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All sources NASA NTRS DOE OSTI

DOE OSTI2018

Computing with Spikes: The Advantage of Fine-Grained Timing

Neural-inspired spike-based computing machines often claim to achieve considerable advantages in terms of energy and time efficiency by using spikes for computation and communication. However, fundamental questions about spike-based computation remain unanswered. For instance, how much advantage do spike-based approaches have over conventional methods, and under what circumstances does spike-based computing provide a comparative advantage? Simply implementing existing algorithms using spikes as the medium of computation and communication is not guaranteed to yield an advantage. Here, we demonstrate that spike-based communication and computation within algorithms can increase throughput, and they can decrease energy cost in some cases. We present several spiking algorithms, including sorting a set of numbers in ascending/descending order, as well as finding the maximum or minimum or median of a set of numbers. We also provide an example application: a spiking median-filtering approach for image processing providing a low-energy, parallel implementation. Furthermore, the algorithms and analyses presented here demonstrate that spiking algorithms can provide performance advantages and offer efficient computation of fundamental operations useful in more complex algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Time-periodic steady-state solution of fluid-structure interaction and cardiac flow problems through multigrid-reduction-in-time

In this study, a time-periodic MGRIT algorithm is proposed as a means to reduce the time-to-solution of numerical algorithms by exploiting the time periodicity inherent to many applications in science and engineering. The time-periodic MGRIT algorithm is applied to a variety of linear and nonlinear single- and multiphysics problems that are periodic-in-time. It is demonstrated that the proposed parallel-in-time algorithm can obtain the same time-periodic steady-state solution as sequential time-stepping. It is shown that the required number of MGRIT iterations can be estimated a priori and that the new MGRIT variant can significantly and consistently reduce the time-to-solution compared to sequential time-stepping, irrespective of the number of dimensions, linear or nonlinear PDE models, single-physics or coupled problems and the employed computing resources. The numerical experiments demonstrate that the time-periodic MGRIT algorithm enables a greater level of parallelism yielding faster turnaround, and thus, facilitating more complex and more realistic problems to be solved.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Using OpenMP for HEP framework algorithm scheduling

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software packages (such as CMSSW, GaudiHive, and ROOT) make use of Intel’s Threading Building Blocks (TBB) library to accomplish the same goal. In these proceedings we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework. This includes both scheduling of different interdependent algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1988

A parallel householder tridiagonalization stratagem using scattered row decomposition

Householder's method for tridiagonalizing a real symmetric matrix, a major step in evaluating eigenvalues of the matrix, is modified into a parallel algorithm for a concurrent machine of message passing type. Each processor of the concurrent machine has its own CPU, communications control and local memory. Messages are passed through connections between processors. Although the basic algorithm is inherently serial, the computations can be spread over all processors by scattering different rows of the matrix into processors, hence the term 'Scattered Row Decomposition'. The steps in the serial and the parallel algorithms are identified. Expressions for efficiency and speedup are given in terms of problem and machine parameters. For a concurrent machine of ring type interconnection, a selected representative problem of large order exhibits efficiency approaching 66 per cent.

Chang, H. Y.↗

NASA NTRS1985

Partitioning problems in parallel, pipelined and distributed computing

The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.

Bokhari, S.↗

DOE OSTI2018

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities’ operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities’ locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

58 GEOSCIENCES↗

DOE OSTI2016

Array-based, parallel hierarchical mesh refinement algorithms for unstructured meshes

In this paper, we describe an array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements (by loading smaller meshes and in memory refinement). We also describe a high-order boundary reconstruction capability that can be used to project the new points after refinement using high-order approximations instead of linear projection in order to minimize and provide more control on geometrical errors introduced by curved boundaries.The capability is developed under the parallel unstructured mesh framework "Mesh Oriented dAtaBase" (MOAB Tautges et al. (2004)). We describe the underlying data structures and algorithms to generate such hierarchies in parallel and present numerical results for computational efficiency and effect on mesh quality. Furthermore, we also present results to demonstrate the applicability of the developed capability to study convergence properties of different point projection schemes for various mesh hierarchies and to a multigrid finite-element solver for elliptic problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Large-scale atomistic calculations of clusters in intense x-ray pulses

Here, we present the methodology of our recently developed Monte-Carlo/ Molecular-Dynamics method for studying the fundamental ultrafast dynamics induced by high-fluence, high-intensity x-ray free electron laser (XFEL) pulses in clusters. The quantum nature of the initiating ionization process is accounted for by a Monte Carlo method to calculate probabilities of electronic transitions, including photo absorption, inner-shell relaxation, photon scattering, electron collision and recombination dynamics, and thus track the transient electronic configurations explicitly. The freed electrons and ions are followed by classical particle trajectories using a molecular dynamics algorithm. These calculations reveal the surprising role of electron-ion recombination processes that lead to the development of nonuniform spatial charge density profiles in x-ray excited clusters over femtosecond timescales. In the high-intensity limit, it is important to include the recombination dynamics in the calculated scattering response even for a 2- fs pulse. We also demonstrate that our numerical codes and algorithms can make e!cient use of the computational power of massively parallel supercomputers to investigate the intense-field dynamics in systems with increasing complexity and size at the ultrafast timescale and in non-linear x-ray interaction regimes. In particular, picosecond trajectories of XFEL clusters with attosecond time resolution containing millions of particles can be e!ciently computed on upwards of 262,144 processes.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Pececillo

