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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PMU-Based Decoupled State Estimation for Unsymmetrical Power Systems

Modal decomposition of measurement equations has already been shown to simplify the formulation and resulting computational complexity of three-phase state estimation of systems where all the transmission lines are three-phase and fully transposed. When there are non-transposed and/or mixed-phase lines, modal decomposition can no longer fully decouple the threephase measurement equations. Here, this paper addresses the above shortcoming by proposing a simple yet practical solution based on the commonly used numerical compensation techniques. Thus, it enables application of the powerful decoupling approach to any type of three-phase networks which may contain non-transposed or mixed-phase lines and are fully observable by PMUs. The proposed procedure modifies the measurement set by deriving additive terms that compensate for the neglected unsymmetrical effects. It will be shown that unbalanced systems including nontransposed and mixed-phase elements, can still be transformed into three decoupled subsystems and solved in parallel by the proposed approach. Performance of the proposed algorithm is validated against several IEEE test cases.

42 ENGINEERING↗
DOE OSTI2020

Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]

This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution. This software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.

Hasandka, Adarsh↗
DOE OSTI2017

RAJA Performance Suite

The RAJA Performance Suite is designed to evaluate performance of the RAJA performance portability library on a wide variety of important high performance computing (HPC) algorithmic lulmels. These kernels assess compiler optimizations and various parallel programming model backends accessible through RAJA, such as OpenMP, CUDA, etc. The Initial version of the suite contains 25 computational kernels, each of which appears in 6 variants: Baseline SequcntiaJ, RAJA SequentiaJ, Baseline OpenMP, RAJA OpenMP, Baseline CUDA, RAJA CUDA. All variants of each kernel perform essentially the same mathematical operations and the loop body code for each kernel is identical across all variants. There are a few kernels, such as those that contain reduction operations, that require CUDA-specific coding for their CUDA variants. ActuaJ computer instructions executed and how they run in parallel differs depending on the parallel programming model backend used and which optimizations are perfonned by the compiler used to build the Perfonnance Suite executable. The Suite will be used primarily by RAJA developers to perform regular assessments of RAJA performance across a range of hardware platforms and compilers as RAJA features are being developed. It will also be used by LLNL hardware and software vendor panners for new defining requirements for future computing platform procurements and acceptance testing. In particular, the RAJA Performance Suite will be used for compiler acceptance testing of the upcoming CORAUSierra machine {initial LLNL delivery expected in late-2017/early 2018) and the CORAL-2 procurement. The Suite will aJso be used to generate concise source code reproducers of compiler and runtime issues we uncover so that we may provide them to relevant vendors to be fixed.

Hornung, RichardD.↗
DOE OSTI2017

Extreme scale unstructured adaptive CFD for aerodynamic flow control

Understanding the flow of fluid, either liquid or gas, through and around solid bodies has challenged man since the dawn of scientific inquiry. Many of the great minds of science and mathematics have progressively built up a hierarchy of fluid models since fluid flow impacts our lives in so many fundamental ways - from the early days of flow of water in viaducts to cities, to today's flight of planes. This chapter is concerned with the computational modeling of turbulent flow around aerodynamic bodies such as planes and wind turbines. In this case, viscous effects near the solid bodies create very thin boundary layers that yield highly anisotropic (gradients normal to the surface may be 10 6 larger than gradients along the surface) solutions to the governing non-linear partial differential equations (PDE); the Navier-Stokes equations. Furthermore, turbulent flows develop extremely broad ranges of length and time scales motivating the use of discretization methods capable of employing adaptivity and implicit time integration. The combination of these features - non-linear, anisotropy, adaptivity, and implicit - dramatically raise the complexity of the discretization, posing large challenges to efficient scalable parallel implementation. However, through careful design, the more complex algorithms can provide great reductions in computational cost relative to simpler methods (e.g., Cartesian grids with explicit time integration) that are easier to mate efficiently to hardware. In this chapter, we not only describe our approach but we also address the fact that while complex algorithms may never be as efficient flop-for-flop as simple methods, in the important measure of science-per-core-hour, they can still win big by making complex features like adaptivity and implicit methods as efficient and scalable as possible.

42 ENGINEERING↗
DOE OSTI2014

MueLu User's Guid for Trilinos Version 11.12.

This is the official user guide for the M UE L U multigrid library in Trilinos version 11.12. This guide provides an overview of M UE L U , its capabilities, and instructions for new users who want to start using M UE L U with a minimum of effort. Detailed information is given on how to drive M UE L U through its XML interface. Links to more advanced use cases are given. This guide gives information on how to achieve good parallel performance, as well as how to introduce new algorithms. Finally, readers will find a comprehensive listing of available M UE L U options. Any options not documented in this manual should be considered strictly experimental.

