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At least 541 records · Page 30

Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing

Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more---operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity in the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.

Bethel, E. Wes↗

Programming Abstractions for Managing Workflows on Tiered Storage Systems

Scientific workflows in High Performance Computing (HPC) environments are processing large amounts of data. The storage hierarchy on HPC systems is getting deeper, driven by new technologies (NVRAMs, SSDs, etc.) There is a need for new programming abstractions that allow users to seamlessly manage data at the workflow level on multi-tiered storage systems, and provide optimal workflow performance and use of storage resources. In previous work, we introduced a software architecture Managing Data on Tiered Storage for Scientific Workflows (MaDaTS) that used a Virtual Data Space (VDS) abstraction to hide the complexities of the underlying storage system while allowing users to control data management strategies. In this article, we detail the data-centric programming abstractions that allow users to manage a workflow around its data on the storage layer. The programming abstractions simplify data management for scientific workflows on multi-tiered storage systems, without affecting workflow performance or storage capacity. We measure the overheads and effectiveness introduced by the programming abstractions of MaDaTS. Our results show that these abstractions can optimally use the storage capacity in lesser capacity storage tiers, and simplify data management without adding any performance overheads.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Automated metadata--final project report

This report summarizes the work of the Automated Metadata, Provenance Cataloging, and Navigable Interfaces: Ensuring the Usefulness of Extreme-Scale Data Project (MPO Project) funded by the United States Department of Energy (DOE), Offices of Advanced Scientific Computing Research and Fusion Energy Sciences. Initially funded for three years starting in 2012, it was extended for 6 months with additional funding. The project was a collaboration between scientists at General Atomics, Lawrence Berkley National Laboratory (LBNL), and Massachusetts Institute of Technology (MIT). The group leveraged existing computer science technology where possible, and extended or created new capabilities where required. The MPO project was able to successfully create a suite of software tools that can be used by a scientific community to automatically document their scientific workflows. These tools were integrated into workflows for fusion energy and climate research illustrating the general applicability of the project’s toolkit. Feedback was very positive on the project’s toolkit and the value of such automatic workflow documentation to the scientific endeavor.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Software Reuse Methods to Improve Technological Infrastructure for e-Science

Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.

Marshall, James J.↗

Validation of NSSC-I software for the Hubble Space Telescope

This paper describes the simulation and test methods used to ensure that the NASA Standard Spacecraft Computer, Model 1, (NSSC-I) flight software for the Hubble Space Telescope properly carries out its requirements for control of scientific observations and for monitoring the health and safety of the payload. The hardware and software test environment is discussed. The different kinds of tests (unit, special real time, and stress tests) that are performed before the software is incorporated into the flight system are described, and the kinds of errors that each test category is best suited to find are listed. Finally, the limitations of the tests are discussed, and current plans for enhancing the test environment are outlined.

Foley, Glenn↗

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗

Why scientists should learn to program in Python

Scientists have been central to the historical development of the computer industry, but the importance of software only continues to grow for all areas of scientific research and in particular for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. The article introduces the three types of programming languages and why scripting languages are now preferred for scientists. Of them, the authors assert Python is the most useful and easiest to learn. Python is introduced. Also presented is an overview to a few of the many add-on packages available to extend the capabilities of Python, for example, for numerical computations, scientific graphics and graphical user interface programming.

97 MATHEMATICS AND COMPUTING↗

Picking an Open Source License at LLNL: Guidance and Recommendations from the Computing Directorate

Science and innovation are at the core of LLNL’s mission, and open source software is a vehicle by which LLNL innovations reach the scientific community, the nation, and the world. It also serves as a vehicle for building collaborations, publicizing our capabilities, and attracting new employees. Over half of the software produced by LLNL is open source, and open source licenses are the legal tools that allow our software to be used widely. Choosing an appropriate license can be difficult, but it can be even more difficult to change licenses after your software has amassed a significant number of contributors, so it is important understand the potentially subtle implications of your license choice. This document provides a set of recommendations for the busy and uninitiated. They are not set in stone (there are always exceptions). Our goal is to provide default choices that align best with LLNL’s mission, along with a high-level rationale.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Astro2020 APC White Paper: Elevating the Role of Software as a Product of the Research Enterprise

Software is a critical part of modern research, and yet there are insufficient mechanisms in the scholarly ecosystem to acknowledge, cite, and measure the impact of research software. The majority of academic fields rely on a one-dimensional credit model whereby academic articles (and their associated citations) are the dominant factor in the success of a researcher's career. In the petabyte era of astronomical science, citing software and measuring its impact enables academia to retain and reward researchers that make significant software contributions. These highly skilled researchers must be retained to maximize the scientific return from petabyte-scale datasets. Evolving beyond the one-dimensional credit model requires overcoming several key challenges, including the current scholarly ecosystem and scientific culture issues. This white paper will present these challenges and suggest practical solutions for elevating the role of software as a product of the research enterprise.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Software Correlator of the Chinese VLBI Network

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability.

