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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Griffin Software Development Plan

Griffin is a MOOSE-based reactor physics application for advanced reactor multiphysics modeling and simulation. The application is developed in a consistent multiphysics environment with strong software quality assurance. Griffin inherited most of the capabilities of MAMMOTH/Rattlesnake and is adopting the capabilities from PROTEUS that are needed in the code. The toolset includes a variety of deterministic radiation transport solvers for fixed source, k-eigenvalue, ad-joint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code contains the cross-section preparation capabilities applicable to fast and thermal reactors, including TRISO-fueled reactors. Core management capabilities include core performance, fuel depletion and shuffling, equilibrium core calculation, pebble-bed reactor run-in and equilibrium core, molten-salt reactor delayed neutron precursor drift, and control rod and drum movement with cusping correction. This software development plan presents the current and future capabilities and features in Griffin for the design and analysis of non-light-water reactor systems in steady-state and transient conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

An Agile/XP software development process for modernizing the accelerator control system at Fermilab

Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.

Diamond, John [Fermilab]↗
DOE OSTI2014

ARCHER{sub RT} – A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy

Purpose: Using the graphical processing units (GPU) hardware technology, an extremely fast Monte Carlo (MC) code ARCHER{sub RT} is developed for radiation dose calculations in radiation therapy. This paper describes the detailed software development and testing for three clinical TomoTherapy® cases: the prostate, lung, and head and neck. Methods: To obtain clinically relevant dose distributions, phase space files (PSFs) created from optimized radiation therapy treatment plan fluence maps were used as the input to ARCHER{sub RT}. Patient-specific phantoms were constructed from patient CT images. Batch simulations were employed to facilitate the time-consuming task of loading large PSFs, and to improve the estimation of statistical uncertainty. Furthermore, two different Woodcock tracking algorithms were implemented and their relative performance was compared. The dose curves of an Elekta accelerator PSF incident on a homogeneous water phantom were benchmarked against DOSXYZnrc. For each of the treatment cases, dose volume histograms and isodose maps were produced from ARCHER{sub RT} and the general-purpose code, GEANT4. The gamma index analysis was performed to evaluate the similarity of voxel doses obtained from these two codes. The hardware accelerators used in this study are one NVIDIA K20 GPU, one NVIDIA K40 GPU, and six NVIDIA M2090 GPUs. In addition, to make a fairer comparison of the CPU and GPU performance, a multithreaded CPU code was developed using OpenMP and tested on an Intel E5-2620 CPU. Results: For the water phantom, the depth dose curve and dose profiles from ARCHER{sub RT} agree well with DOSXYZnrc. For clinical cases, results from ARCHER{sub RT} are compared with those from GEANT4 and good agreement is observed. Gamma index test is performed for voxels whose dose is greater than 10% of maximum dose. For 2%/2mm criteria, the passing rates for the prostate, lung case, and head and neck cases are 99.7%, 98.5%, and 97.2%, respectively. Due to specific architecture of GPU, modified Woodcock tracking algorithm performed inferior to the original one. ARCHER{sub RT} achieves a fast speed for PSF-based dose calculations. With a single M2090 card, the simulations cost about 60, 50, 80 s for three cases, respectively, with the 1% statistical error in the PTV. Using the latest K40 card, the simulations are 1.7–1.8 times faster. More impressively, six M2090 cards could finish the simulations in 8.9–13.4 s. For comparison, the same simulations on Intel E5-2620 (12 hyperthreading) cost about 500–800 s. Conclusions: ARCHER{sub RT} was developed successfully to perform fast and accurate MC dose calculation for radiotherapy using PSFs and patient CT phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗
DOE OSTI2022

The Science of Scientific Software Development and Use

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them is often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. The US Department of Energy Office of Science (DOE-SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. In December 2021, the DOE-SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: software has become an essential part of modern science that impacts new discovery, policy, and technological development. To have full confidence in science delivered via software, we must improve the processes and tools that help us create and use it, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work. The full workshop report will be available at https://doi.org/10.2172/1846009.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
DOE OSTI2022

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich data challenges existing data storage and access technologies, therefore precluding informatics advancements. Here we present MZA™ (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed by a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and efficient programmatic access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards a Software Development Framework for Interconnected Science Ecosystems

