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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

The PhEDEx next-gen website

PhEDEx is the data-transfer management solution written by CMS. It consists of agents running at each site, a website for presentation of information, and a web-based data-service for scripted access to information. The website allows users to monitor the progress of data-transfers, the status of site agents and links between sites, and the overall status and behaviour of everything about PhEDEx. It also allows users to make and approve requests for data-transfers and for deletion of data. It is the main point-of-entry for all users wishing to interact with PhEDEx. For several years, the website has consisted of a single perl program with about 10K SLOC. This program has limited capabilities for exploring the data, with only coarse filtering capabilities and no context-sensitive awareness. Graphical information is presented as static images, generated on the server, with no interactivity. It is also not well connected to the rest of the PhEDEx codebase, since much of it was written before the data-service was developed. All this makes it hard to maintain and extend. We are re-implementing the website to address these issues. The UI is being rewritten in Javascript, replacing most of the server-side code. We are using the YUI toolkit to provide advanced features and context-sensitive interaction, and will adopt a Javascript charting library for generating graphical representations client-side. This relieves the server of much of its load, and automatically improves server-side security. The Javascript components can be re-used in many ways, allowing custom pages to be developed for specific uses. In particular, standalone test-cases using small numbers of components make it easier to debug the Javascript than it is to debug a large server program. Information about PhEDEx is accessed through the PhEDEx data-service, since direct SQL is not available from the clients browser. This provides consistent semantics with other, externally written monitoring tools, which already use the data-service. It also reduces redundancy in the code, yielding a simpler, consolidated codebase. In this talk we describe our experience of re-factoring this monolithic server-side program into a lighter client-side framework. We describe some of the techniques that worked well for us, and some of the mistakes we made along the way. We present the current state of the project, and its future direction.

Egeland, R.↗
DOE OSTI2019

GUNDAM: a toolkit for fast spatial correlation functions in galaxy surveys

ABSTRACT We describe the capabilities of a new software package to calculate two-point correlation functions (2PCFs) of large galaxy samples. The code can efficiently estimate 3D/projected/angular 2PCFs with a variety of statistical estimators and bootstrap errors, and is intended to provide a complete framework (including calculation, storage, manipulation, and plotting) to perform this type of spatial analysis with large redshift surveys. Gundam implements a very fast skip list/linked list algorithm that efficiently counts galaxy pairs and avoids the computation of unnecessary distances. It is several orders of magnitude faster than a naive pair counter, and matches or even surpass other advanced algorithms. The implementation is also embarrassingly parallel, making full use of multicore processors or large computational clusters when available. The software is designed to be flexible, user friendly and easily extensible, integrating optimized, well-tested packages already available in the astronomy community. Out of the box, it already provides advanced features such as custom weighting schemes, fibre collision corrections and 2D correlations. Gundam will ultimately provide an efficient toolkit to analyse the large-scale structure ‘buried’ in upcoming extremely large data sets generated by future surveys.

Donoso, E.↗
DOE OSTI2016

Fault Tolerant Frequent Pattern Mining

FP-Growth algorithm is a Frequent Pattern Mining (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several researchers have designed distributed memory FP-Growth algorithms, it is pivotal to consider fault tolerant FP-Growth, which can address the increasing fault rates in large scale systems. In this work, we propose a novel parallel, algorithm-level fault-tolerant FP-Growth algorithm. We leverage algorithmic properties and MPI advanced features to guarantee an O(1) space complexity, achieved by using the dataset memory space itself for checkpointing. We also propose a recovery algorithm that can use in-memory and disk-based checkpointing, though in many cases the recovery can be completed without any disk access, and incurring no memory overhead for checkpointing. We evaluate our FT algorithm on a large scale InfiniBand cluster with several large datasets using up to 2K cores. Our evaluation demonstrates excellent efficiency for checkpointing and recovery in comparison to the disk-based approach. We have also observed 20x average speed-up in comparison to Spark, establishing that a well designed algorithm can easily outperform a solution based on a general fault-tolerant programming model.