Hu, Jonathan Joseph↗
DOE OSTI2015

Methods and Tools to allow molecular flow simulations to be coupled to higher level continuum descriptions of flows in porous/fractured media and aerosol/dust dynamics

The purpose of this project was to develop methods and tools that will aid in safety evaluation of nuclear fuels and licensing of nuclear reactors relating to accidents.The objectives were to develop more detailed and faster computations of fission product transport and aerosol evolution as they generally relate to nuclear fuel and/or nuclear reactor accidents. The two tasks in the project related to molecular transport in nuclear fuel and aerosol transport in reactor vessel and containment. For both the tasks, explorations of coupling of Direct Simulation Monte Carlo with Navier-Stokes solvers or the Sectional method were not successful. However, Mesh free methods for the Direct Simulation Monte Carlo method were successfully explored.These explorations permit applications to porous and fractured media, and arbitrary geometries.The computations were carried out in Mathematica and are fully parallelized. The project has resulted in new computational tools (algorithms and programs) that will improve the fidelity of computations to actual physics, chemistry and transport of fission products in the nuclear fuel and aerosol in reactor primary and secondary containments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Documentation for MeshKit - Reactor Geometry (&mesh) Generator

This report gives documentation for using MeshKit’s Reactor Geometry (and mesh) Generator (RGG) GUI and also briefly documents other algorithms and tools available in MeshKit. RGG is a program designed to aid in modeling and meshing of complex/large hexagonal and rectilinear reactor cores. RGG uses Argonne’s SIGMA interfaces, Qt and VTK to produce an intuitive user interface. By integrating a 3D view of the reactor with the meshing tools and combining them into one user interface, RGG streamlines the task of preparing a simulation mesh and enables real-time feedback that reduces accidental scripting mistakes that could waste hours of meshing. RGG interfaces with MeshKit tools to consolidate the meshing process, meaning that going from model to mesh is as easy as a button click. This report is designed to explain RGG v 2.0 interface and provide users with the knowledge and skills to pilot RGG successfully. Brief documentation of MeshKit source code, tools and other algorithms available are also presented for developers to extend and add new algorithms to MeshKit. RGG tools work in serial and parallel and have been used to model complex reactor core models consisting of conical pins, load pads, several thousands of axially varying material properties of instrumentation pins and other interstices meshes.

Jain, Rajeev↗
DOE OSTI2017

Extreme Scale Unstructured Adaptive CFD: From Multiphase Flow to Aerodynamic Flow Control

Understanding the flow of fluid, either liquid or gas, through and around solid bodies has challenged man since the dawn of scientific inquiry. Many of the great minds of science and math have progressively built up a hierarchy of fluid models. This report is concerned with the computational modeling of turbulent flow around aerodynamic bodies such as planes and wind turbines. In this case, viscous effects near the solid bodies create very thin boundary layers that yield highly anisotropic (gradients normal to the surface may be 10^6 times larger than gradients along the surface) solutions to the governing non-linear partial differential equations (PDE); the Navier-Stokes equations. Furthermore, turbulent flows develop extremely broad ranges of length and time scales.This disparity motivates the use of discretization methods capable of employing adaptivity and implicit time integration. The combination of these features (non-linear, anisotropy, adaptivity, andimplicit) dramatically raise the complexity of the discretization, posing large challenges to efficient scalable parallel implementation. However, through careful design, the more complex algorithms can provide great reductions in computational cost relative to simpler methods (e.g., Cartesian grids with explicit time integration) that are easier to mate efficiently to hardware. In this report, we not only describe our approach but we also address the fact that while complex algorithms may never be as efficient flop-for-flop as simple methods, in the important measure of science-per-core-hour, they can still win big by making complex features like adaptivity and implicit methods as efficient and scalable as possible.

42 ENGINEERING↗
DOE OSTI2019

MueLu User's Guide

This is the official user guide for MUELU multigrid library in Trilinos version 12.13 (Dev). This guide provides an overview of MUELU, its capabilities, and instructions for new users who want to start using MUELU with a minimum of effort. Detailed information is given on how to drive MUELU through its XML interface. Links to more advanced use cases are given. This guide gives information on how to achieve good parallel performance, as well as how to introduce new algorithms Finally, readers will find a comprehensive listing of available MUELU options. Any options not documented in this manual should be considered strictly experimental.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Development of Multistep and Degenerate Variational Integrators for Applications in Plasma Physics

