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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

We introduce a task-parallel algorithm for sparse incomplete Cholesky factorization that utilizes a 2D sparse partitioned-block layout of a matrix. Our factorization algorithm follows the idea of algorithms-by-blocks by using the block layout. The algorithm-byblocks approach induces a task graph for the factorization. These tasks are inter-related to each other through their data dependences in the factorization algorithm. To process the tasks on various manycore architectures in a portable manner, we also present a portable tasking API that incorporates different tasking backends and device-specific features using an open-source framework for manycore platforms i.e., Kokkos. A performance evaluation is presented on both Intel Sandybridge and Xeon Phi platforms for matrices from the University of Florida sparse matrix collection to illustrate merits of the proposed task-based factorization. Experimental results demonstrate that our task-parallel implementation delivers about 26.6x speedup (geometric mean) over single-threaded incomplete Choleskyby- blocks and 19.2x speedup over serial Cholesky performance which does not carry tasking overhead using 56 threads on the Intel Xeon Phi processor for sparse matrices arising from various application problems.

2D layout↗
NASA NTRS2012

Real-Time Adaptive Lossless Hyperspectral Image Compression using CCSDS on Parallel GPGPU and Multicore Processor Systems

The proposed CCSDS (Consultative Committee for Space Data Systems) Lossless Hyperspectral Image Compression Algorithm was designed to facilitate a fast hardware implementation. This paper analyses that algorithm with regard to available parallelism and describes fast parallel implementations in software for GPGPU and Multicore CPU architectures. We show that careful software implementation, using hardware acceleration in the form of GPGPUs or even just multicore processors, can exceed the performance of existing hardware and software implementations by up to 11x and break the real-time barrier for the first time for a typical test application.

realtime↗
NASA NTRS2015

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design.

Parallel Flow Path modeling↗
NASA NTRS2015

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine, NASA Advanced Air Vehicles Program - Commercial Supersonic Technology Project - AeroServoElasticity

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Compressor Modeling Modeling↗
DOE OSTI2012

Applied Parallel Metadata Indexing

The GPFS Archive is parallel archive is a parallel archive used by hundreds of users in the Turquoise collaboration network. It houses 4+ petabytes of data in more than 170 million files. Currently, users must navigate the file system to retrieve their data, requiring them to remember file paths and names. A better solution might allow users to tag data with meaningful labels and searach the archive using standard and user-defined metadata, while maintaining security. last summer, I developed the backend to a tool that adheres to these design goals. The backend works by importing GPFS metadata into a MongoDB cluster, which is then indexed on each attribute. This summer, the author implemented security and developed the user interfae for the search tool. To meet security requirements, each database table is associated with a single user, which only stores records that the user may read, and requires a set of credentials to access. The interface to the search tool is implemented using FUSE (Filesystem in USErspace). FUSE is an intermediate layer that intercepts file system calls and allows the developer to redefine how those calls behave. In the case of this tool, FUSE interfaces with MongoDB to issue queries and populate output. A FUSE implementation is desirable because it allows users to interact with the search tool using commands they are already familiar with. These security and interface additions are essential for a usable product.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Structured building model reduction toward parallel simulation

Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to improve simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inherently limited by inter-processor communication. This paper bridges these disparate techniques to implement efficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allocate processing resources. Experimental results demonstrate faster simulation and low error without any interprocessor communication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Parallel Multi-Domain Solution Methodology Applied to Nonlinear Thermal Transport Problems in Nuclear Fuel Pins

This paper describes an efficient and nonlinearly consistent parallel solution methodology for solving coupled nonlinear thermal transport problems that occur in nuclear reactor applications over hundreds of individual 3D physical subdomains. Efficiency is obtained by leveraging knowledge of the physical domains, the physics on individual domains, and the couplings between them for preconditioning within a Jacobian Free Newton Krylov method. Details of the computational infrastructure that enabled this work, namely the open source Advanced Multi-Physics (AMP) package developed by the authors is described. Details of verification and validation experiments, and parallel performance analysis in weak and strong scaling studies demonstrating the achieved efficiency of the algorithm are presented. Furthermore, numerical experiments demonstrate that the preconditioner developed is independent of the number of fuel subdomains in a fuel rod, which is particularly important when simulating different types of fuel rods. Finally, we demonstrate the power of the coupling methodology by considering problems with couplings between surface and volume physics and coupling of nonlinear thermal transport in fuel rods to an external radiation transport code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Shift: A Massively Parallel Monte Carlo Radiation Transport Package

