973 research outputs found
WFIRST Coronagraph Technology Requirements: Status Update and Systems Engineering Approach
The coronagraphic instrument (CGI) on the Wide-Field Infrared Survey
Telescope (WFIRST) will demonstrate technologies and methods for high-contrast
direct imaging and spectroscopy of exoplanet systems in reflected light,
including polarimetry of circumstellar disks. The WFIRST management and CGI
engineering and science investigation teams have developed requirements for the
instrument, motivated by the objectives and technology development needs of
potential future flagship exoplanet characterization missions such as the NASA
Habitable Exoplanet Imaging Mission (HabEx) and the Large UV/Optical/IR
Surveyor (LUVOIR). The requirements have been refined to support
recommendations from the WFIRST Independent External Technical/Management/Cost
Review (WIETR) that the WFIRST CGI be classified as a technology demonstration
instrument instead of a science instrument. This paper provides a description
of how the CGI requirements flow from the top of the overall WFIRST mission
structure through the Level 2 requirements, where the focus here is on
capturing the detailed context and rationales for the CGI Level 2 requirements.
The WFIRST requirements flow starts with the top Program Level Requirements
Appendix (PLRA), which contains both high-level mission objectives as well as
the CGI-specific baseline technical and data requirements (BTR and BDR,
respectively)... We also present the process and collaborative tools used in
the L2 requirements development and management, including the collection and
organization of science inputs, an open-source approach to managing the
requirements database, and automating documentation. The tools created for the
CGI L2 requirements have the potential to improve the design and planning of
other projects, streamlining requirement management and maintenance. [Abstract
Abbreviated]Comment: 16 pages, 4 figure
Guide to Good Practice in using Open Source Compilers with the AGCC Lexical Analyzer
Quality software always demands a compromise between users' needs and hardware resources. To be faster means expensive devices like powerful processors and virtually unlimited amounts of RAM memory. Or you just need reengineering of the code in terms of adapting that piece of software to the client's hardware architecture. This is the purpose of optimizing code in order to get the utmost software performance from a program in certain given conditions. There are tools for designing and writing the code but the ultimate tool for optimizing remains the modest compiler, this often neglected software jewel the result of hundreds working hours by the best specialists in the world. Even though, only two compilers fulfill the needs of professional developers, a proprietary solution from a giant in the IT industry, and the Open source GNU compiler, for which we develop the AGCC lexical analyzer that helps producing even more efficient software applications. It relies on the most popular hacks and tricks used by professionals and discovered by the author who are proud to present them further below.registers, dynamic linkage, cache, null pointers, tweaking
GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs
We present a prototype of a software tool for exploration of multiple
combinatorial optimisation problems in large real-world and synthetic complex
networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial
Explorer), provides a unified framework for scalable computation and
presentation of high-quality suboptimal solutions and bounds for a number of
widely studied combinatorial optimisation problems. Efficient representation
and applicability to large-scale graphs and complex networks are particularly
considered in its design. The problems currently supported include maximum
clique, graph colouring, maximum independent set, minimum vertex clique
covering, minimum dominating set, as well as the longest simple cycle problem.
Suboptimal solutions and intervals for optimal objective values are estimated
using scalable heuristics. The tool is designed with extensibility in mind,
with the view of further problems and both new fast and high-performance
heuristics to be added in the future. GraphCombEx has already been successfully
used as a support tool in a number of recent research studies using
combinatorial optimisation to analyse complex networks, indicating its promise
as a research software tool
Preserving Command Line Workflow for a Package Management System Using ASCII DAG Visualization
Package managers provide ease of access to applications by removing the time-consuming and sometimes completely prohibitive barrier of successfully building, installing, and maintaining the software for a system. A package dependency contains dependencies between all packages required to build and run the target software. Package management system developers, package maintainers, and users may consult the dependency graph when a simple listing is insufficient for their analyses. However, users working in a remote command line environment must disrupt their workflow to visualize dependency graphs in graphical programs, possibly needing to move files between devices or incur forwarding lag. Such is the case for users of Spack, an open source package management system originally developed to ease the complex builds required by supercomputing environments. To preserve the command line workflow of Spack, we develop an interactive ASCII visualization for its dependency graphs. Through interviews with Spack maintainers, we identify user goals and corresponding visual tasks for dependency graphs. We evaluate the use of our visualization through a command line-centered study, comparing it to the system's two existing approaches. We observe that despite the limitations of the ASCII representation, our visualization is preferred by participants when approached from a command line interface workflow.U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344, LLNL-JRNL-746358]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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