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Automated Kaguya TC and MRO CTX Stereo DEM Generation 5th Planetary Data Workshop and 2nd Planetary Science Informatics & Data Analytics Meeting Processing Session 1: June 28, 2021 Lauren A. Adoram-Kershner, [email protected] Ben H. Wheeler, [email protected] Jason R. Laura, [email protected] Robin L. Fergason, [email protected] David P. Mayer, [email protected] Motivation • The volume of stereographic images coupled with manual generation standard means a lot of DEM potential. Figure 2: Distribution of • Targeted generation; not covering full datasets. Kaguya TC stereopairs. • Served across various research institutes applying their own processing. • Difficulty tracing provenance of processing typically contained in separate paper(s). Method: Serving LOLA RDR ASAP-Stereo, Ames Stereo Automated Pipeline A. M. Annex1, K. W. Lewis1. 1Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD 21218, USA ([email protected]) 1 @AndrewAnnex [email protected] www.andrewannex.com What is ASAP-Stereo? 1. Python Library and CLI, higher-level wrapper for Ames Stereo Pipeline 2. Framework to implement ASP workflows, currently implements “asp_scripts” for HiRISE & CTX with enhancements Why use ASAP-Stereo? 1. Reproducibility with Jupyter Notebooks, avoid ad hoc processing! 2. Speedups over asp_scripts 3. Ease of use, less monitoring 2 @AndrewAnnex [email protected] www.andrewannex.com Try ASAP-Stereo! Welcoming contributions for other instruments! Links: https://asap-stereo.readthedocs.io https://asap-stereo.readthedocs.io/en/main/install.html https://github.com/AndrewAnnex/asap_stereo https://doi.org/10.5281/zenodo.4171570 3 @AndrewAnnex [email protected] www.andrewannex.com High-Throughput Processing of Diviner Data from the Planetary Data System (PDS) Norbert Schorghofer ([email protected]) Planetary Science Institute, Arizona & Hawaii June 2021, Lightning Presentation, Abstract #7004 I The PDS currently holds about 2 PB of data; High-throughput data processing is increasingly important I Case Study: Diviner, onboard LRO, 160 TB of numerical data I Benchmarked various compression ﬁle formats for these data I Benchmarked decompression | awk I Benchmarked parallel processing from single drive (HDD + SSD) I How can I get my hardware's worth of throughput, or more? File Size and Decompression Speed 20 lzma br zst-19 15 rzip bz2 10 lzma-0 br-9 rar zst zip gz Compression Ratio Compression lz4-9 5 lz4 txt 0 0 0.2 0.4 0.6 0.8 Decompression Speed (GB/s) Parallel Throughput, Solid State Drive (SSD) 1.2 txt gzip lz4-9 1 lzma zip 0.8 zstd-19 0.6 Throughput (GB/s)Throughput 0.4 0.2 0 1 2 3 4 5 6 # Parallel Processes Throughput relative to uncompressed ﬁle size..