Geometric integrators yield high-fidelity numerical results by retaining conservation laws in the time advance. A particularly powerful class of geometric integrators is symplectic integrators, which are widely used in orbital mechanics and accelerator physics. An important application presently lacking symplectic integrators is the guiding center motion of magnetized particles represented by non-canonical coordinates. Because guiding center trajectories are foundational to many simulations of magnetically confined plasmas, geometric guiding center algorithms have high potential for impact. The motivation is compounded by the need to simulate long-pulse fusion devices, including ITER, and opportunities in high performance computing, including the use of petascale resources and beyond. This dissertation uses a systematic procedure for constructing geometric integrators - known as variational integration - to deliver new algorithms for guiding center trajectories and other plasma-relevant dynamical systems. These variational integrators are non-trivial because the Lagrangians of interest are degenerate - the Euler-Lagrange equations are first-order differential equations and the Legendre transform is not invertible. The first contribution of this dissertation is that variational integrators for degenerate Lagrangian systems are typically multistep methods. Multistep methods admit parasitic mode instabilities that can ruin the numerical results. These instabilities motivate the second major contribution: degenerate variational integrators. By replicating the degeneracy of the continuous system, degenerate variational integrators avoid parasitic mode instabilities. The new methods are therefore robust geometric integrators for degenerate Lagrangian systems. These developments in variational integration theory culminate in one-step degenerate variational integrators for non-canonical magnetic field line flow and guiding center dynamics. The guiding center integrator assumes coordinates such that one component of the magnetic field is zero; it is shown how to construct such coordinates for nested magnetic surface configurations. Additionally, collisional drag effects are incorporated in the variational guiding center algorithm for the first time, allowing simulation of energetic particle thermalization. Advantages relative to existing canonical-symplectic and non-geometric algorithms are numerically demonstrated. All algorithms have been implemented as part of a modern, parallel, ODE-solving library, suitable for use in high-performance simulations.

Guiding Center↗
DOE OSTI2021

Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple events using nested OpenMP parallelism on CPU or CUDA streams on GPU. The new implementation along with earlier work in developing a parallelized and vectorized implementation of the combinatoric Kalman filter algorithm has enabled efficient global reconstruction of the entire event on modern computer architectures. We demonstrate the performance of the new implementation on Intel Xeon and NVIDIA GPU architectures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Efficient Routing of Quantum LDPC Codes on Programmable 2D Toric Architectures

Quantum low-density parity-check codes are promising candidates towards scalable fault-tolerant quantum computation. Among these, bivariate bicycle (BB) codes offer superior encoding rates and large code distance compared to surface codes. However, their requirement on long-range stabilizer measurements poses significant challenges for implementation on realistic hardware with limited connectivity, such as superconducting circuit platforms. In this work, we introduce a novel hardware-software co-design that leverages a programmable communication network architecture to address these limitations. Our approach utilizes a 2D toric network of oscillators as a flexible communication fabric linking qubits at each site. Such architecture significantly reduces the number of long-range couplers required from O ( n ) to O (√ n ). Dual-rail qubits, along with native gates including Swap-Wait-Swap gates and beamsplitter SWAPs, ensure that long-range two-qubit gates can be executed with high fidelity and low latency. To further enhance performance, our qubit layout and routing algorithm utilize symmetries of the codes and enable maximum parallelism for long-range two-qubit gates, maintaining a low syndrome extraction cycle duration and scalability over the code length. We perform circuit-level simulation with realistic noise modeling based on experimental hardware parameters, observing an logical error rate per logical qubit per cycle of 3.06% for [[18,4,4]] BB code, 2.6× less than the existing experimental result. These findings provide a practical roadmap and identify key technological advancements needed to achieve low-overhead fault-tolerant quantum computing at scale.

Liu, Kun [Yale Univ., New Haven, CT (United States↗
DOE OSTI2017

Task-based Parallel Computation of the Density Matrix in Quantum-based Molecular Dynamics using Graph Partitioning

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms. These constraints arise due to expensive self-consistent ground-state electronic structure calculations that can often scale cubically with the number of atoms. Linearly scaling methods depend on computing the density matrix P from the Hamiltonian matrix H by exploiting the sparsity in both matrices. The second-order spectral projection (SP2) algorithm is an O(N) algorithm that computes P with a sequence of 40 - 50 matrix-matrix multiplications. In this paper, we present task-based implementations of a recently developed data-parallel graph-based approach to the SP2 algorithm, G-SP2. We represent the density matrix P as an undirected graph and use graph partitioning techniques to divide the computation into smaller independent tasks. The partitions thus obtained are generally not of equal size and give rise to undesirable load imbalances in standard MPI-based implementations. This load-balancing challenge can be mitigated by dynamically scheduling parallel computations at runtime using task-based programming models. We develop task-based implementations of the data-parallel G-SP2 algorithm using both Intel's Concurrent Collections (CnC) as well as the Charm++ programming model and evaluate these implementations for future use. Scaling and performance results of our implementations are investigated for representative segments of QMD simulations for solvated protein systems containing more than 10,000 atoms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Semicoherent symmetric quantum processes: Theory and applications

