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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CoSyR: A novel beam dynamics code for the modeling of synchrotron radiation effects

The self-consistent nonlinear dynamics of a relativistic charged particle beam interacting with its complete self-fields is a fundamental problem underpinning many of the accelerator design issues in high brightness beam applications, as well as the development of advanced accelerators. Particularly, synchrotron radiation induced effects in a magnetic dispersive beamline element can lead to collective beam instabilities and emittance growth. A novel beam dynamics code is developed based on a Lagrangian method for the calculation of the particles’ radiation near-fields using wavefront/wavelet meshes via the Green’s function of the Maxwell equations. These fields are then interpolated onto a moving mesh for dynamic update of the beam. This method allows radiation co-propagation and self-consistent interaction with the beam in 2D/3D simulations at greatly reduced numerical errors. Multiple levels of parallelisms are inherent in this method and implemented in our code CoSyR to enable at-scale simulations of nonlinear beam dynamics on modern computing platforms using MPI, multi-threading, and GPUs. Here, the current 2D implementation of CoSyR has been used to evaluate the transverse and longitudinal coherent radiation effects on the beam and to investigate beam optics designs proposed for mitigation of beam brightness degradation in a magnetic bunch compressor. In this paper, the design of CoSyR, as well as the benchmark with other coherent synchrotron radiation models, are described and discussed. Extension of the core algorithms to 3D is possible and planned.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1998

Performance Analysis of an Actor-Based Distributed Simulation

Object-oriented design of simulation programs appears to be very attractive because of the natural association of components in the simulated system with objects. There is great potential in distributing the simulation across several computers for the purpose of parallel computation and its consequent handling of larger problems in less elapsed time. One approach to such a design is to use "actors", that is, active objects with their own thread of control. Because these objects execute concurrently, communication is via messages. This is in contrast to an object-oriented design using passive objects where communication between objects is via method calls (direct calls when they are in the same address space and remote procedure calls when they are in different address spaces or different machines). This paper describes a performance analysis program for the evaluation of a design for distributed simulations based upon actors.

Schoeffler, James D.↗
NASA NTRS2003

Support of Multidimensional Parallelism in the OpenMP Programming Model

OpenMP is the current standard for shared-memory programming. While providing ease of parallel programming, the OpenMP programming model also has limitations which often effect the scalability of applications. Examples for these limitations are work distribution and point-to-point synchronization among threads. We propose extensions to the OpenMP programming model which allow the user to easily distribute the work in multiple dimensions and synchronize the workflow among the threads. The proposed extensions include four new constructs and the associated runtime library. They do not require changes to the source code and can be implemented based on the existing OpenMP standard. We illustrate the concept in a prototype translator and test with benchmark codes and a cloud modeling code.

Jin, Hao-Qiang↗
DOE OSTI2019

Exploring Integer Sum Reduction using Atomics on Intel CPU

Atomic functions are useful in updating a shared variable by multiple threads, barrier synchronizations, constructing complex data structures, and building high-level frameworks. In this paper, we focus on the evaluation and analysis of integer sum reduction, a common data parallel primitive. We convert the sequential reduction into parallel OpenCL implementations on the CPU. We also develop three micro kernels, which allow us to understand the relationships between the kernel performance and the operations involved in reduction. The results of the micro kernels show that increasing the work-group size linearly can linearly improve the kernel performance. There is a sweet spot in the relationship between the work-group size and barrier synchronization overhead. The performance of the atomics over local memory are not sensitive to the work-group size. The sum reduction kernel with vectorized memory accesses can improve the performance of the baseline kernel for a wide range of work-group sizes. However, the vectorization efficiency shrinks with the growing work-group size. We also find that the vendor’s default OpenCL kernel optimization does not improve the kernel performance. On average, disabling the optimization can reduce the execution time of the kernel with vectorized memory accesses by 15%. We attribute the performance drop to the fact that the default kernel optimizations instantiate a large number of atomics over global memory when implicitly vectorizing the kernel computation.

atomics↗
DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Parallel general purpose multiobjective optimization framework with application to electron beam dynamics