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Table of Contents Modules and Packages
Table of Contents Modules and Packages...........................................................................................1 Software on NAS Systems..................................................................................................1 Using Software Packages in pkgsrc...................................................................................4 Using Software Modules....................................................................................................7 Modules and Packages Software on NAS Systems UPDATE IN PROGRESS: Starting with version 2.17, SGI MPT is officially known as HPE MPT. Use the command module load mpi-hpe/mpt to get the recommended version of MPT library on NAS systems. This article is being updated to reflect this change. Software programs on NAS systems are managed as modules or packages. Available programs are listed in tables below. Note: The name of a software module or package may contain additional information, such as the vendor name, version number, or what compiler/library is used to build the software. For example: • comp-intel/2016.2.181 - Intel Compiler version 2016.2.181 • mpi-sgi/mpt.2.15r20 - SGI MPI library version 2.15r20 • netcdf/4.4.1.1_mpt - NetCDF version 4.4.1.1, built with SGI MPT Modules Use the module avail command to see all available software modules. Run module whatis to view a short description of every module. For more information about a specific module, run module help modulename. See Using Software Modules for more information. Available Modules (as
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An Optimal Real-Time Controller for Vertical Plasma Stabilization N
1 An optimal real-time controller for vertical plasma stabilization N. Cruz, J.-M. Moret, S. Coda, B.P. Duval, H.B. Le, A.P. Rodrigues, C.A.F. Varandas, C.M.B.A. Correia and B. Gonçalves Abstract—Modern Tokamaks have evolved from the initial ax- presents important advantages since it allows the creation isymmetric circular plasma shape to an elongated axisymmetric of divertor plasmas, the increase of the plasma current and plasma shape that improves the energy confinement time and the density limit as well as providing plasma stability. However, triple product, which is a generally used figure of merit for the conditions needed for fusion reactor performance. However, the an elongated plasma is unstable due to the forces that pull elongated plasma cross section introduces a vertical instability the plasma column upward or downward. The result of these that demands a real-time feedback control loop to stabilize forces is a plasma configuration that tends to be pushed up or the plasma vertical position and velocity. At the Tokamak down depending on the initial displacement disturbance. For Configuration Variable (TCV) in-vessel poloidal field coils driven example, a small displacement downwards results in the lower by fast switching power supplies are used to stabilize highly elongated plasmas. TCV plasma experiments have used a PID poloidal field coils pulling the plasma down, with increased algorithm based controller to correct the plasma vertical position. strength as the plasma gets further from the equilibrium posi- In late 2013 experiments a new optimal real-time controller was tion. To compensate this instability, feedback controllers have tested improving the stability of the plasma.
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Aligning Intent and Behavior in Software Systems: How Programs Communicate & Their Distribution and Organization
© 2020 William B. Dietz ALIGNING INTENT AND BEHAVIOR IN SOFTWARE SYSTEMS: HOW PROGRAMS COMMUNICATE & THEIR DISTRIBUTION AND ORGANIZATION BY WILLIAM B. DIETZ DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate College of the University of Illinois at Urbana-Champaign, 2020 Urbana, Illinois Doctoral Committee: Professor Vikram Adve, Chair Professor John Regehr, University of Utah Professor Tao Xie Assistant Professor Sasa Misailovic ABSTRACT Managing the overwhelming complexity of software is a fundamental challenge because complex- ity is the root cause of problems regarding software performance, size, and security. Complexity is what makes software hard to understand, and our ability to understand software in whole or in part is essential to being able to address these problems effectively. Attacking this overwhelming complexity is the fundamental challenge I seek to address by simplifying how we write, organize and think about programs. Within this dissertation I present a system of tools and a set of solutions for improving the nature of software by focusing on programmer’s desired outcome, i.e. their intent. At the program level, the conventional focus, it is impossible to identify complexity that, at the system level, is unnecessary. This “accidental complexity” includes everything from unused features to independent implementations of common algorithmic tasks. Software techniques driving innovation simultaneously increase the distance between what is intended by humans – developers, designers, and especially the users – and what the executing code does in practice. By preserving the declarative intent of the programmer, which is lost in the traditional process of compiling and linking and building software, it is easier to abstract away unnecessary details.