Discovering pragmatic and efficient approaches to construct ε-approximations of quantum operators such as real (imaginary) time-evolution propagators in terms of the basic quantum operations (gates) is challenging. Prior ε-approximations are invaluable, in that they enable the compilation of classical and quantum algorithm modeling of, e.g., dynamical and thermodynamic quantum properties. In parallel, symmetries are powerful tools concisely describing the fundamental laws of nature; the symmetric underpinnings of physical laws have consistently provided profound insights and substantially increased predictive power. In this work, we consider the interplay between the ε-approximate processes and the exact symmetries in a semicoherent context—where measurements occur at each logical clock cycle. Here we draw inspiration from Pascual Jordan's groundbreaking formulation of nonassociative, but commutative, symmetric algebraic form. Our symmetrized formalism is then applied in various domains such as quantum random walks, real-time evolutions, variational algorithm ansatzes, and efficient entanglement verification. Our work paves the way for a deeper understanding and greater appreciation of how symmetries can be used to control quantum dynamics in settings where coherence is a limited resource.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

WE-G-18A-08: Axial Cone Beam DBPF Reconstruction with Three-Dimensional Weighting and Butterfly Filtering

Purpose: With the major benefit in dealing with data truncation for ROI reconstruction, the algorithm of differentiated backprojection followed by Hilbert filtering (DBPF) is originally derived for image reconstruction from parallel- or fan-beam data. To extend its application for axial CB scan, we proposed the integration of the DBPF algorithm with 3-D weighting. In this work, we further propose the incorporation of Butterfly filtering into the 3-D weighted axial CB-DBPF algorithm and conduct an evaluation to verify its performance. Methods: Given an axial scan, tomographic images are reconstructed by the DBPF algorithm with 3-D weighting, in which streak artifacts exist along the direction of Hilbert filtering. Recognizing this orientation-specific behavior, a pair of orthogonal Butterfly filtering is applied on the reconstructed images with the horizontal and vertical Hilbert filtering correspondingly. In addition, the Butterfly filtering can also be utilized for streak artifact suppression in the scenarios wherein only partial scan data with an angular range as small as 270° are available. Results: Preliminary data show that, with the correspondingly applied Butterfly filtering, the streak artifacts existing in the images reconstructed by the 3-D weighted DBPF algorithm can be suppressed to an unnoticeable level. Moreover, the Butterfly filtering also works at the scenarios of partial scan, though the 3-D weighting scheme may have to be dropped because of no sufficient projection data are available. Conclusion: As an algorithmic step, the incorporation of Butterfly filtering enables the DBPF algorithm for CB image reconstruction from data acquired along either a full or partial axial scan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Improving the Performance of the Extreme-scale Simulator

Investigating the performance of parallel applications at scale on future high-performance computing (HPC) architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. The Extreme-scale Simulator (xSim) is a simulation-based toolkit for investigating the performance of parallel applications at scale. xSim scales to millions of simulated Message Passing Interface (MPI) processes. The overhead introduced by a simulation tool is an important performance and productivity aspect. This paper documents two improvements to xSim: (1) a new deadlock resolution protocol to reduce the parallel discrete event simulation management overhead and (2) a new simulated MPI message matching algorithm to reduce the oversubscription management overhead. The results clearly show a significant performance improvement, such as by reducing the simulation overhead for running the NAS Parallel Benchmark suite inside the simulator from 1,020\% to 238% for the conjugate gradient (CG) benchmark and from 102% to 0% for the embarrassingly parallel (EP) and benchmark, as well as, from 37,511% to 13,808% for CG and from 3,332% to 204% for EP with accurate process failure simulation.

Engelmann, Christian↗
DOE OSTI2020

ArborX: A Performance Portable Geometric Search Library

Searching for geometric objects that are close in space is a fundamental component of many applications. The performance of search algorithms comes to the forefront as the size of a problem increases both in terms of total object count as well as in the total number of search queries performed. Scientific applications requiring modern leadership-class supercomputers also pose an additional requirement of performance portability, i.e., being able to efficiently utilize a variety of hardware architectures. In this article, we introduce a new open-source C++ search library, ArborX, which we have designed for modern supercomputing architectures. Herein, we examine scalable search algorithms with a focus on performance, including a highly efficient parallel bounding volume hierarchy implementation, and propose a flexible interface making it easy to integrate with existing applications. We demonstrate the performance portability of ArborX on multi-core CPUs and GPUs and compare it to the state-of-the-art libraries such as Boost.Geometry.Index and nanoflann.

97 MATHEMATICS AND COMPUTING↗