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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Extrapolating W -associated jet-production ratios at the LHC

Electroweak vector-boson production, accompanied by multiple jets, is an important background to searches for physics beyond the standard model. A precise and quantitative understanding of this process is helpful in constraining deviations from known physics. We study four key ratios in W + n -jet production at the LHC. We compute the ratio of cross sections for W + n - to W + (n-1)-jet production as a function of the minimum jet transverse momentum. We also study the ratio differentially, as a function of the W-boson transverse momentum; as a function of the scalar sum of the jet transverse energy, H$jets\atop{T}$; and as a function of certain jet transverse momenta. We show how to use such ratios to extrapolate differential cross sections to W + 6 -jet production at next-to-leading order, and we cross-check the method against a direct calculation at leading order. We predict the differential distribution in H$jets\atop{T}$ for W + 6 jets at next-to-leading order using such an extrapolation. We use the BlackHat software library together with SHERPA to perform the computations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Collaborative Computational Project for Electron cryo-Microscopy

The Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) is a new initiative for the structural biology community, following the success of CCP4 for macromolecular crystallography. Progress in supporting the users and developers of cryoEM software is reported. The Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has recently been established. The aims of the project are threefold: to build a coherent cryoEM community which will provide support for individual scientists and will act as a focal point for liaising with other communities, to support practising scientists in their use of cryoEM software and finally to support software developers in producing and disseminating robust and user-friendly programs. The project is closely modelled on CCP4 for macromolecular crystallography, and areas of common interest such as model fitting, underlying software libraries and tools for building program packages are being exploited. Nevertheless, cryoEM includes a number of techniques covering a large range of resolutions and a distinct project is required. In this article, progress so far is reported and future plans are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Exploring Hardware Support For Scaling Irregular Applications on Multi-node Multi-core Architectures

With the recent emergence of large-scale knowledge dis- covery, data mining and social network analysis, irregular applications have gained renewed interest. Classic cache-based high-performance architectures do not provide optimal performances with such kind of workloads, mainly due to the very low spatial and temporal locality of the irregular control and memory access patterns. In this paper, we present a multi-node, multi-core, fine-grained multi-threaded shared-memory system architecture specifically designed for the execution of large-scale irregular applications, and built on top of three pillars, that we believe are fundamental to support these workloads. First, we offer transparent hardware support for Partitioned Global Address Space (PGAS) to provide a large globally-shared address space with no software library overhead. Second, we employ multi-threaded multi-core processing nodes to achieve the necessary latency tolerance required by accessing global memory, which potentially resides in a remote node. Finally, we devise hardware support for inter-thread synchronization on the whole global address space. We first model the performances by using an analytical model that takes into account the main architecture and application characteristics. We describe the hardware design of the proposed cus- tom architectural building blocks that provide support for the above- mentioned three pillars. Finally, we present a limited-scale evaluation of the system on a multi-board FPGA prototype with typical irregular kernels and benchmarks. The experimental evaluation demonstrates the architecture performance scalability for different configurations of the whole system.

FPGA↗
DOE OSTI2017

Scalable Static and Dynamic Community Detection Using Grappolo

Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detection are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.

Community Detection↗
DOE OSTI2025

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

When a vulnerability is reported by the National Vulnerability Database (NVD), affected products are listed in the structured Common Platform Enumeration (CPE) format. Unfortunately, if the vulnerability is in a software library (e.g., Log4j), it will not include CPEs for each product containing that library. In these cases, security operators need to manually read the vendor's or third-party security advisories to see if their product is affected. However, these advisories do not report affected products in a structured format, which prevents automated processing, This paper makes the first effort towards automatically constructing structured CPEs for the vulnerable products in a non-NVD security advisory from the unstructured data in the advisory. Since this is a very challenging problem, this paper specifically focuses on the initial but key step of matching the un-structured vendor names in security advisories to the structured vendor representations in the standard CPE format. We explore the feasibility of using string similarity to solve the problem. The basic idea is to compare a vendor name from the non-NVD advisory with each vendor in the official CPE dictionary. The CPE vendor with the highest similarity score to the advisory's vendor will be considered as the match. We first conduct an experimental, comparative study of multiple mainstream string similarity metrics for this matching problem. To improve the performance, we then design a new string similarity metric that is adapted from an existing metric by weighing different tokens in the advisory's vendor name differently.

McClanahan, Kylie↗
DOE OSTI2023

ExTreeM: Scalable Augmented Merge Tree Computation via Extremum Graphs

Over the last decade merge trees have been proven to support a plethora of visualization and analysis tasks since they effectively abstract complex datasets. Here, this paper describes the ExTreeM-Algorithm: A scalable algorithm for the computation of merge trees via extremum graphs. The core idea of ExTreeM is to first derive the extremum graph G of an input scalar field f defined on a cell complex K, and subsequently compute the unaugmented merge tree of f on G instead of K; which are equivalent. Any merge tree algorithm can be carried out significantly faster on G, since K in general contains substantially more cells than G. To further speed up computation, ExTreeM includes a tailored procedure to derive merge trees of extremum graphs. The computation of the fully augmented merge tree, i.e., a merge tree domain segmentation of K, can then be performed in an optional post-processing step. All steps of ExTreeM consist of procedures with high parallel efficiency, and we provide a formal proof of its correctness. Our experiments, performed on publicly available datasets, report a speedup of up to one order of magnitude over the state-of-the-art algorithms included in the TTK and VTK-m software libraries, while also requiring significantly less memory and exhibiting excellent scaling behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗
DOE OSTI2023