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Volume 5: DAF Variable Detail Pages
Anc hor Volume 5: DAF Variable Detail Pages August 2020 Submitted to: Social Security Administration Office of Retirement and Disability Policy Office of Research, Demonstration, and Employment Support Washington, DC 20024-2796 Project Officers: Paul O’Leary and Debra Tidwell-Peters Contract Number: SS00-16-60003 Submitted by: Mathematica 1100 1st Street, NE 12th Floor Washington, DC 20002-4221 Telephone: (202) 484-9220 Facsimile: (202) 863-1763 Project Director: Jody Schimmel Hyde Reference Number: 50214.Y3.T05.530.360 Suggested Citation: “Disability Analysis File 2018 (DAF18) Documentation: Data from January 1994 through December 2018.” Washington, DC: Mathematica, August 2020. This page has been left blank for double-sided copying. MATHEMATICA CONTENTS GLOSSARY .................................................................................................................................................. .v OVERVIEW OF DAF DOCUMENTATION ................................................................................................... .ix QUICK REFERENCE GUIDE ....................................................................................................................... 1 PART A DAF VARIABLE DETAIL PAGES .................................................................................................. 7 PART B RSA VARIABLE DETAIL PAGES .............................................................................................. 635 iii This page has been left blank for double-sided copying. MATHEMATICA GLOSSARY AB Accelerated
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Kafl: Hardware-Assisted Feedback Fuzzing for OS Kernels
kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels Sergej Schumilo1, Cornelius Aschermann1, Robert Gawlik1, Sebastian Schinzel2, Thorsten Holz1 1Ruhr-Universität Bochum, 2Münster University of Applied Sciences Motivation IJG jpeg libjpeg-turbo libpng libtiff mozjpeg PHP Mozilla Firefox Internet Explorer PCRE sqlite OpenSSL LibreOffice poppler freetype GnuTLS GnuPG PuTTY ntpd nginx bash tcpdump JavaScriptCore pdfium ffmpeg libmatroska libarchive ImageMagick BIND QEMU lcms Adobe Flash Oracle BerkeleyDB Android libstagefright iOS ImageIO FLAC audio library libsndfile less lesspipe strings file dpkg rcs systemd-resolved libyaml Info-Zip unzip libtasn1OpenBSD pfctl NetBSD bpf man mandocIDA Pro clamav libxml2glibc clang llvmnasm ctags mutt procmail fontconfig pdksh Qt wavpack OpenSSH redis lua-cmsgpack taglib privoxy perl libxmp radare2 SleuthKit fwknop X.Org exifprobe jhead capnproto Xerces-C metacam djvulibre exiv Linux btrfs Knot DNS curl wpa_supplicant Apple Safari libde265 dnsmasq libbpg lame libwmf uudecode MuPDF imlib2 libraw libbson libsass yara W3C tidy- html5 VLC FreeBSD syscons John the Ripper screen tmux mosh UPX indent openjpeg MMIX OpenMPT rxvt dhcpcd Mozilla NSS Nettle mbed TLS Linux netlink Linux ext4 Linux xfs botan expat Adobe Reader libav libical OpenBSD kernel collectd libidn MatrixSSL jasperMaraDNS w3m Xen OpenH232 irssi cmark OpenCV Malheur gstreamer Tor gdk-pixbuf audiofilezstd lz4 stb cJSON libpcre MySQL gnulib openexr libmad ettercap lrzip freetds Asterisk ytnefraptor mpg123 exempi libgmime pev v8 sed awk make
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Pipenightdreams Osgcal-Doc Mumudvb Mpg123-Alsa Tbb