Shohdy, Sameh↗
DOE OSTI2020

Inferring the Dynamics of the State Evolution During Quantum Annealing

To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we propose to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Furthermore, using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called "slicing", we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits.

42 ENGINEERING↗
DOE OSTI2015

Performance characterization of high quantum efficiency metal package photomultiplier tubes for time-of-flight and high-resolution PET applications

Purpose: Metal package photomultiplier tubes (PMTs) with a metal channel dynode structure have several advanced features for devising such time-of-flight (TOF) and high spatial resolution positron emission tomography (PET) detectors, thanks to their high packing density, large effective area ratio, fast time response, and position encoding capability. Here, we report on an investigation of new metal package PMTs with high quantum efficiency (QE) for high-resolution PET and TOF PET detector modules. Methods: The latest metal package PMT, the Hamamatsu R11265 series, is served with two kinds of photocathodes that have higher quantum efficiency than normal bialkali (typical QE ≈ 25%), super bialkali (SBA; QE ≈ 35%), and ultra bialkali (UBA; QE ≈ 43%). In this study, the authors evaluated the performance of the new PMTs with SBA and UBA photocathodes as a PET detector by coupling various crystal arrays. They also investigated the performance improvements of high QE, focusing in particular on a block detector coupled with a lutetium-based scintillator. A single 4 × 4 × 10 mm{sup 3} LYSO, a 7 × 7 array of 3 × 3 × 20 mm{sup 3} LGSO, a 9 × 9 array of 1.2 × 1.2 × 10 mm{sup 3} LYSO, and a 6 × 6 array of 1.5 × 1.5 × 7 mm{sup 3} LuYAP were used for evaluation. All coincidence data were acquired with a DRS4 based fast digitizer. Results: This new PMT shows promising crystal positioning accuracy, energy and time discrimination performance for TOF, and high-resolution PET applications. The authors also found that a metal channel PMT with SBA was enough for both TOF and high-resolution application, although UBA gave a minor improvement to time resolution. However, significant performance improvement was observed in relative low light output crystals (LuYAP) coupled with UBA. Conclusions: The results of this study will be of value as a useful reference to select PMTs for high-performance PET detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

pcircle - A Suite of Scalable Parallel File System Tools

Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

WANG, FEIYI↗
DOE OSTI2015

TOUGH+ v1.5 Core Code

TOUGH+ v1.5 is a numerical code for the simulation of multi-phase, multi-component flow and transport of mass and heat through porous and fractured media, and represents the third update of the code since its first release [Moridis et al., 2008]. TOUGH+ is a successor to the TOUGH2 [Pruess et al., 1991; 2012] family of codes for multi-component, multiphase fluid and heat flow developed at the Lawrence Berkeley National Laboratory. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstations, PC, Macintosh). TOUGH+ v1.5 employs dynamic memory allocation, thus minimizing storage requirements. It has a completely modular structure, follows the tenets of Object-Oriented Programming (OOP), and involves the advanced features of FORTRAN 95/2003, i.e., modules, derived data types, the use of pointers, lists and trees, data encapsulation, defined operators and assignments, operator extension and overloading, use of generic procedures, and maximum use of the powerful intrinsic vector and matrix processing operations. TOUGH+ v1.5 is the core code for its family of applications, i.e., the part of the code that is common to all its applications. It provides a description of the underlying physics and thermodynamics of non-isothermal flow, of the mathematical and numerical approaches, as well as a detailed explanation of the general (common to all applications) input requirements, options, capabilities and output specifications. The core code cannot run by itself: it needs to be coupled with the code for the specific TOUGH+ application option that describes a particular type of problem. The additional input requirements specific to a particular TOUGH+ application options and related illustrative examples can be found in the corresponding User's Manual.