Zheng, Weimin↗

Tropospheric Emission Spectrometer Product File Readers

TES Product File Reader software extracts data from publicly available Tropospheric Emission Spectrometer (TES) HDF (Hierarchical Data Format) product data files using publicly available format specifications for scientific analysis in IDL (interactive data language). In this innovation, the software returns data fields as simple arrays for a given file. A file name is provided, and the contents are returned as simple IDL variables.

Fisher, Brendan M.↗

A continuous integration and web framework in support of the ATLAS publication process

The ATLAS collaboration defines methods, establishes procedures, and organises advisory groups to manage the publication processes of scientific papers, conference papers, and public notes. All stages are managed through web systems, computing programs, and tools that are designed and developed by the collaboration. A framework called FENCE is integrated into the CERN GitLab software repository, to automatically configure workspaces where each analysis can be documented by the analysis team and managed by the relevant coordinators. Continuous integration is used to guide the writers in applying consistent and correct formatting when preparing papers to be submitted to scientific journals. Additional software assures the correctness of other aspects of each paper, such as the lists of collaboration authors, funding agencies, and foundations. The framework and the workflow therein provide automatic and easy support to the researchers and facilitates each phase of the publication process, allowing authors to focus on the article contents. The framework and its integration with the most up to date and efficient tools has consequently provided a more professional and efficient automatized work environment to the whole collaboration.

47 OTHER INSTRUMENTATION↗

Focused Ion Beam Tomography of Alloy 617 Corroded in Molten Chloride Salt

Materials qualification of reactor structural materials is a critical step in rapid implementation of advanced nuclear reactor technologies, particularly to assess the corrosion performance in these designs. Accelerated qualification of reactor structural materials requires incorporating powerful computational toolsets, such as phase field modelling in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to predict the evolution of structural materials due to corrosion. Accordingly, computational toolsets will require experimental data generated at appropriate length scales to validate accuracy. Focused ion beam (FIB) provides a high degree of control over manipulation of materials for analytical purposes, including capturing data on the evolution in the microstructure and elemental composition of materials at the mesoscale, an appropriate length scale for phase field modelling of intergranular diffusion phenomena using the MOOSE framework. For instance, the FEI Helios G4 UX dual beam plasma FIB microscope at the Irradiated Materials Characterization Laboratory (IMCL) is capable of backscatter diffraction (EBSD) and energy-dispersive x-ray spectroscopy (EDS) documenting the evolution in the microstructure and elemental composition, respectively. The Helios can perform EDS and EBSD three-dimensionally (3D) using tomography, which is then combined using different software packages to visualize 3D volumes correlating elemental composition to microstructural data. The purpose of this investigation was to develop a streamlined characterization and data processing workflow for 3D tomography studies on the FEI Helios G4 plasma FIB. The investigation is segmented into three parts: 1) Optimizing the data collection workflow, 2) identifying appropriate data processing and visualization software (i.e. DREAM.3D, MIPAR, and VGStudioMax), and 3) establishing an infrastructure for public release. The optimization of the data collection workflow is in collaboration with members of the U220 department to setup formal training on the tomography operation of the G4, through ThermoFisher Scientific, and exploring DREAM.3D, MIPAR, and VGStudioMax data processing/visualization software packages. VGStudioMax currently demonstrates the most promise for future use. Optimization of the data collection and processing workflow is still ongoing. A collaboration with INL High Performance Computing (HPC) established an open-source license for expediting the public release of FIB tomography datasets through HPC. FIB tomography data generated by the G4 will provide comprehensive data for validating 3D phase field mesoscale modelling tools within the MOOSE framework for accelerated qualification of reactor structural materials.

Copeland-Johnson, Trishelle↗

Hardening of DOE UQ Codes for Ultra-Deep Proactive Geosteering in Oilfield Service

The primary objective of this project was to harden the DOE uncertainty quantification (UQ) code to solve the inverse problem for the geosteering service in the oilfield drilling and exploration. The primary focus is to verify the feasibility of using QUESO to solve geosteering inverse problems through statistical inversion. QUESO is a software library developed by QUEST, a DOE's Scientific Discovery through Advanced Computing (SciDAC) institute. In the process of drilling a borehole, geosteering is the act of adjusting the well trajectory on the fly to reach the geological targets or to keep the wellbore within desired formation. Geosteering inversion is to infer underground formation structure using measurements such as azimuthal resistivity logging data. The geosteering process relies on the real-time reconstruction of the subsurface earth model, and a robust and efficient inversion algorithm is always necessary to satisfy the job requirement. The new generation of azimuthal resistivity geosteering tool is capable of detecting multiple formation boundaries 20-100 ft away, and the corresponding geosteering inversion problem can be very challenging as many parameters need to be inverted within such a large depth of investigation. The success of the project will support US energy security by helping to advance subsurface modeling and characterization technologies in oilfield applications. An effective subsurface inversion algorithm and the implementation as a software package will promote the usage of ultra-deep azimuthal resistivity measurements, which can help well placement in complicated underground environments, reduce costs and risks of drilling, and increase oil and gas production. It will help medium and small size independent service companies and tool manufactures to enter the more advanced and lucrative directional drilling area. In addition, by hardening the QUESO code and building a transparent interface for easy manipulation of the QUESO functions, we provide a user-friendly tool for a larger scientific and industry communities that rely heavily on modeling and simulation tools for forecasting, parameter studies, design, and decision making. These are all activities that can strongly benefit from meaningful representations of modeling uncertainty supported by our product.