pipenightdreams osgcal-doc mumudvb mpg123-alsa tbb-examples libgammu4-dbg gcc-4.1-doc snort-rules-default davical cutmp3 libevolution5.0-cil aspell-am python-gobject-doc openoffice.org-l10n-mn libc6-xen xserver-xorg trophy-data t38modem pioneers-console libnb-platform10-java libgtkglext1-ruby libboost-wave1.39-dev drgenius bfbtester libchromexvmcpro1 isdnutils-xtools ubuntuone-client openoffice.org2-math openoffice.org-l10n-lt lsb-cxx-ia32 kdeartwork-emoticons-kde4 wmpuzzle trafshow python-plplot lx-gdb link-monitor-applet libscm-dev liblog-agent-logger-perl libccrtp-doc libclass-throwable-perl kde-i18n-csb jack-jconv hamradio-menus coinor-libvol-doc msx-emulator bitbake nabi language-pack-gnome-zh libpaperg popularity-contest xracer-tools xfont-nexus opendrim-lmp-baseserver libvorbisfile-ruby liblinebreak-doc libgfcui-2.0-0c2a-dbg libblacs-mpi-dev dict-freedict-spa-eng blender-ogrexml aspell-da x11-apps openoffice.org-l10n-lv openoffice.org-l10n-nl pnmtopng libodbcinstq1 libhsqldb-java-doc libmono-addins-gui0.2-cil sg3-utils linux-backports-modules-alsa-2.6.31-19-generic yorick-yeti-gsl python-pymssql plasma-widget-cpuload mcpp gpsim-lcd cl-csv libhtml-clean-perl asterisk-dbg apt-dater-dbg libgnome-mag1-dev language-pack-gnome-yo python-crypto svn-autoreleasedeb sugar-terminal-activity mii-diag maria-doc libplexus-component-api-java-doc libhugs-hgl-bundled libchipcard-libgwenhywfar47-plugins libghc6-random-dev freefem3d ezmlm cakephp-scripts aspell-ar ara-byte not+sparc openoffice.org-l10n-nn linux-backports-modules-karmic-generic-pae
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Systems Cost/Performance Analysis (Study 2.3) Final Report
AEROSPffE REPORT NO. AZ "'14(7343)-1, VOL III Systems Cost/Performance Analysis (Study 2.3) Final Report Volume IH: Programmer's Manual and User's Guide Prepared by V'< ADVANCED MISSION ANALYSIS DIRECTORATE Advanced Orbital Systems Division 27 September 1974 Prepared for OFFICE OF MANNED SPACE FLIGHT NATIONAL AERONAUTICS AND SPACE ADMINISTRATION Washington, D.C. 20546 Contract No. NASW-2575 Systems Engineering Operations THE AEROSPACE CORPORATION .(NASA-C-lP3377) SYSTEMS COSr/PERFORACE N75-309211 ANALYSIS (STUDY 2.3). VOLUME 3: IPROG AMER'S MANUAL AND USER'S GUIDE Final Report (Aerospace Corp., El Segundo, Calif.) Unclas 592 p HC $13.25 CSCL 05A G3/8-1 34377 ) Aerospace Report No. ATR-74(7343)-I, Vol, III SYSTEMS COST/PERFORMANCE ANALYSIS (STUDY 2. 3) FINAL REPORT Volume III: Programmer's Manual and User's Guide Prepared by Advanced Mission Analysis Directorate Advanced Orbital Systems Division Z7 September 1974 Systems Engineering Operations THE AEROSPACE CORPORATION El Segundo, California Prepared for OFFICE OF MANNED SPACE FLIGHT NATIONAL AERONAUTICS AND SPACE ADMINISTRATION Washington, D. C. Contract No. NASW-2575 PAGE INTENTIONALLY BLANK Aerospace Report No. ATR-74(7343)-I, Vol. III SYSTEMS COST/PERFORMANCE ANALYSIS (STUDY 2. 3) FINAL REPORT Volume III: Programmer's Manual and User's Guide Prepared R *F.OJ , Man e Data Sys ems An sis Section Data Processing Subdivision Approved L. Sashkin, Director R. H. Herndon, Assoc. Group Data Processing Subdivision Director Information Processing Division Advanced Mission Analysis Engineering Science Operations Directorate Advanced Orbital Systems Division PRECEDING PAGE-iii- BLANK NOT FILMED PAGE INTENTIONALLY BLANK FOREWORD This report documents The Aerospace Corporation effort on Study 2.3, Systems Cost/Perfbrmance Analysis, performed under NASA Contract NASW-2575 during Fiscal Year 1974.