Moridis, GeorgeJ↗
DOE OSTI2018

Parallel Fenics Implementation of Block Solvers (pFibs)

This software is a Python package designed to act as an interface between FEniCS and PETSc to facilitate the construction and application of parallel block solvers/preconditioners. The original intent of this software was to help enable Battery and Wind Farm simulations for use on high performance computing systems. The code is written in Python and uses the petsc4py module to access the more advance features of the PETSc Krylov Solver. In essence, pFibs is an interface to make accessing these features more streamlined. Additionally, pFibs also provides a template for building custom Python based preconditioning algorithms.

Allen, Jeffery↗
DOE OSTI2021

drtsans

drtsans is highly modular, allowing users to customize collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.

Bilheux, JeanC↗
DOE OSTI2025

Preparing MPICH for exascale

The advent of exascale supercomputers heralds a new era of scientific discovery, yet it introduces significant architectural challenges that must be overcome for MPI applications to fully exploit its potential. Among these challenges is the adoption of heterogeneous architectures, particularly the integration of GPUs to accelerate computation. Additionally, the complexity of multithreaded programming models has also become a critical factor in achieving performance at scale. The efficient utilization of hardware acceleration for communication, provided by modern NICs, is also essential for achieving low latency and high throughput communication in such complex systems. In response to these challenges, the MPICH library, a high-performance and widely used Message Passing Interface (MPI) implementation, has undergone significant enhancements. Here, this paper presents four major contributions that prepare MPICH for the exascale transition. First, we describe a lightweight communication stack that leverages the advanced features of modern NICs to maximize hardware acceleration. Second, our work showcases a highly scalable multithreaded communication model that addresses the complexities of concurrent environments. Third, we introduce GPU-aware communication capabilities that optimize data movement in GPU-integrated systems. Finally, we present a new datatype engine aimed at accelerating the use of MPI derived datatypes on GPUs. These improvements in the MPICH library not only address the immediate needs of exascale computing architectures but also set a foundation for exploiting future innovations in high-performance computing. By embracing these new designs and approaches, MPICH-derived libraries from HPE Cray and Intel were able to achieve real exascale performance on OLCF Frontier and ALCF Aurora respectively.

Guo, Yanfei [Argonne National Laboratory (ANL), Ar↗
DOE OSTI2012

High Performance Computing Productivity Study - Evaluation of Parallel Tools Platform (PTP) Eclipse Plug-In

This report is a DARPA funded Work For Others (WFO) evaluation of the Parallel Tools Platform (PTP) version 5.0.3 (Released October 18, 2011). PTP is currently being developed and supported as an open source product managed by Project Lead Greg Watson and team at IBM plus several other contributors. The tool has been in development since 2005 with a goal of providing an infrastructure for the integration of high performance computing tools. Basic functionality such as source code editing, compiling, launching, and debugging, plus more advanced features including performance monitoring and deployment have been bundled into an Eclipse Integrated Development Environment (IDE) plug-in to give parallel application programmers the features and improved productivity gained from using a common, well established development platform. The evaluation encompasses the basic aspects of using PTP, beginning with the installation and configuration of the plug-in, followed by code development and debugging. Each aspect is evaluated based on the expectations of my experience as an Eclipse user and is presented in the following format: • Feature description • User Experience • Evaluation The feature description is based on the provided documentation for PTP and the ‘generic’ expectations of what the feature should provide. The user experience reveals the actual use and exercise of the feature – specifically in the context and perspective of the evaluation platform provided by Lawrence Livermore National Laboratory. The evaluation of each feature includes the overall outcome of the user experience, along with the expectations that were not met, met, or exceeded along with any issues that were encountered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Application note :

The development of the XyceTM Parallel Electronic Simulator has focused entirely on the creation of a fast, scalable simulation tool, and has not included any schematic capture or data visualization tools. This application note will describe how to use the open source schematic capture tool gschem and its associated netlist creation tool gnetlist to create basic circuit designs for Xyce, and how to access advanced features of Xyce that are not directly supported by either gschem or gnetlist.

