The Netlib Mathematical Software Repository
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Developer Survey
Developer Survey Questions requiring a response are in r ed . Questions in which a response is NOT required are in blue. This survey is a critical element of the developers workshop. We are using it to capture nuts and bolts information about codes within the community so that we can assess the landscape before the workshop and use this information to drive the discussions. Please collaborate to provide only one submission per code and submit your response using the online survey: h ttps://ucdavis.co1.qualtrics.com/jfe/form/SV_57wtv4gpuaowTsh Basic Information Code identification 1. What is the name of the code? [small text box] 2. Who are the primary authors/maintainers? [medium text box] 3. URL of webpage for the code (if different than the version control repository) [small text box] 4. URL of version control repository (if public) [small text box] Software 1. Which license(s) do you use? Select all that apply. a. Apache license b. BSD license c. GNU General Public License d. GNU Lesser General Public License e. MIT license f. Mozilla Public License g. Common Development and Distribution License h. Eclipse Public License i. Other. Please specify [small text box] j. No license 2. What programming language(s) is your code currently written in? Select all that apply a. Fortran 77 b. Fortran 90 or later c. C d. C++ e. Go f. Python g. Julia h. Matlab i. Other. Please specify. [small text box] 3. List the primary (high-level) code dependencies (e.g., PETSc, deal.ii, FEniCS) [medium text box] 4. List any additional (low-level) code dependencies (e.g., MPI, NetCDF, HDF5) [medium text box] 5. -
Updating Systems and Adding Software in Oracle® Solaris 11.4
Updating Systems and Adding Software ® in Oracle Solaris 11.4 Part No: E60979 November 2020 Updating Systems and Adding Software in Oracle Solaris 11.4 Part No: E60979 Copyright © 2007, 2020, Oracle and/or its affiliates. License Restrictions Warranty/Consequential Damages Disclaimer This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. Warranty Disclaimer The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. Restricted Rights Notice If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs) and Oracle computer documentation or other Oracle data delivered to or accessed by U.S. Government end users are "commercial -
Project Report
Project Report An Extension of CodeFeedr Team 1Up Project Report An Extension of CodeFeedr by Roald van der Heijden, Matthijs van Wijngaarden, Wouter Zonneveld in order to obtain the degree of Bachelor of Science in Computer Science at the Delft University of Technology, to be defended publicly on the 5th of February 2020, 10:30 Project duration: November 11, 2019 – January 31, 2020 Thesis committee: Dr. G. Gousios, Client, TU Delft Dr. A. Katsifodimos, Supervisor, TU Delft Dr. H. Wang, Bachelor Project Coordinator, TU Delft An electronic version of this thesis is available at http://repository.tudelft.nl/. Contents 1 Introduction 4 2 CodeFeedr 5 2.1 Overview.........................................5 2.2 Architecture........................................5 2.3 Dependencies.......................................6 3 Research Report 7 3.1 Overview.........................................7 3.2 Problem Description...................................7 3.3 Design Goals.......................................8 3.4 Requirement Analysis...................................9 3.5 Development Methodology................................ 10 3.6 Related Work....................................... 11 3.7 Design Choices...................................... 12 4 Software Architecture 15 4.1 Design Patterns...................................... 15 4.2 Plugins.......................................... 15 4.3 SQL REPL......................................... 17 5 Implementation 18 5.1 Plugins.......................................... 18 5.2 SQL REPL........................................ -
Over-Scalapack.Pdf
1 2 The Situation: Parallel scienti c applications are typically Overview of ScaLAPACK written from scratch, or manually adapted from sequen- tial programs Jack Dongarra using simple SPMD mo del in Fortran or C Computer Science Department UniversityofTennessee with explicit message passing primitives and Mathematical Sciences Section Which means Oak Ridge National Lab oratory similar comp onents are co ded over and over again, co des are dicult to develop and maintain http://w ww .ne tl ib. org /ut k/p e opl e/J ackDo ngarra.html debugging particularly unpleasant... dicult to reuse comp onents not really designed for long-term software solution 3 4 What should math software lo ok like? The NetSolve Client Many more p ossibilities than shared memory Virtual Software Library Multiplicityofinterfaces ! Ease of use Possible approaches { Minimum change to status quo Programming interfaces Message passing and ob ject oriented { Reusable templates { requires sophisticated user Cinterface FORTRAN interface { Problem solving environments Integrated systems a la Matlab, Mathematica use with heterogeneous platform Interactiveinterfaces { Computational server, like netlib/xnetlib f2c Non-graphic interfaces Some users want high p erf., access to details {MATLAB interface Others sacri ce sp eed to hide details { UNIX-Shell interface Not enough p enetration of libraries into hardest appli- Graphic interfaces cations on vector machines { TK/TCL interface Need to lo ok at applications and rethink mathematical software { HotJava Browser -
