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At least 793 records · Page 44

Runtime optimization of an application executing on a parallel computer

Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.

97 MATHEMATICS AND COMPUTING↗

EUPDF: Eulerian Monte Carlo Probability Density Function Solver for Applications With Parallel Computing, Unstructured Grids, and Sprays

The success of any solution methodology used in the study of gas-turbine combustor flows depends a great deal on how well it can model the various complex and rate controlling processes associated with the spray's turbulent transport, mixing, chemical kinetics, evaporation, and spreading rates, as well as convective and radiative heat transfer and other phenomena. The phenomena to be modeled, which are controlled by these processes, often strongly interact with each other at different times and locations. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. The influence of turbulence in a diffusion flame manifests itself in several forms, ranging from the so-called wrinkled, or stretched, flamelets regime to the distributed combustion regime, depending upon how turbulence interacts with various flame scales. Conventional turbulence models have difficulty treating highly nonlinear reaction rates. A solution procedure based on the composition joint probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices (such as extinction, blowoff limits, and emissions predictions) because it can account for nonlinear chemical reaction rates without making approximations. In an attempt to advance the state-of-the-art in multidimensional numerical methods, we at the NASA Lewis Research Center extended our previous work on the PDF method to unstructured grids, parallel computing, and sprays. EUPDF, which was developed by M.S. Raju of Nyma, Inc., was designed to be massively parallel and could easily be coupled with any existing gas-phase and/or spray solvers. EUPDF can use an unstructured mesh with mixed triangular, quadrilateral, and/or tetrahedral elements. The application of the PDF method showed favorable results when applied to several supersonic-diffusion flames and spray flames. The EUPDF source code will be available with the National Combustion Code (NCC) as a complete package.

Raju, M. S.↗

Parallel variable-band Choleski solvers for computational structural analysis applications on vector multiprocessor supercomputers

A Choleski method used to solve linear systems of equations that arise in large scale structural analyses is described. The method uses a novel variable-band storage scheme and is structured to exploit fast local memory caches while minimizing data access delays between main memory and vector registers. Several parallel implementations of this method are described for the CRAY-2 and CRAY Y-MP computers demonstrating the use of microtasking and autotasking directives. A portable parallel language, FORCE, is also used for two different parallel implementations, demonstrating the use of CRAY macrotasking. Results are presented comparing the matrix factorization times for three representative structural analysis problems from runs made in both dedicated and multi-user modes on both the CRAY-2 and CRAY Y-MP computers. CPU and wall clock timings are given for the various parallel methods and are compared to single processor timings of the same algorithm. Computation rates over 1 GIGAFLOP (1 billion floating point operations per second) on a four processor CRAY-2 and over 2 GIGAFLOPS on an eight processor CRAY Y-MP are demonstrated as measured by wall clock time in a dedicated environment. Reduced wall clock times for the parallel methods relative to the single processor implementation of the same Choleski algorithm are also demonstrated for runs made in multi-user mode.

Poole, E. L.↗

Transonic aerodynamics; Transonic Perspective Symposium, Moffett Field, CA, February 18-20, 1981, Technical Papers

After an historical account of the development of transonic aerodynamics before 1940 and in the period 1945-1975, attention is given to the design for cruise performance efficiency of commercial transport aircraft, with emphasis on transonic wing design, the practical aerodynamic problems of military aircraft, with emphasis on store carriage and separation, experimental testing in transonic wind tunnels capable of Reynolds number simulation and aerodynamic flow visualization, and such mathematical techniques as potential equation methods for flow prediction and Reynolds-averaged Navier-Stokes computations of transonic flows. Also considered are transonic design using computational aerodynamics, the application of computation methods to transonic wing design, computational experience with advanced tactical aircraft, the evaluation of full potential flow methods, and the application of a shock-turbulent boundary layer interaction theory to transonic flowfield analysis.

Nixon, D.↗

Lunar Applications in Reconfigurable Computing

NASA s Constellation Program is developing a lunar surface outpost in which reconfigurable computing will play a significant role. Reconfigurable systems provide a number of benefits over conventional software-based implementations including performance and power efficiency, while the use of standardized reconfigurable hardware provides opportunities to reduce logistical overhead. The current vision for the lunar surface architecture includes habitation, mobility, and communications systems, each of which greatly benefit from reconfigurable hardware in applications including video processing, natural feature recognition, data formatting, IP offload processing, and embedded control systems. In deploying reprogrammable hardware, considerations similar to those of software systems must be managed. There needs to be a mechanism for discovery enabling applications to locate and utilize the available resources. Also, application interfaces are needed to provide for both configuring the resources as well as transferring data between the application and the reconfigurable hardware. Each of these topics are explored in the context of deploying reconfigurable resources as an integral aspect of the lunar exploration architecture.