This paper discusses the massively-parallel Monte Carlo radiation transport package, Shift, developed at Oak Ridge National Laboratory. It reviews the capabilities, implementation, and parallel performance of this code package. Scaling results demonstrate very good strong and weak scaling behavior of the implemented algorithms. Benchmark results from various reactor problems show that Shift results compare well to other contemporary Monte Carlo codes and experimental results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Dynamic Resource Management for Parallel Tasks in an Oversubscribed Energy-Constrained Heterogeneous Environment

Abstract: The worth of completing parallel tasks is modeled using utility functions, which monotonically-decrease with time and represent the importance and urgency of a task. These functions define the utility earned by a task at the time of its completion. The performance of such a system is measured as the total utility earned by all completed tasks over some interval of time (e.g., 24 hours). To maximize system performance when scheduling dynamically arriving parallel tasks onto a high performance computing (HPC) system that is oversubscribed and energy-constrained, we have designed, analyzed, and compared different heuristic techniques. Four utility-aware heuristics (i.e., Max Utility, Max Utility-per-Time, Max Utility-per-Resource, and Max Utility-per-Energy), three FCFS-based heuristics (Conservative Backfilling, EASY Backfilling, and FCFS with Multiple Queues), and a Random heuristic were examined in this study. A technique that is often used with the FCFS-based heuristics is the concept of a permanent reservation. We compare the performance of permanent reservations with temporary place-holders to demonstrate the advantages that place-holders can provide. We also present a novel energy filtering technique that constrains the maximum energy-per-resource used by each task. We conducted a simulation study to evaluate the performance of these heuristics and techniques in an energy-constrained oversubscribed HPC environment. With place-holders, energy filtering, and dropping tasks with low potential utility, our utility-aware heuristics are able to significantly outperform the existing FCFS-based techniques.

Energy-Constrained↗
DOE OSTI2017

Parallel Asynchronous Distributed-Memory Maximal Independent Set Algorithm with Work Ordering

The maximal independent set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of graph data suggests the use of distributed memory hardware as a cost-effective approach to providing necessary compute and memory resources. Existing distributed memory parallel MIS algorithms rely on synchronous communication and use techniques such as subgraph computations. In this paper, we present an asynchronous distributed-memory parallel graph algorithm that relies on a virtual directed acyclic graph (DAG) that is created during the algorithm execution. We introduce two additional algorithms that save computations by ordering generated work. The first algorithm applies ordering globally to reduce computations, and the second algorithm applies ordering locally at the level of threads to minimize the synchronization overhead. We use two different implementations of Luby’s algorithm variants as baseline to compare the performance of the presented algorithms: (1) vertex-centric Luby A and Luby B implementations, and (2) the CombBLAS linear-algebra Luby A implementation. Results show that proposed algorithms outperform both implementations of Luby algorithms, especially in distributed execution. Furthermore, we show that for low-diameter graphs the algorithm that applies global ordering scales better than other algorithms and for high diameter graphs the original asynchronous algorithm and thread-level ordering algorithm show better performance.

maximal independent set (MIS), distributed memory ↗
DOE OSTI2023

An Open-Source Parallel EMT Simulation Framework: Preprint

As the integration level of inverter-based resources (IBR) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗
DOE OSTI2017

Parallel electron heating in the magnetospheric inflow region: Electron Heating in Reconnection