Diplomat: Using Delegations to Protect Community Repositories
Diplomat: Using Delegations to Protect Community Repositories Trishank Karthik Kuppusamy, Santiago Torres-Arias, Vladimir Diaz, and Justin Cappos, New York University https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/kuppusamy This paper is included in the Proceedings of the 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’16). March 16–18, 2016 • Santa Clara, CA, USA ISBN 978-1-931971-29-4 Open access to the Proceedings of the 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’16) is sponsored by USENIX. Diplomat: Using Delegations to Protect Community Repositories Trishank Karthik Kuppusamy Santiago Torres-Arias Vladimir Diaz Justin Cappos Tandon School of Engineering, New York University Abstract software. Major repositories run by Adobe, Apache, Debian, Fedora, FreeBSD, Gentoo, GitHub, GNU Sa- Community repositories, such as Docker Hub, PyPI, vannah, Linux, Microsoft, npm, Opera, PHP, RedHat, and RubyGems, are bustling marketplaces that distribute RubyGems, SourceForge, and WordPress repositories software. Even though these repositories use common have all been compromised at least once [4,5,7,27,28,30, software signing techniques (e.g., GPG and TLS), at- 31,35,36,39–41,48,59,61,62,67,70,79,80,82,86,87,90]. tackers can still publish malicious packages after a server For example, a compromised SourceForge repository compromise. This is mainly because a community repos- mirror located in Korea distributed a malicious ver- itory must have immediate access to signing keys in or- sion of phpMyAdmin, a popular database administration der to certify the large number of new projects that are tool [79]. The modified version allowed attackers to gain registered each day. -
Prospectus for the Next LAPACK and Scalapack Libraries
Prospectus for the Next LAPACK and ScaLAPACK Libraries James Demmel1, Jack Dongarra23, Beresford Parlett1, William Kahan1, Ming Gu1, David Bindel1, Yozo Hida1, Xiaoye Li1, Osni Marques1, E. Jason Riedy1, Christof Voemel1, Julien Langou2, Piotr Luszczek2, Jakub Kurzak2, Alfredo Buttari2, Julie Langou2, Stanimire Tomov2 1 University of California, Berkeley CA 94720, USA, 2 University of Tennessee, Knoxville TN 37996, USA, 3 Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA, 1 Introduction Dense linear algebra (DLA) forms the core of many scienti¯c computing appli- cations. Consequently, there is continuous interest and demand for the devel- opment of increasingly better algorithms in the ¯eld. Here 'better' has a broad meaning, and includes improved reliability, accuracy, robustness, ease of use, and most importantly new or improved algorithms that would more e±ciently use the available computational resources to speed up the computation. The rapidly evolving high end computing systems and the close dependence of DLA algo- rithms on the computational environment is what makes the ¯eld particularly dynamic. A typical example of the importance and impact of this dependence is the development of LAPACK [1] (and later ScaLAPACK [2]) as a successor to the well known and formerly widely used LINPACK [3] and EISPACK [3] libraries. Both LINPACK and EISPACK were based, and their e±ciency depended, on optimized Level 1 BLAS [4]. Hardware development trends though, and in par- ticular an increasing Processor-to-Memory speed gap of approximately 50% per year, started to increasingly show the ine±ciency of Level 1 BLAS vs Level 2 and 3 BLAS, which prompted e®orts to reorganize DLA algorithms to use block matrix operations in their innermost loops. -
Jack Dongarra: Supercomputing Expert and Mathematical Software Specialist
