the interface defeat transition velocity. In-situ diagnostics were unsuccessful in aiding the identification of interface defeat, necessitating a reliance on post-mortem assessment. A transition velocity of approx. 1000 m/s was identified for the unstressed target, increasing to approx. 1200 m/s for the pre-stressed configurations. No performance effect was discernible between the moderate (372 MPa) and high (899 MPa) pre-stress configurations, suggesting that an optimal performance may be achieved for lower pre-stress levels (i.e., <372 MPa). Additionally, the test results were compared with four semi-analytical predictions of interface defeat performance and good agreement was found, albeit with significant range in the model predictions.

42 ENGINEERING↗