The innovative science of the future must be multi-domain and interconnected to usher in the next generation of “self-driving” laboratories enabling consequential discoveries and transformative inventions. Such a disparate and interconnected ecosystem of scientific instruments will need to evolve using a system-of-systems (SoS) approach. The key to enabling application integration with such an SoS will be the use of Software Development Kits (SDKs). Currently, SDKs facilitate scientific research breakthroughs via algorithmic automation, databases and storage, optimization and structure, pervasive environmental monitoring, among others. However, existing SDKs lack instrument-interoperability and reusability capabilities, do not effectively work in an open federated architectural environment, and are largely isolated within silos of the respective scientific disciplines. Inspired by the scalable SoS framework, this work proposes the development of INTERSECT-SDK to provide a coherent environment for multi-domain scientific applications to benefit from the open federated architecture in an interconnected ecosystem of instruments. This approach will decompose functionality into loosely coupled software services for interoperability among several solutions that do not scale beyond a single domain and/or application. Furthermore, the proposed environment will allow operational and managerial inter-dependence while providing opportunities for the researchers to reuse software components from other domains and build universal solution libraries. We demonstrate this research for microscopy use-case, where we show how INTERSECT-SDK is developing the tools necessary to enable advanced scanning methods and accelerate scientific discovery.

Malviya, Addi Thakur↗
DOE OSTI2023

MicroBooNE Public Data Sets: a Collaborative Tool for LArTPC Software Development

Among liquid argon time projection chamber (LArTPC) experiments MicroBooNE is the one that continually took physics data for the longest time (2015-2021), and represents the state of the art for reconstruction and analysis with this detector. Recently published analyses include oscillation physics results, searches for anomalies and other BSM signatures, and cross section measurements. LArTPC detectors are being used in current experiments such as ICARUS and SBND, and being planned for future experiments such as DUNE. MicroBooNE has recently released to the public two of its data sets, with the goal of enabling collaborative software developments with other LArTPC experiments and with AI or computing experts. These data sets simulate neutrino interactions on top of off-beam data, which include cosmic ray background and noise. The data sets are released in two formats: the native art/ROOT format used internally by the collaboration and familiar to other LArTPC experts, and the HDF5 format which contains reduced and simplified content and is suitable for usage by the broader community. This contribution presents the open data sets, discusses their motivation, the technical implementation, and the extensive documentation -- all inspired by FAIR principles. Finally, opportunities for collaborations are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

ExaWorks software development kit: a robust and scalable collection of interoperable workflows technologies

Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be mapped, scheduled, and launched on different computing. That requires a software stack that enables users to code their workflows and automate resource management and workflow execution. Currently, there are many workflow technologies with diverse levels of robustness and capabilities, and users face difficult choices of software that can effectively and efficiently support their use cases on HPC machines, especially when considering the latest exascale platforms. We contributed to addressing this issue by developing the ExaWorks Software Development Kit (SDK). The SDK is a curated collection of workflow technologies engineered following current best practices and specifically designed to work on HPC platforms. We present our experience with (1) curating those technologies, (2) integrating them to provide users with new capabilities, (3) developing a continuous integration platform to test the SDK on DOE HPC platforms, (4) designing a dashboard to publish the results of those tests, and (5) devising an innovative documentation platform to help users to use those technologies. Our experience details the requirements and the best practices needed to curate workflow technologies, and it also serves as a blueprint for the capabilities and services that DOE will have to offer to support a variety of scientific heterogeneous workflows on the newly available exascale HPC platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DevOps Pragmatic Practices and Potential Perils in Scientific Software Development

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

artdaq : DAQ software development made simple

For a few years now, the artdaq data acquisition software toolkit has provided numerous experiments with ready-to-use components which allow for rapid development and deployment of DAQ systems. Developed within the Fermilab Scientific Computing Division, artdaq provides data transfer, event building, run control, and event analysis functionality. This latter feature includes built-in support for the art event analysis framework, allowing experiments to run art modules for real-time filtering, compression, disk writing and online monitoring; as art, also developed at Fermilab, is also used for online analysis, a major advantage of artdaq is that it allows developers to easily switch between developing online and online software. artdaq continues to be improved. Support for an alternate mode of running whereby data from some subdetector components are only streamed if requested has been added; this option will reduce unnecessary DAQ throughput. Real-time reporting of DAQ metrics has been implemented, along with the flexibility to choose the format through which experiments receive the reports; these formats include the Ganglia, Graphite and syslog software packages, along with at ASCII files. Additionally, work has been performed investigating more flexible modes of online monitoring, including the capability of being able to run multiple online monitoring processes on different hosts, each running its own set of art modules. Finally, a web-based GUI interface through which users can configure details of their DAQ system has been implemented, increasing the ease of use of the system. Already successfully deployed on the LArIAT, DarkSide-50, DUNE 35ton and Mu2e experiments, artdaq will be employed for SBND and is a strong candidate for use on ICARUS and protoDUNE. With each experiment comes new ideas for how artdaq can be made more flexible and powerful; the above improvements will be described, along with potential ideas for the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Creating Continuous Integration Infrastructure for Software Development on U.S. Department of Energy High-Performance Computing Systems