Biographies Jack Dongarra: Supercomputing Expert and Mathematical Software Specialist Thomas Haigh University of Wisconsin Editor: Thomas Haigh Jack J. Dongarra was born in Chicago in 1950 to a he applied for an internship at nearby Argonne National family of Sicilian immigrants. He remembers himself as Laboratory as part of a program that rewarded a small an undistinguished student during his time at a local group of undergraduates with college credit. Dongarra Catholic elementary school, burdened by undiagnosed credits his success here, against strong competition from dyslexia.Onlylater,inhighschool,didhebeginto students attending far more prestigious schools, to Leff’s connect material from science classes with his love of friendship with Jim Pool who was then associate director taking machines apart and tinkering with them. Inspired of the Applied Mathematics Division at Argonne.2 by his science teacher, he attended Chicago State University and majored in mathematics, thinking that EISPACK this would combine well with education courses to equip Dongarra was supervised by Brian Smith, a young him for a high school teaching career. The first person in researcher whose primary concern at the time was the his family to go to college, he lived at home and worked lab’s EISPACK project. Although budget cuts forced Pool to in a pizza restaurant to cover the cost of his education.1 make substantial layoffs during his time as acting In 1972, during his senior year, a series of chance director of the Applied Mathematics Division in 1970– events reshaped Dongarra’s planned career. On the 1971, he had made a special effort to find funds to suggestion of Harvey Leff, one of his physics professors, protect the project and hire Smith. -
Designdocument < Hellasgrid/Egiumdrepository
Table of Contents EGI Repository Design Document...................................................................................................................1 Executive Summary................................................................................................................................1 Glossary..................................................................................................................................................1 Table of Contents....................................................................................................................................1 Introduction and Requirements and Objectives......................................................................................1 Operations on the repository............................................................................................................2 Contents of the repository................................................................................................................2 Supported Projects............................................................................................................................2 Users and User's Roles in the Repository...............................................................................................2 Repository Contents for End Users..................................................................................................3 Repository Administrators...............................................................................................................3 -
Kace Asset Management Guide
Kace Asset Management Guide Metaphorical Lucio always evangelising his synarchy if Moishe is capitular or writhe sufferably. Hymenopterous Sibyl always politicks his decimators if Aub is alabastrine or site photogenically. Which Rodolph breezed so fined that Swen inculcated her speculator? With kace customers run quest kace systems management, united states merchant marine academy. Maintenance costs have been annualized over several period on three years to extract their harvest over time. Comparing suites from sap helps clients bring their asset management solutions provider hardinge inc, kace asset management are stored in lifecycle management feature relies on active assets. Learn how asset management leaders are ensuring a reliable and sustainable supply chain, Microsoft and Symantec all require the installation of an agent to perform OS and application discovery tasks, and Symantec problems. You need to unselect a conflict with. Using Custom fields Within software Asset where in Dell KACE, etc. Are you sure you as to delete your attachment? All four evaluated solutions include: antioch university as well as it opens a solution helps track down systems management? An integrated mechanism to report problems and service requests enables prompt response to end users and reduces administrative roadblocks. Product was easy to use. To analyze the opportunities in the market for stakeholders by identifying the high growth segments. Best Practices in Lifecycle Management: Comparing Suites from Dell, and complete security. Although Microsoft does not natively include vulnerability scans, this in proper way detracts from our investment in supporting operating systems regardless of equipment brand. Past performance is just poor indicator of future performance. -
Possible Directions for Improving Dependency Versioning in R by Jeroen Ooms