Somervill, Kevin↗

Aggregating job exit statuses of a plurality of compute nodes executing a parallel application

Aggregating job exit statuses of a plurality of compute nodes executing a parallel application, including: identifying a subset of compute nodes in the parallel computer to execute the parallel application; selecting one compute node in the subset of compute nodes in the parallel computer as a job leader compute node; initiating execution of the parallel application on the subset of compute nodes; receiving an exit status from each compute node in the subset of compute nodes, where the exit status for each compute node includes information describing execution of some portion of the parallel application by the compute node; aggregating each exit status from each compute node in the subset of compute nodes; and sending an aggregated exit status for the subset of compute nodes in the parallel computer.

97 MATHEMATICS AND COMPUTING↗

Application of Soft Computing in Coherent Communications Phase Synchronization

The use of soft computing techniques in coherent communications phase synchronization provides an alternative to analytical or hard computing methods. This paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for phase synchronization in coherent communications systems utilizing Multiple Phase Shift Keying (MPSK) modulation. A brief overview of the M-PSK digital communications bandpass modulation technique is presented and it's requisite need for phase synchronization is discussed. We briefly describe the hybrid platform developed by Jang that incorporates fuzzy/neural structures namely the, Adaptive Neuro-Fuzzy Interference Systems (ANFIS). We then discuss application of ANFIS to phase estimation for M-PSK. The modeling of both explicit, and implicit phase estimation schemes for M-PSK symbols with unknown structure are discussed. Performance results from simulation of the above scheme is presented.

Drake, Jeffrey T.↗

Applicability of Parallel Computing to Partial Wave Analysis

Bound states of Quantum Chromodynamics (QCD) give insights into the nature of confinement, a key element of the strong interaction. States may be identified from weak signals extracted from the analysis of high statistics data from reactions with many final state particles. One of the best tools for the analysis of these reactions is Partial Wave Analysis (PWA). PWA transforms an ensemble of experimental data from a large acceptance detector from free particle eigenstates to angular momentum eigenstates. The PWA program must be fast enough to deal with the large amounts of data available currently, as processing time scales with the number of events. The scope of this research is to study the applicability and scalability of Intel's Xeon Phi using the Many Integrated Core (MIC) architecture when applied to the existing PWA code at Jefferson Laboratory. An algorithm was developed for the Xeon Phi and scaled across 240 available threads, giving parallel functionality to the PWA which was originally written serially. This scaling can make the fitting process fifteen times faster.

Ruger, Justin↗

MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific Computing

Scientific applications often require high-bandwidth shared storage to perform joint simulations and collaborative data analytics. Shared memory pools provide a chance to satisfy such needs. Recently, a high-speed network such as Gen-Z utilizing persistent memory (PM) offers an opportunity to create a shared memory pool connected to compute nodes. However, there are several challenges to use scientific applications on the shared memory pool directly such as scalability, failure-atomicity, and lack of scientific metadata-based search and query. In this paper, we propose MOSIQS, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design MOSIQS based on the key idea that memory objects on PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. MOSIQS provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects to accelerate scientific computing. MOSIQS uses a lightweight persistent memory key-value store to manage the metadata of memory objects, which enables memory object sharing. To facilitate metadata search and query over millions of memory objects resident on memory pool, we introduce Group Split and Merge (GSM), a novel persistent index data structure designed primarily for scientific datasets. GSM splits and merges dynamically to minimize the query search space and maintains low query processing time while overcoming the index storage overhead. MOSIQS is implemented on top of PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. Experimental results show that MOSIQS gains a 100% write performance improvement and executes multi-attribute queries efficiently with 2.7× less index storage overhead offering significant potential to speed up scientific computing applications.

97 MATHEMATICS AND COMPUTING↗

A Framework for Integrating Quantum Simulation and High Performance Computing

Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM & NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.

Shehata, Amir [ORNL] (ORCID:0000000224531426)↗

High-Throughput Computation and the Applicability of Monte Carlo Integration in Fatigue Load Estimation of Floating Offshore Wind Turbines

Long-term fatigue loads for floating offshore wind turbines are hard to estimate because they require the evaluation of the integral of a highly nonlinear function over a wide variety of wind and wave conditions. Current design standards involve scanning over a uniform rectangular grid of metocean inputs (e.g., wind speed and direction and wave height and period), which becomes intractable in high dimensions as the number of required evaluations grows exponentially with dimension. Monte Carlo integration offers a potentially efficient alternative because it has theoretical convergence proportional to the inverse of the square root of the number of samples, which is independent of dimension. In this paper, we first report on the integration of the aeroelastic code FAST into NREL's systems engineering tool, WISDEM, and the development of a high-throughput pipeline capable of sampling from arbitrary distributions, running FAST on a large scale, and postprocessing the results into estimates of fatigue loads. Second, we use this tool to run a variety of studies aimed at comparing grid-based and Monte Carlo-based approaches with calculating long-term fatigue loads. We observe that for more than a few dimensions, the Monte Carlo approach can represent a large improvement in computational efficiency, but that as nonlinearity increases, the effectiveness of Monte Carlo is correspondingly reduced. The present work sets the stage for future research focusing on using advanced statistical methods for analysis of wind turbine fatigue as well as extreme loads.

