Build Guide for Mingw (Draft)
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Cygwin User's Guide
Cygwin User’s Guide Cygwin User’s Guide ii Copyright © Cygwin authors Permission is granted to make and distribute verbatim copies of this documentation provided the copyright notice and this per- mission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this documentation under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this documentation into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the Free Software Foundation. Cygwin User’s Guide iii Contents 1 Cygwin Overview 1 1.1 What is it? . .1 1.2 Quick Start Guide for those more experienced with Windows . .1 1.3 Quick Start Guide for those more experienced with UNIX . .1 1.4 Are the Cygwin tools free software? . .2 1.5 A brief history of the Cygwin project . .2 1.6 Highlights of Cygwin Functionality . .3 1.6.1 Introduction . .3 1.6.2 Permissions and Security . .3 1.6.3 File Access . .3 1.6.4 Text Mode vs. Binary Mode . .4 1.6.5 ANSI C Library . .4 1.6.6 Process Creation . .5 1.6.6.1 Problems with process creation . .5 1.6.7 Signals . .6 1.6.8 Sockets . .6 1.6.9 Select . .7 1.7 What’s new and what changed in Cygwin . .7 1.7.1 What’s new and what changed in 3.2 . -
Linear Algebra Libraries
Linear Algebra Libraries Claire Mouton [email protected] March 2009 Contents I Requirements 3 II CPPLapack 4 III Eigen 5 IV Flens 7 V Gmm++ 9 VI GNU Scientific Library (GSL) 11 VII IT++ 12 VIII Lapack++ 13 arXiv:1103.3020v1 [cs.MS] 15 Mar 2011 IX Matrix Template Library (MTL) 14 X PETSc 16 XI Seldon 17 XII SparseLib++ 18 XIII Template Numerical Toolkit (TNT) 19 XIV Trilinos 20 1 XV uBlas 22 XVI Other Libraries 23 XVII Links and Benchmarks 25 1 Links 25 2 Benchmarks 25 2.1 Benchmarks for Linear Algebra Libraries . ....... 25 2.2 BenchmarksincludingSeldon . 26 2.2.1 BenchmarksforDenseMatrix. 26 2.2.2 BenchmarksforSparseMatrix . 29 XVIII Appendix 30 3 Flens Overloaded Operator Performance Compared to Seldon 30 4 Flens, Seldon and Trilinos Content Comparisons 32 4.1 Available Matrix Types from Blas (Flens and Seldon) . ........ 32 4.2 Available Interfaces to Blas and Lapack Routines (Flens and Seldon) . 33 4.3 Available Interfaces to Blas and Lapack Routines (Trilinos) ......... 40 5 Flens and Seldon Synoptic Comparison 41 2 Part I Requirements This document has been written to help in the choice of a linear algebra library to be included in Verdandi, a scientific library for data assimilation. The main requirements are 1. Portability: Verdandi should compile on BSD systems, Linux, MacOS, Unix and Windows. Beyond the portability itself, this often ensures that most compilers will accept Verdandi. An obvious consequence is that all dependencies of Verdandi must be portable, especially the linear algebra library. 2. High-level interface: the dependencies should be compatible with the building of the high-level interface (e. -
Technical Computing on the OS … That Is Not Linux! Or How to Leverage Everything You‟Ve Learned, on a Windows Box As Well
Tools of the trade: Technical Computing on the OS … that is not Linux! Or how to leverage everything you‟ve learned, on a Windows box as well Sean Mortazavi & Felipe Ayora Typical situation with TC/HPC folks Why I have a Windows box How I use it It was in the office when I joined Outlook / Email IT forced me PowerPoint I couldn't afford a Mac Excel Because I LIKE Windows! Gaming It's the best gaming machine Technical/Scientific computing Note: Stats completely made up! The general impression “Enterprise community” “Hacker community” Guys in suits Guys in jeans Word, Excel, Outlook Emacs, Python, gmail Run prepackaged stuff Builds/runs OSS stuff Common complaints about Windows • I have a Windows box, but Windows … • Is hard to learn… • Doesn‟t have a good shell • Doesn‟t have my favorite editor • Doesn‟t have my favorite IDE • Doesn‟t have my favorite compiler or libraries • Locks me in • Doesn‟t play well with OSS • …. • In summary: (More like ) My hope … • I have a Windows box, and Windows … • Is easy to learn… • Has excellent shells • Has my favorite editor • Supports my favorite IDE • Supports my compilers and libraries • Does not lock me in • Plays well with OSS • …. • In summary: ( or at least ) How? • Recreating a Unix like veneer over windows to minimize your learning curve • Leverage your investment in know how & code • Showing what key codes already run natively on windows just as well • Kicking the dev tires using cross plat languages Objective is to: Help you ADD to your toolbox, not take anything away from it! At a high level… • Cygwin • SUA • Windowing systems “The Unix look & feel” • Standalone shell/utils • IDE‟s • Editors General purpose development • Compilers / languages / Tools • make • Libraries • CAS environments Dedicated CAS / IDE‟s And if there is time, a couple of demos… Cygwin • What is it? • A Unix like environment for Windows. -
User Guide for CHOLMOD: a Sparse Cholesky Factorization and Modification Package