CONTRIBUTED RESEARCH ARTICLES 197 Possible Directions for Improving Dependency Versioning in R by Jeroen Ooms Abstract One of the most powerful features of R is its infrastructure for contributed code. The built-in package manager and complementary repositories provide a great system for development and exchange of code, and have played an important role in the growth of the platform towards the de-facto standard in statistical computing that it is today. However, the number of packages on CRAN and other repositories has increased beyond what might have been foreseen, and is revealing some limitations of the current design. One such problem is the general lack of dependency versioning in the infrastructure. This paper explores this problem in greater detail, and suggests approaches taken by other open source communities that might work for R as well. Three use cases are defined that exemplify the issue, and illustrate how improving this aspect of package management could increase reliability while supporting further growth of the R community. Package management in R One of the most powerful features of R is its infrastructure for contributed code (Fox, 2009). The base R software suite that is released several times per year ships with the base and recommended packages and provides a solid foundation for statistical computing. However, most R users will quickly resort to the package manager and install packages contributed by other users. By default, these packages are installed from the “Comprehensive R Archive Network” (CRAN), featuring over 4300 contributed packages as of 2013. In addition, other repositories like BioConductor (Gentleman et al., 2004) and Github (Dabbish et al., 2012) are hosting a respectable number of packages as well. -
C++ API for BLAS and LAPACK
2 C++ API for BLAS and LAPACK Mark Gates ICL1 Piotr Luszczek ICL Ahmad Abdelfattah ICL Jakub Kurzak ICL Jack Dongarra ICL Konstantin Arturov Intel2 Cris Cecka NVIDIA3 Chip Freitag AMD4 1Innovative Computing Laboratory 2Intel Corporation 3NVIDIA Corporation 4Advanced Micro Devices, Inc. February 21, 2018 This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, in support of the nation's exascale computing imperative. Revision Notes 06-2017 first publication 02-2018 • copy editing, • new cover. 03-2018 • adding a section about GPU support, • adding Ahmad Abdelfattah as an author. @techreport{gates2017cpp, author={Gates, Mark and Luszczek, Piotr and Abdelfattah, Ahmad and Kurzak, Jakub and Dongarra, Jack and Arturov, Konstantin and Cecka, Cris and Freitag, Chip}, title={{SLATE} Working Note 2: C++ {API} for {BLAS} and {LAPACK}}, institution={Innovative Computing Laboratory, University of Tennessee}, year={2017}, month={June}, number={ICL-UT-17-03}, note={revision 03-2018} } i Contents 1 Introduction and Motivation1 2 Standards and Trends2 2.1 Programming Language Fortran............................ 2 2.1.1 FORTRAN 77.................................. 2 2.1.2 BLAST XBLAS................................. 4 2.1.3 Fortran 90.................................... 4 2.2 Programming Language C................................ 5 2.2.1 Netlib CBLAS.................................. 5 2.2.2 Intel MKL CBLAS................................ 6 2.2.3 Netlib lapack cwrapper............................. 6 2.2.4 LAPACKE.................................... 7 2.2.5 Next-Generation BLAS: \BLAS G2"..................... -
A Peer-To-Peer Framework for Message Passing Parallel Programs
A Peer-to-Peer Framework for Message Passing Parallel Programs Stéphane GENAUD a;1, and Choopan RATTANAPOKA b;2 a AlGorille Team - LORIA b King Mongkut’s University of Technology Abstract. This chapter describes the P2P-MPI project, a software framework aimed at the development of message-passing programs in large scale distributed net- works of computers. Our goal is to provide a light-weight, self-contained software package that requires minimum effort to use and maintain. P2P-MPI relies on three features to reach this goal: i) its installation and use does not require administra- tor privileges, ii) available resources are discovered and selected for a computation without intervention from the user, iii) program executions can be fault-tolerant on user demand, in a completely transparent fashion (no checkpoint server to config- ure). P2P-MPI is typically suited for organizations having spare individual comput- ers linked by a high speed network, possibly running heterogeneous operating sys- tems, and having Java applications. From a technical point of view, the framework has three layers: an infrastructure management layer at the bottom, a middleware layer containing the services, and the communication layer implementing an MPJ (Message Passing for Java) communication library at the top. We explain the de- sign and the implementation of these layers, and we discuss the allocation strategy based on network locality to the submitter. Allocation experiments of more than five hundreds peers are presented to validate the implementation. We also present how fault-management issues have been tackled. First, the monitoring of the infras- tructure itself is implemented through the use of failure detectors.