Pececillo is a proxy-app for the open source Truchas metal processing code (LA-CC-15-097). It implements many of the physics models used in Truchas: free-surface, incompressible Navier-Stokes fluid dynamics (e.g., water waves); heat transport, material phase change, view factor thermal radiation; species advection-diffusion; quasi-static, elastic/plastic solid mechanics with contact; electomagnetics (Maxwell's equations). The models are simplified versions that retain the fundamental computational complexity of the Truchas models while omitting many non-essential features and modeling capabilities. The purpose is to expose Truchas algorithms in a greatly simplified context where computer science problems related to parallel performance on advanced architectures can be more easily investigated. While Pececillo is capable of performing simulations representative of typical Truchas metal casting, welding, and additive manufacturing simulations, it lacks many of the modeling capabilites needed for real applications.

Jibben, Zechariah↗

NASA NTRS1988

Computer sciences

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Smith, Paul H.↗

NASA NTRS1992

Developing A Navier-Stokes Algorithm For Supercomputers

Report discusses development of algorithm for solution of Navier-Stokes equations of flow on parallel-processing supercomputers. Involves combination of prior techniques to form algorithm to compute flows in complicated three-dimensional configurations. Includes explicit finite-difference numerical-integration scheme applicable to flows represented by hierarchy of mathematical models ranging from Euler to full Navier-Stokes. Of interest to researchers looking for ways to structure problems for greater computational efficiency.

Swisshelm, Julie M.↗

NASA NTRS1995

Circuit for high resolution decoding of multi-anode microchannel array detectors

A circuit for high resolution decoding of multi-anode microchannel array detectors consisting of input registers accepting transient inputs from the anode array; anode encoding logic circuits connected to the input registers; midpoint pipeline registers connected to the anode encoding logic circuits; and pixel decoding logic circuits connected to the midpoint pipeline registers is described. A high resolution algorithm circuit operates in parallel with the pixel decoding logic circuit and computes a high resolution least significant bit to enhance the multianode microchannel array detector's spatial resolution by halving the pixel size and doubling the number of pixels in each axis of the anode array. A multiplexer is connected to the pixel decoding logic circuit and allows a user selectable pixel address output according to the actual multi-anode microchannel array detector anode array size. An output register concatenates the high resolution least significant bit onto the standard ten bit pixel address location to provide an eleven bit pixel address, and also stores the full eleven bit pixel address. A timing and control state machine is connected to the input registers, the anode encoding logic circuits, and the output register for managing the overall operation of the circuit.

Kasle, David B.↗

NASA NTRS2019

Testing Scientific Software: Challenges and Remedies

Over the past two decades, the emergence of highly effective software testing frameworks has greatly simplified the development and use of unit tests and has led to new software development paradigms such as test driven development (TDD). However, scientific computing introduces a number of unique testing challenges, including numerical algorithms, distributed parallelism, and exascale environments. This presentation will begin with a brief introduction to unit testing, testing frameworks, and some simple examples using pFUnit, a unit testing framework for Fortran + MPI. I will then take a closer look at several of the obstacles one faces when testing technical software and suggest methodologies that can mitigate these difficulties.

Clune, Tom↗

DOE OSTI2017

Pececillo

Carlson, Neil↗

DOE OSTI2018

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position, depth, etc., obtained from such an Internet of Floating Things, we illustrate how, with a specialized protocol, data can be communicated to cloud resources, even when using delayed, intermittent, or disconnected networks. We then propose a method for automatic sensor calibration based on a novel reputation approach. Sampled depth data are interpolated efficiently on a cloud computing platform in order to provide a continuously updated bathymetric database. Our prototype implementation uses the FACE-IT Galaxy workflow engine to manage network communication and exploits the computational power of GPGPUs in a virtualized cloud environment, working with a CUDA-parallel algorithm, for efficient data processing. We report on an initial evaluation involving data from a sailing vessel in Italian coastal waters.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Very fast motion planning for highly dexterous-articulated robots

Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.

Challou, Daniel J.↗

DOE OSTI2022

Towards a more general understanding of the algorithmic utility of recurrent connections

Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation” algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and construct hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to propagating multiple interacting tags and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Simulations of relativistic quantum plasmas using real-time lattice scalar QED

Real-time lattice quantum electrodynamics (QED) provides a unique tool for simulating plasmas in the strong-field regime, where collective plasma scales are not well separated from relativistic-quantum scales. As a toy model, we study scalar QED, which describes self-consistent interactions between charged bosons and electromagnetic fields. To solve this model on a computer, we first discretize the scalar-QED action on a lattice, in a way that respects geometric structures of exterior calculus and U(1)-gauge symmetry. The lattice scalar QED can then be solved, in the classical-statistics regime, by advancing an ensemble of statistically equivalent initial conditions in time, using classical field equations obtained by extremizing the discrete action. To demonstrate the capability of our numerical scheme, we apply it to two example problems. The first example is the propagation of linear waves, where we recover analytic wave dispersion relations using numerical spectrum. The second example is an intense laser interacting with a one-dimensional plasma slab, where we demonstrate natural transition from wakefield acceleration to pair production when the wave amplitude exceeds the Schwinger threshold. Our real-time lattice scheme is fully explicit and respects local conservation laws, making it reliable for long-time dynamics. The algorithm is readily parallelized using domain decomposition, and the ensemble may also be computed using quantum parallelism in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