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Porovnání Komprimaˇcních Program ˚U Na Textových Korpusech
MASARYKOVA UNIVERZITA FAKULTA}w¡¢£¤¥¦§¨ INFORMATIKY !"#$%&'()+,-./012345<yA| Porovnání komprimaˇcních program ˚una textových korpusech BAKALÁRSKÁˇ PRÁCE Jakub Foltas Brno, 2014 Prohlášení Prohlašuji, že tato bakaláˇrskápráce je mým p ˚uvodnímautorským dílem, které jsem vypracoval samostatnˇe.Všechny zdroje, prameny a literaturu, které jsem pˇrivypracování používal nebo z nich ˇcerpal, v práci ˇrádnˇecituji s uvedením úplného odkazu na pˇríslušnýzdroj. Jakub Foltas Vedoucí práce: RNDr. Miloš Jakubíˇcek ii Podˇekování Chtˇelbych podˇekovatvedoucímu mé bakaláˇrské práce RNDr. Mi- loši Jakubíˇckoviza odborné vedení, cenné rady a trpˇelivost,kterou se mnou mˇel.Také bych rád podˇekovalsvé rodinˇea pˇrátel˚umza podporu, kterou mi v dobˇepsaní bakaláˇrsképráce poskytovali. iii Shrnutí Bakaláˇrskápráce se zabývá porovnáním volnˇedostupných bezeztrá- tových komprimaˇcníchprogram ˚una textových korpusech. Hlavním cílem výzkumu bylo najít vhodný komprimaˇcníprogram, který by nahradil souˇcasnˇepoužívaný program XZ v Laboratoˇripro zpraco- vání pˇrirozeného jazyka pˇriMasarykovˇeuniverzitˇe. Testování na dvou odlišných textových korpusech se podrobilo celkem dvacet volnˇedostupných komprimaˇcníchprogram ˚u.Primár- ním kritériem porovnání byla urˇcenavelikost komprimace. Dále byla porovnávána doba bˇehuprogramu a programové vytížení pamˇeti. Dalším pˇredmˇetemzkoumání byly úˇcinkypˇredzpracováníkorpus ˚u pˇredsamotnou komprimací testovanými programy. Tˇriprogramy dokázaly korektnˇezkomprimovat oba zadané kor- pusy a významnˇepˇredˇcilysouˇcasnˇepoužívaný
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IZO: Applications of Large-Window Compression to Virtual Machine Management
IZO: Applications of Large-Window Compression to Virtual Machine Management Mark A. Smith, Jan Pieper, Daniel Gruhl, and Lucas Villa Real – IBM Almaden Research Center ABSTRACT The increased use of virtual machines in the enterprise environment presents an interesting new set of challenges for the administrators of today’s information systems. In addition to the management of the sheer volume of easily-created new data on physical machines, VMs themselves contain data that is important to the user of the virtual machine. Efficient storage, transmission, and backup of VM images has become a growing concern. We present IZO, a novel large-window compression tool inspired by data deduplication algorithms, which provides significantly faster and better compression than existing large-window compression tools. We apply this tool to a number of VM management domains, including deep-freeze, backup, and transmission, to more efficiently store, administer, and move virtual machines. Introduction We find this property analogous to the way a suitcase is packed. It is possible to simply stuff all of Virtual machines are becoming an increasingly one’s clothes into a suitcase, sit on the lid, and zip it important tool for reducing costs in enterprise comput- ing. The ability to generate a machine for a task, and up. However, if the clothes are folded first, and then know it has a clean install of a given OS can be an compressed, they will fit in a smaller space in less invaluable time saver. It provides a degree of separa- time. Large-window compression can be thought of as tion that simplifies support (a major cost) as people all the folding step, while small-window gzip style com- get their ‘‘own’’ machines [26].
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UCLA Electronic Theses and Dissertations
UCLA UCLA Electronic Theses and Dissertations Title Datacomp: Locally-independent Adaptive Compression for Real-World Systems Permalink https://escholarship.org/uc/item/0c3453tc Author Peterson, Peter Andrew Harrington Publication Date 2013 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA Los Angeles Datacomp: Locally-independent Adaptive Compression for Real-World Systems A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Peter Andrew Harrington Peterson 2013 © Copyright Peter Andrew Harrington Peterson 2013 ABSTRACT OF THE DISSERTATION Datacomp: Locally-independent Adaptive Compression for Real-World Systems by Peter Andrew Harrington Peterson Doctor of Philosophy in Computer Science University of California, Los Angeles, 2013 Professor Todd Millstein, Co-chair Professor Peter Reiher, Co-chair Typically used to save space, non-lossy data compression can save time and energy during communication if the cost to compress and send data is less than the cost of sending uncompressed data. However, compression can degrade efficiency if it compresses insufficiently or delays the operation significantly, which can depend on many factors. Because predicting the best strategy is risky and difficult, compression (if available) is typically manually controlled, resulting in missed opportunities and avoidable losses. This dissertation describes Datacomp, a general-purpose Adaptive Compression (AC) framework that improves efficiency in terms of time, space and energy for real-world workloads on real-world systems like laptops and smartphones. Prior systems are limited in important ways or rely on external hosts for prediction and compression, reducing their effectiveness or imposing unnecessary dependencies.