A New Semistructured Algebraic Multigrid Method

Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display good parallelization properties. Since current architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semistructured interface that describes matrices primarily in terms of stencils and logically structured grids. This paper presents a new semistructured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semistructured problems. In conclusion, SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Physics Integration KErnels (PIKE)

Pike is a software library for coupling and solving multiphysics applications. It provides basic interfaces and utilities for performing code-to-code coupling. It provides simple "black-box" Picard iteration methods for solving the coupled system of equations including Jacobi and Gauss-Seidel solvers. Pike was developed originally to couple neutronics and thermal fluids codes to simulate a light water nuclear reactor for the Consortium for Simulation of Light-water Reactors (CASL) DOE Energy Innovation Hub. The Pike library contains no physics and just provides interfaces and utilities for coupling codes. It will be released open source under a BSD license as part of the Trilinos solver framework (trilinos.org) which is also BSD. This code provides capabilities similar to other open source multiphysics coupling libraries such as LIME, AMP, and MOOSE.

Pawlowski, Roger↗
DOE OSTI2016

Stride Search v. 1.0

Stride Search provides a flexible tool for detecting storms or other extreme climate events in high-resolution climate data sets saved on uniform latitude-longitude grids in standard NetCDF format. Users provide the software a quantitative description of a meteorological event they are interested in; the software searches a data set for locations in space and time that meet the user’s description. In its first stage, Stride Search performs a spatial search of the data set at each timestep by dividing a search domain into circular sectors of constant geodesic radius. Data from a netCDF file is read into memory for each circular search sector. If the data meet or exceed a set of storm identification criteria (defined by the user), a storm is recorded to a linked list. Finally, the linked list is examined and duplicate detections of the same storm are removed and the results are written to an output file. The first stage’s output file is read by a second program that builds storm. Additional identification criteria may be applied at this stage to further classify storms. Storm tracks are the software’s ultimate output and routines are provided for formatting that output for various external software libraries for plotting and tabulating data.

Bosler, Peter↗
DOE OSTI2015

Albany v. 3.0

The Albany code is a general-purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in Trilinos as well as those in the Dakota toolkit. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. Albany is both a framework and the host for specific finite element applications. These applications have project names, and can be controlled by configuration option when the code is compiled, but are all developed and released as part of the single Albany code base, These include LCM, QCAD, FELIX, Aeras, and ATO applications.

SciDAC↗
DOE OSTI2016

Progress Version 1.0

Software library for parallel rapid order N and graph-based recursive electronic structure solvers with applications to material science, chemistry, and molecular biology.

Niklasson, AndersM.↗
DOE OSTI2017

Portage, Version 2.0

Portage is a software library system for physics remapping (mapping physics variables from one computational mesh to another) either within a single simulation code or between two disparate simulation codes. Portage is designed to utilize advanced-architecture compute platforms and to be easily extensible by third parties.

Herring, Angela↗
DOE OSTI2017

EOSlib, Version 3

Equilibrium thermodynamics underpins many of the technologies used throughout theoretical physics, yet verification of the various theoretical models in the open literature remains challenging. EOSlib provides a single, consistent, verifiable implementation of these models, in a single, easy-to-use software package. It consists of three parts: a software library implementing various published equation-of-state (EOS) models; a database of fitting parameters for various materials for these models; and a number of useful utility functions for simplifying thermodynamic calculations such as computing Hugoniot curves or Riemann problem solutions. Ready availability of this library will enable reliable code-to- code testing of equation-of-state implementations, as well as a starting point for more rigorous verification work. EOSlib also provides a single, consistent API for its analytic and tabular EOS models, which simplifies the process of comparing models for a particular application.

Woods, Nathan↗
DOE OSTI2015

Acro (A Common Repository for Optimizers) v. 2.0

Acro provides a software infrastructure that integrates a variety of optimization software libraries, as well as general-purpose libraries like UTILIB that support the development of parallel optimizers.

Hart, William↗
DOE OSTI2020

UQ Toolkit v 2.0

The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Loève expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).

Safta, Cosmin↗
DOE OSTI2014

ForQint

ForQint is a Fortran software library to adaptively integrate multivariable functions versus well known probability distributions (e.g. normal, lognormal, etc.) using quadrature rules. Such integration is known to be more efficient and accurate especially when the function evaluation is expensive. The library also FQint enables the creation of both full and sparse anisotropic multi-dimensional quadrature rules. These latter encompass different such as Gauss-Hermite, Gauss-Legendre, etc. The functions Maher Salloum, Bert Debusschere, Kenny Chowdhary and subroutines rely on the C++ Stokhos package of Trilinos (trilinos.sandia.gov) where the appropriate classes were wrapped into Fortran.

Chowdhary, Kamalijit↗