58 GEOSCIENCES↗

Simulating Mars: Enabling Testing of the Perseverance Rover Sampling and Caching Subsystem on Earth

The development of the Sampling and Caching Subsystem (SCS) on the JPL Perseverance Rover lies at the intersection of testing, robotics, and geology. The SCS team established three primary system test campaigns and venues to aid in the development of SCS through verification and validation testing – Qualification Model Dirty Testing (QMDT) to provide a venue for testing in a Martian environment, Vehicle System Testbed (VSTB) for testing while integrated with the mobility subsystem on Martian-like terrain, and the Flight Software Testbed (FSWTB) for conducting tests using the flight motor controllers and software system on a hexapod which had the ability to simulate rover tilt. Each venue contributed a vital piece to the SCS building blocks. However, the QMDT venue operating within a 10-ft diameter Thermal Vacuum chamber to simulate Martian environment provided a sui generis opportunity to fine tune the entire sampling and caching process while building the team’s knowledge base about rock drillability, system life, and target selection. On Earth, because Martian rocks are not readily available, the development team must utilize geoanalogs to the rocks and regolith on Mars. Geologists on the team helped establish a set of standard rock types to use for Mars missions, like Basalt, Sandstone, Mudstone, Gypsum, and other related geoanalogs. These geoanalogs are characterized with a standard suite of tests for density, compressibility, and other characteristics to categorize potential drillability. This concept of drillability is what links the geoanalogs on Earth to the samples we collect on Mars. With the simulant characteristics defined, these geoanalog rocks are ready to be drilled into as we do on the Martian surface. A key aspect of interacting with the surface on Mars is rock target identification and selection. The Perseverance robotic system uses the on-board cameras, instrumentation, and software to collect enough information to identify potential scientific targets. With the targets identified, SCS can place the Corer and abrade the surface or collect a sample. For a ground test activity like QMDT, the test team did not have all of the camera and instrumentation systems that the rover does, so the team developed ground test equivalents to process a rock, build a target map, and define the target. The team constructed a Rock Scanning Station to build a 3D point cloud of the rock. This point cloud was then processed and evaluated with predefined and programmed criteria in a Target Downselect Tool. A primary output of the Target Downselect Tool is a defined target that can be uploaded directly to the robotic software system to simulate and build the robotic sequences used in tests. With these insights and programmatic definition of targets, the QMDT test team was able to make the same decisions that the Perseverance surface operations team does. In addition, valuable lessons learned from developing the target selection ground tools and using them were implemented into the tools used for surface operations.

Kim, Junggon↗

Assessing the Implementation of an SDM at Sandia and LLNL

This report assesses the proposed implementation of a Scientific Data Management system that could be co-developed by LLNL and SNL and installed at each lab. In the current view, the systems would not be connected to each other. This report examines the different collaboration possibilities and status of planning and implementation of the teams at LLNL and SNL. The report uses identified requirements from previous work that has been done and documented in [1]. In that work, a set of simulation data management requirements was developed during a series of meetings, starting from requirements developed by Sandia Laboratory. These requirements are expected to evolve, and it is recommended that these requirements be revisited and updated for the following reasons: 1- Advancement in the computing hardware and software which leads to more processing power and better data movement speeds. 2- Advancement in computer algorithms which creates opportunities for better data management and analysis. 3- The need to expand and add to the capabilities of the SDM tools due to advancement in the applications software and due to new requirements by the scientific community. This report builds upon the experience from the work that has been done by some of the team members and the current SDM development efforts at LLNL and Sandia.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

XPRESS: eXascale PRogramming Environment and System Software

The XPRESS Project is one of four major projects of the DOE Office of Science Advanced Scientific Computing Research X-stack Program initiated in September, 2012. The purpose of XPRESS is to devise an innovative system software stack to enable practical and useful exascale computing around the end of the decade with near-term contributions to efficient and scalable operation of trans-Petaflops performance systems in the next two to three years; both for DOE mission-critical applications. To this end, XPRESS directly addresses critical challenges in computing of efficiency, scalability, and programmability through introspective methods of dynamic adaptive resource management and task scheduling.

97 MATHEMATICS AND COMPUTING↗

The moving target of visualization software for an increasingly complex world

Visualization has evolved into a mature scientific field and it has also become widely accepted as a standard approach in diverse fields, including physics, life sciences, and business intelligence. However, despite its successful development, there are still many open research questions that require customized implementations in order to explore and establish concepts, and to perform experiments and take measurements. Many methods and tools have been developed and published but most are stand-alone prototypes and have not reached a mature state that can be used in a reliable manner by collaborating domain scientists or a wider audience. In this study, we discuss the challenges, solutions, and open research questions that affect the development of sophisticated, relevant, and novel scientific visualization solutions with minimum overheads. Furthermore, we summarize and discuss the results of a recent National Institute of Informatics Shonan seminar on these topics.

97 MATHEMATICS AND COMPUTING↗