17 WIND ENERGY↗

Quantum Computing Algorithms and Applications for Coherent and Strongly Correlated Chemical Systems

This project advanced quantum algorithms, quantum information theory, strongly correlated electronic structure methods, molecular quantum materials, and exciton transport imaging in coherent condensed phase systems. Across the award period, the team developed new methods for open-quantum-system simulation, Hamiltonian learning, state tomography, reduced-density-matrix and contracted-quantum eigensolver approaches, and quantum diagnostics for device capability and openness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance Evaluation of Three Distributed Computing Environments for Scientific Applications

We present performance results for three distributed computing environments using the three simulated CFD applications in the NAS Parallel Benchmark suite. These environments are the DCF cluster, the LACE cluster, and an Intel iPSC/860 machine. The DCF is a prototypic cluster of loosely coupled SGI R3000 machines connected by Ethernet. The LACE cluster is a tightly coupled cluster of 32 IBM RS6000/560 machines connected by Ethernet as well as by either FDDI or an IBM Allnode switch. Results of several parallel algorithms for the three simulated applications are presented and analyzed based on the interplay between the communication requirements of an algorithm and the characteristics of the communication network of a distributed system.

Fatoohi, Rod↗

Anderson acceleration with approximate calculations: Applications to scientific computing

Here we provide rigorous theoretical bounds for Anderson acceleration (AA) that allow for approximate calculations when applied to solve linear problems. We show that, when the approximate calculations satisfy the provided error bounds, the convergence of AA is maintained while the computational time could be reduced. We also provide computable heuristic quantities, guided by the theoretical error bounds, which can be used to automate the tuning of accuracy while performing approximate calculations. For linear problems, the use of heuristics to monitor the error introduced by approximate calculations, combined with the check on monotonicity of the residual, ensures the convergence of the numerical scheme within a prescribed residual tolerance. Motivated by the theoretical studies, we propose a reduced variant of AA, which consists in projecting the least-squares used to compute the Anderson mixing onto a subspace of reduced dimension. The dimensionality of this subspace adapts dynamically at each iteration as prescribed by the computable heuristic quantities. We numerically show and assess the performance of AA with approximate calculations on: (i) linear deterministic fixed-point iterations arising from the Richardson's scheme to solve linear systems with open-source benchmark matrices with various preconditioners and (ii) non-linear deterministic fixed-point iterations arising from non-linear time-dependent Boltzmann equations.

97 MATHEMATICS AND COMPUTING↗

Integrated computational materials engineering: Tools, simulations and new applications

Here, Integrated Computational Materials Engineering (ICME) is a relatively new methodology full of tremendous potential to revolutionize how science, engineering and manufacturing work together. ICME was motivated by the desire to derive greater understanding throughout each portion of the development life cycle of materials, while simultaneously reducing the time between discovery to implementation [1,2].

42 ENGINEERING↗

Understanding the metal-to-insulator transition in La1−xSrxCoO3−δ and its applications for neuromorphic computing

Abstract Transition metal oxides that exhibit a metal-to-insulator transition (MIT) as a function of oxygen vacancy concentration are promising systems to realize energy-efficient platforms for neuromorphic computing. However, the current lack of understanding of the microscopic mechanism driving the MIT hinders the realization of effective and stable devices. Here we investigate defective cobaltites and we unravel the structural, electronic, and magnetic changes responsible for the MIT when oxygen vacancies are introduced in the material. We show that, contrary to accepted views, cooperative structural distortions instead of local bonding changes are responsible for the MIT, and we describe the subtle interdependence of structural and magnetic transitions. Finally, we present a model, based on first principles, to predict the required electric bias to drive the transition, showing good agreement with available measurements and providing a paradigm to establish design rules for low-energy cost devices.

36 MATERIALS SCIENCE↗

Electronic stopping power calculation for water under the Lindhard formalism for application in proton computed tomography

Because of the behavior that charged particles have when they interact with biological material, proton therapy is shaping the future of radiation therapy in cancer treatment. The planning of radiation therapy is made up of several stages. The first one is the diagnostic image, in which you have an idea of the density, size and type of tumor being treated; to understand this it is important to know how the particles beam interacts with the tissue. In this work, by using de Lindhard formalism and the Y.R. Waghmare model for the charge distribution of the proton, the electronic stopping power (SP) for a proton beam interacting with a liquid water target in the range of proton energies 10{sup 1} eV - 10{sup 10} eV taking into account all the charge states is calculated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