We analyzed 20 reconnection events observed by the Magnetosphere MultiScale mission, finding that in a subregion of the magnetospheric inflow, the electron temperature parallel to the magnetic field (T e|| ) decreases toward the separatrix with increasing densities. Such Te|| variation is not consistent with the heating through the parallel potential mechanism for magnetospheric electrons. Associated with the change in T e|| , low-energy gyrotropic magnetosheath-like electrons are observed. These electrons may come from the magnetosheath, penetrate to the magnetospheric side possibly due to waves in the lower hybrid frequency range, and do not experience as much energization as those from deeper in the magnetosphere. In addition, as T e|| decreases, the high-energy field-aligned phase-space densities decrease or fluctuate significantly over time. Wave-particle interaction might produce energy conversion and cause the high-energy phase-space density variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Breaking Parallel Orientation of Rods via a Dendritic Architecture toward Diverse Supramolecular Structures

Abstract Self‐assembled nanostructures of rod‐like molecules are commonly limited to nematic or layered smectic structures dominated by the parallel arrangement of the rod‐like components. Distinct self‐assembly behavior of four categories of dendritic rods constructed by placing a tri(hydroxy) group at the apex of dendritic oligo‐fluorenes is observed. Designed hydrogen bonding and dendritic architecture break the parallel arrangement of the rods, resulting in molecules with specific (fan‐like or cone‐like) shapes. While the fan‐shaped molecules tend to form hexagonal packing cylindrical phases, the cone‐shaped molecules could form spherical motifs to pack into various ordered structures, including the Frank–Kasper A15 phase and dodecagonal quasicrystal. This study provides a model system to engineer diverse supramolecular structures by rod‐like molecules and sheds new light into the mechanisms of the formation of unconventional spherical packing structures in soft matter.

Zhang, Ruimeng↗
DOE OSTI2019

Breaking Parallel Orientation of Rods via a Dendritic Architecture toward Diverse Supramolecular Structures

Abstract Self‐assembled nanostructures of rod‐like molecules are commonly limited to nematic or layered smectic structures dominated by the parallel arrangement of the rod‐like components. Distinct self‐assembly behavior of four categories of dendritic rods constructed by placing a tri(hydroxy) group at the apex of dendritic oligo‐fluorenes is observed. Designed hydrogen bonding and dendritic architecture break the parallel arrangement of the rods, resulting in molecules with specific (fan‐like or cone‐like) shapes. While the fan‐shaped molecules tend to form hexagonal packing cylindrical phases, the cone‐shaped molecules could form spherical motifs to pack into various ordered structures, including the Frank–Kasper A15 phase and dodecagonal quasicrystal. This study provides a model system to engineer diverse supramolecular structures by rod‐like molecules and sheds new light into the mechanisms of the formation of unconventional spherical packing structures in soft matter.

Zhang, Ruimeng↗
DOE OSTI2015

A switch from parallel to antiparallel strand orientation in a coiled-coil X-ray structure via two core hydrophobic mutations

The coiled-coil is one of the most ubiquitous and well studied protein structural motifs. Significant effort has been devoted to dissecting subtle variations of the typical heptad repeat sequence pattern that can designate larger topological features such as relative α-helical orientation and oligomer size. Here in this paper we report the X-ray structure of a model coiled-coil peptide, HA2-Del-L2seM, which forms an unanticipated core antiparallel dimer with potential sites for discrete higher-order multimerization (trimer or tetramer). In the X-ray structure, a third, partially-ordered α-helix is weakly associated with the antiparallel dimer and analytical ultracentrifugation experiments indicate the peptide forms a well-defined tetramer in solution. The HA2-Del-L2seM sequence is closely related to a parent model peptide, HA2-Del, which we previously reported adopts a parallel trimer; HA2-Del-L2seM differs by only hydrophobic leucine to selenomethione mutations and thus this subtle difference is sufficient to switch both relative α-helical topology and number of α-helices participating in the coiled-coil. Comparison of the X-ray structures of HA2-Del-L2seM (reported here) with the HA2-Del parent (reported previously) reveals novel interactions involving the selenomethionine residues that promote antiparallel coiled-coil configuration and preclude parallel trimer formation. Finally, these novel atomic insights are instructive for understanding subtle features that can affect coiled-coil topology and provide additional information for design of antiparallel coiled-coils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Genetic algorithm based task reordering to improve the performance of batch scheduled massively parallel scientific applications

The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on the performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.

97 MATHEMATICS AND COMPUTING↗