The Exascale Computing Project (ECP) software deployment effort developed and advanced DevOps capabilities. One goal was to enable robust continuous integration (CI) workflows that span the protected high performance computing (HPC) environments found within many of the Department of Energy’s (DOE) national laboratories. This article highlights several challenges encountered with enabling automation, such as charging models for CI jobs, and meeting individualized security requirements that revolve around strongly associating running code with a human identity. Here, it also describes how the Jacamar CI tool evolved to meet latter requirements and became a key aspect of the solutions currently offered. Derived from this experience, we offer a conceptual framework for understanding current and future CI challenges at DOE facilities and offer suggestions for long-term solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Chemical Reactivity Through Adaptive Quantum Mechanics/Many-Body Representations: Theoretical Development, Software Implementation, and Applications (Final Report)

The main objective of this research project was the development and application of a new theoretical/computational framework to model chemical transformations and electronic excitations in fluid mixtures across different phases. Our theoretical/computational framework combines our data-driven many-body (DD-MB) potentials representing molecular interactions with adaptive schemes for modeling chemical reactions in solution. The combination of these two components resulted in an adaptive quantum mechanics/many-body (adQM/MB) method that largely suppresses discontinuities between QM and MM regions, which affect existing QM/MM methods, and thus provides an accurate representation of both quantum mechanical and environmental effects through a rigorous description of mutual polarization between QM and MM regions. The implementation of our DD-MB potentials and adQM/MB method in popular software enabled computer simulations of solvation phenomena, reactive processes, and electronic excitations in fluid mixtures with chemical and spectroscopic accuracy, representing a major step toward realistic computer simulations of a wide range of molecular systems relevant to the DOE mission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

HEP Software Development in the Next Decade; the Views of the HSF Community

We have known for a while now that projections of computing needs for the experiments running in 10 years from now are unaffordable. Over the past year the HSF has convened a series of workshops aiming to find consensus on the needs, and produce proposals for research and development to address this challenge. At this time many of the software related drafts are far enough along to give a clear picture of what will result from this process. This talk will synthesize and report on some of the key elements to come out of this community work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Peregrine Software Development: Report on the Code Conversion From Python to C++

This work package seeks to convert the Peregrine software tool from its original Python implementation to a production version based on the C++ language. Peregrine is a powerful research platform with a multitude of advanced data analytics and data visualization functionalities. Developed by scientists to explore multimodal and multidimensional data related to the production of components using powder bed additive manufacturing processes, the tool implements state-of-the-art algorithms to assist machine users in making build or part quality determinations. Given that Peregrine is data-intensive, the goal of this conversion is to enhance the tool’s flexibility and interactivity and reduce the number of code dependencies to facilitate its deployment as part of the ongoing technology transfer campaign. This brief document provides an overview of Peregrine’s functionalities and capabilities, along with a detailed description of the core functionalities that have been implemented to date in the new C++ version. This document serves as a development update at the end of the first year of the ongoing conversion and will be regularly updated as progress continues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Status of SAS4A/SASSYS-1 Software Development and Application (FY2024)

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years. It has been identified as a critical element of safety analysis capabilities for the U.S. Department of Energy and is utilized within industry to perform the transient safety analyses required to support the licensing of Liquid Metal-cooled Fast Reactors (LMFRs). This report summarizes the code development and update activities carried out during FY2024. In FY2024, programmatic activities focused on key improvements to software useability, such as enhanced user interfaces for reactivity feedback modeling, improvements in stability/useability of the Code Manual, and improvements to the acceptance testing infrastructure, including automation of acceptance testing and generation of the Acceptance Testing Report. To support end user applications, an open training was held, a semi-public forum was maintained, and a practical benchmarking and validation matrix was developed which allowed limitations of existing testing capabilities to be assessed. The existing fuel models were also enhanced with improved modeling capabilities and testing for the oxide and annular fuel models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