Russo, Thomas V.↗
DOE OSTI2014

User's Manual of the TOUGH+ Core Code v1.5: A General-Purpose Simulator of Non-Isothermal Flow and Transport through Porous and Fractured Media

TOUGH+ v1.5 is a numerical code for the simulation of multi-phase, multi-component flow and transport of mass and heat through porous and fractured media, and represents the third update of the code since its first release [Moridis et al., 2008]. TOUGH+ is a successor to the TOUGH2 [Pruess et al., 1991] family of codes for multi-component, multiphase fluid and heat flow developed at the Lawrence Berkeley National Laboratory. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstations, PC, Macintosh). TOUGH+ v1.5 employs dynamic memory allocation, thus minimizing storage requirements. It has a completely modular structure, follows the tenets of Object-Oriented Programming (OOP), and involves the advanced features of FORTRAN 95/2003, i.e., modules, derived data types, the use of pointers, lists and trees, data encapsulation, defined operators and assignments, operator extension and overloading, use of generic procedures, and maximum use of the powerful intrinsic vector and matrix processing operations. This report presents the core TOUGH+ v1.5 code, i.e., the part of the code that is common to all its applications. It provides a description of the underlying physics and thermodynamics of non-isothermal flow, of the mathematical and numerical approaches, as well as a detailed explanation of the general (common to all applications) input requirements, options, capabilities and output specifications. The core code cannot run by itself: it needs to be coupled with the code for the specific TOUGH+ application option that describes a particular type of problem. The additional input requirements specific to a particular TOUGH+ application options and related illustrative examples can be found in the corresponding User’s Manual.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

LDRD Report: Scheduling Irregular Algorithms

This LDRD project was a campus exec fellowship to fund (in part) Donald Nguyen’s PhD research at UT-Austin. His work has focused on parallel programming models, and scheduling irregular algorithms on shared-memory systems using the Galois framework. Galois provides a simple but powerful way for users and applications to automatically obtain good parallel performance using certain supported data containers. The naïve user can write serial code, while advanced users can optimize performance by advanced features, such as specifying the scheduling policy. Galois was used to parallelize two sparse matrix reordering schemes: RCM and Sloan. Such reordering is important in high-performance computing to obtain better data locality and thus reduce run times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

FY15 Report on Thermomechanical Testing

Sandia is participating in the third phase of a United States (US)-German Joint Project that compares constitutive models and simulation procedures on the basis of model calculations of the thermomechanical behavior and healing of rock salt (Salzer et al. 2015). The first goal of the project is to evaluate the ability of numerical modeling tools to correctly describe the relevant deformation phenomena in rock salt under various influences. Among the numerical modeling tools required to address this are constitutive models that are used in computer simulations for the description of the thermal, mechanical, and hydraulic behavior of the host rock under various influences and for the long-term prediction of this behavior. Achieving this goal will lead to increased confidence in the results of numerical simulations related to the secure disposal of radioactive wastes in rock salt. Results of the Joint Project may ultimately be used to make various assertions regarding stability analysis of an underground repository in salt during the operating phase as well as long-term integrity of the geological barrier in the post-operating phase A primary evaluation of constitutive model capabilities comes by way of predicting large-scale field tests. The Joint Project partners decided to model Waste Isolation Pilot Plant (WIPP) Rooms B & D which are full-scale rooms having the same dimensions. Room D deformed under natural, ambient conditions while Room B was thermally driven by an array of waste-simulating heaters (Munson et al. 1988; 1990). Existing laboratory test data for WIPP salt were carefully scrutinized and the partners decided that additional testing would be needed to help evaluate advanced features of the constitutive models. The German partners performed over 140 laboratory tests on WIPP salt at no charge to the US Department of Energy (DOE).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Percept User Manual.

This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included. This page intentionally left blank.

97 MATHEMATICS AND COMPUTING↗