Particle accelerators are invaluable tools for research in the basic and applied sciences, such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a nontrivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. The Argonne Wakefield Accelerator facility has some unique challenges resulting from its purpose to carry out advanced accelerator R&D. Individual experiments often have challenging beam requirements, and the physical configuration of the beam lines is often changed to accommodate the variety of supported experiments. The need for rapid deployment of different operational settings further complicates the optimization work that must be done for multiple constraints and challenging operational regimes. One example of this is an independently staged two-beam acceleration experiment which requires the construction of an additional beam line (this is now in progress). The high charge drive beam, well into the space charge regime, must be threaded through small aperture (17.6 mm) decelerating structures. In addition, the bunch length must be sufficiently short to maximize power generation in the decelerator. We propose to tackle this problem by means of multiobjective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame, a fast and scalable software framework is required. In this paper, we present a general-purpose framework for simulation-based multiobjective optimization methods that allows the automatic investigation of optimal sets of machine parameters. Using evolutionary algorithms as the optimizer and opal as the forward solver, validation experiments and results of multiobjective optimization problems in the domain of beam dynamics are presented. Optimized solutions for the new high charge drive beam line found by the framework were used to finish the design of a two beam acceleration experiment. The selected solution along with the associated beam parameters is presented.

43 PARTICLE ACCELERATORS↗
NASA NTRS2002

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

In this paper we describe how to apply powerful performance analysis techniques to understand the behavior of multilevel parallel applications. We use the Paraver/OMPItrace performance analysis system for our study. This system consists of two major components: The OMPItrace dynamic instrumentation mechanism, which allows the tracing of processes and threads and the Paraver graphical user interface for inspection and analyses of the generated traces. We describe how to use the system to conduct a detailed comparative study of a benchmark code implemented in five different programming paradigms applicable for shared memory

Jost, Gabriele↗
NASA NTRS1989

Kilometric radiation power flux dependence on area of discrete aurora

Kilometer wavelength radiation, measured from distant positions over the North Pole and over the Earth's equator, was compared to the area of discrete aurora imaged by several low-altitude spacecraft. Through correlative studies of auroral kilometric radiation (AKR) with about two thousand auroral images, a stereoscopic view of the average auroral acceleration region was obtained. A major result is that the total AKR power increases as the area of the discrete auroral oval increases. The implications are that the regions of parallel potentials or the auroral plasma cavities, in which AKR is generated, must possess the following attributes: (1) they are shallow in altitude and their radial position depends on wavelength, (2) they thread flux tubes of small cross section, (3) the generation mechanism in them reaches a saturation limit rapidly, and (4) their distribution over the discrete auroral oval is nearly uniform. The above statistical results are true for large samples collected over a long period of time (about six months). In the short term, AKR frequently exhibits temporal variations with scales as short as three minutes (the resolution of the averaged data used). These fluctuations are explainable by rapid quenchings as well as fast starts of the electron cyclotron maser mechanism. There were times when AKR was present at substantial power levels while optical emissions were below instrument thresholds. A recent theoretical result may account for this set of observations by predicting that suprathermal electrons, of energies as low as several hundred eV, can generate second harmonic AKR. The indirect observations of second harmonic AKR require that these electrons have mirror points high above the atmosphere so as to minimize auroral light emissions. The results provide evidence supporting the electron cyclotron maser mechanism.

Saflekos, N. A.↗
DOE OSTI2015

Fano effect dominance over Coulomb blockade in transport properties of parallel coupled quantum dot system

Theoretical study of the Coulomb blockade effect on transport properties (Transmission Probability and I-V characteristics) for varied configuration of coupled quantum dot system has been studied by using Non Equilibrium Green Function(NEGF) formalism and Equation of Motion(EOM) method in the presence of magnetic flux. The self consistent approach and intra-dot Coulomb interaction is being taken into account. As the key parameters of the coupled quantum dot system such as dot-lead coupling, inter-dot tunneling and magnetic flux threading through the system can be tuned, the effect of asymmetry parameter and magnetic flux on this tuning is being explored in Coulomb blockade regime. The presence of the Coulomb blockade due to on-dot Coulomb interaction decreases the width of transmission peak at energy level ε + U and by adjusting the magnetic flux the swapping effect in the Fano peaks in asymmetric and symmetric parallel configuration sustains despite strong Coulomb blockade effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

DIY2

DIY2 is a data parallel out-of-core library, written in C++. It provides facilities for domain decomposition into blocks and abstracts both neighborhood and global communication patterns to the level of blocks. DIY2 supports automatic threading. It also provides a data serialization mechanism, using which it allows for automatic movement of blocks in and out of core.