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MIGRATORY COMPRESSION Coarse-Grained Data Reordering to Improve Compressibility
MIGRATORY COMPRESSION Coarse-grained Data Reordering to Improve Compressibility Xing Lin*, Guanlin Lu, Fred Douglis, Philip Shilane, Grant Wallace *University of Utah EMC Corporation Data Protection and Availability Division © Copyright 2014 EMC Corporation. All rights reserved. 1 Overview Compression： finds redundancy among strings within a certain distance (window size) – Problem: window sizes are small, and similarity across a larger distance will not be identified Migratory compression (MC): coarse-grained reorganization to group similar blocks to improve compressibility – A generic pre-processing stage for standard compressors – In many cases, improve both compressibility and throughput – Effective for improving compression for archival storage © Copyright 2014 EMC Corporation. All rights reserved. 2 Background • Compression Factor (CF) = ratio of original / compressed • Throughput = original size / (de)compression time Compressor MAX Window size Techniques gzip 64 KB LZ; Huffman coding bzip2 900 KB Run-length encoding; Burrows-Wheeler Transform; Huffman coding 7z 1 GB LZ; Markov chain-based range coder © Copyright 2014 EMC Corporation. All rights reserved. 3 Background • Compression Factor (CF) = ratio of original / compressed • Throughput = original size / (de)compression time Compressor MAX Window size Techniques gzip 64 KB LZ; Huffman coding bzip2 900 KB Run-length encoding; Burrows-Wheeler Transform; Huffman coding 7z 1 GB LZ; Markov chain-based range coder © Copyright 2014 EMC Corporation. All rights reserved. 4 Background • Compression Factor (CF) = ratio of original / compressed • Throughput = original size / (de)compression time Compressor MAX Window size Techniques Example Throughput vs. CF gzip 64 KB LZ; Huffman coding 14 gzip bzip2 900 KB Run-length encoding; Burrows- 12 Wheeler Transform; Huffman coding 10 (MB/s) 7z 1 GB LZ; Markov chain-based range 8 coder Tput 6 bzip2 4 7z 2 0 Compression 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Compression Factor (X) The larger the window, the better the compression but slower © Copyright 2014 EMC Corporation.
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Disk Space Management Topics for SAS in the Solaris
NESUG 17 Administration & Support Disk Space Management Topics for SASR in the SolarisTM Operating Environment Adeline J. Wilcox Delmarva Foundation for Medical Care, Inc. Hanover, MD 1ABSTRACT Adding disk space to SunR enterprise servers has become a relatively inexpensive solution. Still, these gigabytes and terabytes are finite and must be managed. I address two related topics, file compression and reporting disk space usage BY user. First, I describe a Kornshell script that calls sed, awk, and SAS before producing a SAS listing showing gigabytes used by userid. Second, I performed factorial experiments in which I compared the CHAR, BINARY, and NO values of the SAS data set COMPRESS option with each other and with the UNIX compress program. UNIX compress effectively compressed all three types of test SAS data sets but minimized file size when SAS COMPRESS=NO. Using ten replicates, I also measured the CPU time required to run PROC FREQ on one character variable from each test data set compressed the three different ways with SAS. As expected, PROC FREQ executed most quickly on SAS data sets with COMPRESS=NO. When no UNIX compression was used, SAS took, on average, 73 percent longer to execute PROC FREQ on SAS data sets with SAS COMPRESS=CHAR than those with SAS COMPRESS=NO. 2INTRODUCTION This paper covers two related topics, file compression and reporting disk space usage by userid, both specific to running SAS on Solaris. The first topic, reporting disk space usage by userid, may be relevant to any UNIX or Linux system running the KornShell, sed, awk and SAS.
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