Morozov, Dmitriy↗
DOE OSTI2015

OpenACC acceleration of an unstructured CFD solver based on a reconstructed discontinuous Galerkin method for compressible flows

Here, an OpenACC directive-based graphics processing unit (GPU) parallel scheme is presented for solving the compressible Navier–Stokes equations on 3D hybrid unstructured grids with a third-order reconstructed discontinuous Galerkin method. The developed scheme requires the minimum code intrusion and algorithm alteration for upgrading a legacy solver with the GPU computing capability at very little extra effort in programming, which leads to a unified and portable code development strategy. A face coloring algorithm is adopted to eliminate the memory contention because of the threading of internal and boundary face integrals. A number of flow problems are presented to verify the implementation of the developed scheme. Timing measurements were obtained by running the resulting GPU code on one Nvidia Tesla K20c GPU card (Nvidia Corporation, Santa Clara, CA, USA) and compared with those obtained by running the equivalent Message Passing Interface (MPI) parallel CPU code on a compute node (consisting of two AMD Opteron 6128 eight-core CPUs (Advanced Micro Devices, Inc., Sunnyvale, CA, USA)). Speedup factors of up to 24× and 1.6× for the GPU code were achieved with respect to one and 16 CPU cores, respectively. The numerical results indicate that this OpenACC-based parallel scheme is an effective and extensible approach to port unstructured high-order CFD solvers to GPU computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Framework for Lattice QCD Calculations on GPUs

Efficient calculation of the greatest common divisor (GCD) for big integers each whose number of bits is greater than or equal to 1024 has drawn a considerable amount of attention because it can be used to detect a weakness of the RSA security infrastructure. This paper presents a parallel binary GCD algorithm and its implementation for big integers on the Intel Xeon Phi coprocessor. This algorithm is capable of computing GCDs efficiently on many pairs of big integers in parallel by utilizing all cores on a Xeon Phi coprocessor as well as taking advantage of all vector processing units of the coprocessor to speed up critical integer operations within the algorithm. Using 240 threads on a Xeon Phi coprocessor to carry out GCD calculations for a large amount of 2048-bit integers, the implementation achieves the speedup of 30 times over a sequential binary GCD algorithm implementation on a single CPU core, and it delivers twice amount of performance in comparison to the same sequential binary GCD implementation running on 240 threads of the Xeon Phi.

Winter, F. T.↗
DOE OSTI2022

ECP-ExaGraph/netAlign

We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. We demonstrate almost a 20-fold speedup using 40 threads on an 8 processor Intel Xeon E7-8870 system and now solve real-world problems in 36 seconds instead of 10 minutes

Khan, Arif↗
NASA NTRS1997

Fully Threaded Tree for Adaptive Refinement Fluid Dynamics Simulations

A fully threaded tree (FTT) for adaptive refinement of regular meshes is described. By using a tree threaded at all levels, tree traversals for finding nearest neighbors are avoided. All operations on a tree including tree modifications are O(N), where N is a number of cells, and are performed in parallel. An efficient implementation of the tree is described that requires 2N words of memory. A filtering algorithm for removing high frequency noise during mesh refinement is described. A FTT can be used in various numerical applications. In this paper, it is applied to the integration of the Euler equations of fluid dynamics. An adaptive mesh time stepping algorithm is described in which different time steps are used at different l evels of the tree. Time stepping and mesh refinement are interleaved to avoid extensive buffer layers of fine mesh which were otherwise required ahead of moving shocks. Test examples are presented, and the FTT performance is evaluated. The three dimensional simulation of the interaction of a shock wave and a spherical bubble is carried out that shows the development of azimuthal perturbations on the bubble surface.

FINITE ELEMENT ANALYSIS↗
DOE OSTI2020

Scalable line and plane relaxation in a parallel structured multigrid solver

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother — producing error compatible for coarse-grid correction with structured coarsening. Here, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver’s execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers — directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Software Defined Radio with Parallelized Software Architecture

This software implements software-defined radio procession over multicore, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to approx.50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.

Heckler, Greg↗
DOE OSTI2021

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs

Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.

Thavappiragasam, Mathialakan↗
DOE OSTI2016

Closeout Report ARRA supplement to DE-FG02-08ER41546, 03/15/2010 to 03/14/2011 - Advanced Transfer Map Methods for the Description of Particle Beam Dynamics

The ARRA funds were utilized to acquire a cluster of high performance computers, consisting of one Altus 2804 Server based on a Quad AMD Opteron 6174 12C with 4 2.2 GHz nodes of 12 cores each, resulting in 48 directly usable cores; as well as a Relion 1751 Server using an Intel Xeon X5677 consisting of 4 3.46 GHz cores supporting 8 threads. Both systems run the Unix flavor CentOS, which is designed for use without need of updates, which greatly enhances their reliability. The systems are used to operate our COSY INFINITY environment which supports MPI parallelization. The units arrived at MSU in September 2010, and were taken into operation shortly thereafter.

43 PARTICLE ACCELERATORS↗