User Guide for CHOLMOD: a sparse Cholesky factorization and modification package Timothy A. Davis [email protected], http://www.suitesparse.com VERSION 3.0.14, Oct 22, 2019 Abstract CHOLMOD1 is a set of routines for factorizing sparse symmetric positive definite matrices of the form A or AAT, updating/downdating a sparse Cholesky factorization, solving linear systems, updating/downdating the solution to the triangular system Lx = b, and many other sparse matrix functions for both symmetric and unsymmetric matrices. Its supernodal Cholesky factorization relies on LAPACK and the Level-3 BLAS, and obtains a substantial fraction of the peak performance of the BLAS. Both real and complex matrices are supported. It also includes a non-supernodal LDLT factorization method that can factorize symmetric indefinite matrices if all of their leading submatrices are well-conditioned (D is diagonal). CHOLMOD is written in ANSI/ISO C, with both C and MATLAB interfaces. This code works on Microsoft Windows and many versions of Unix and Linux. CHOLMOD Copyright c 2005-2015 by Timothy A. Davis. Portions are also copyrighted by William W. Hager (the Modify Module), and the University of Florida (the Partition and Core Modules). All Rights Reserved. See CHOLMOD/Doc/License.txt for the license. CHOLMOD is also available under other licenses that permit its use in proprietary applications; contact the authors for details. See http://www.suitesparse.com for the code and all documentation, including this User Guide. 1CHOLMOD is short for CHOLesky MODification, since a key feature of the package is its ability to up- date/downdate a sparse Cholesky factorization 1 Contents 1 Overview 8 2 Primary routines and data structures 9 3 Simple example program 11 4 Installation of the C-callable library 12 5 Using CHOLMOD in MATLAB 15 5.1 analyze: order and analyze . -
Latexsample-Thesis
INTEGRAL ESTIMATION IN QUANTUM PHYSICS by Jane Doe A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Mathematics The University of Utah May 2016 Copyright c Jane Doe 2016 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Jane Doe has been approved by the following supervisory committee members: Cornelius L´anczos , Chair(s) 17 Feb 2016 Date Approved Hans Bethe , Member 17 Feb 2016 Date Approved Niels Bohr , Member 17 Feb 2016 Date Approved Max Born , Member 17 Feb 2016 Date Approved Paul A. M. Dirac , Member 17 Feb 2016 Date Approved by Petrus Marcus Aurelius Featherstone-Hough , Chair/Dean of the Department/College/School of Mathematics and by Alice B. Toklas , Dean of The Graduate School. ABSTRACT Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. -
Apple File System Reference
Apple File System Reference Developer Contents About Apple File System 7 General-Purpose Types 9 paddr_t .................................................. 9 prange_t ................................................. 9 uuid_t ................................................... 9 Objects 10 obj_phys_t ................................................ 10 Supporting Data Types ........................................... 11 Object Identifier Constants ......................................... 12 Object Type Masks ............................................. 13 Object Types ................................................ 14 Object Type Flags .............................................. 20 EFI Jumpstart 22 Booting from an Apple File System Partition ................................. 22 nx_efi_jumpstart_t ........................................... 24 Partition UUIDs ............................................... 25 Container 26 Mounting an Apple File System Partition ................................... 26 nx_superblock_t ............................................. 27 Container Flags ............................................... 36 Optional Container Feature Flags ...................................... 37 Read-Only Compatible Container Feature Flags ............................... 38 Incompatible Container Feature Flags .................................... 38 Block and Container Sizes .......................................... 39 nx_counter_id_t ............................................. 39 checkpoint_mapping_t ........................................ -
Cobol Pic Clause Z
Cobol Pic Clause Z Johny never assembles any guereza gatings fallalishly, is Herby deepening and campodeiform enough? Scotch and apetalous Alister never gorgonise his Queenstown! Cybernetic and pleasurable Tyler often salvaged some chalkstones incorruptibly or whoop forkedly. If statement multiplies numeric character variables let us know, cobol output does include fully used state of cobol pic clause z is pic is not to. There maintain some basic guidelines which cab be applied in board to despite the code more readable and easier to maintain. It is counted toward the size of course item. In cobol blank spaces are delivered in a program use indicators is. How this face Telephone Interview? The pic g datatype is within embedded sql must use nextval stores data without knowing the pic clause apply to be applied in the constituent data. The S indicates that entity sign value might be maintained at the leftmost byte position. CHARF, trailing blanks are never stripped. 9 Write a program to illustrate the Edit a clause Z CRDB. If it contained two clauses based on pic clause in a superclass of coding have used. The V in which PICTURE indicates that when processing the computer will establish that there possess a decimal point in stock position. McCloskey's notes on COBOL DATA DIVISION. The length component is assumed to duration the length of the slash in characters, not bytes. If a sending field has PIC 94V99 with value 0012 34 to print this as bbb1234 the future-item must have chain of both following PIC clauses ZZZ999. Special logic for parsing Unicode strings. -
Gnucobol: a Gnu Life for an Old Workhorse
GnuCOBOL: A Gnu Life for an Old Workhorse Linux Users of Victoria, July 16, 2016 [email protected] A Brief History of COBOL COBOL (COmmon Business-Oriented Language) is a compiled, imperative, procedural, and (in recent versions) object-orientated language. It was first designed in 1959 by the near-legendary Rear Admiral Grace Hooper (first programmer of the Harvard Mark I in 1944, who invented the first compiler (for the A-0 programming language) in 1951, developed first machine-independent program, original developer of COBOL). Many implementations of COBOL, and several standards; ANSI COBOL 1968 (became ISO in 1972), 1974 (file organisation, segmentation module), 1980 (abandoned after extensive criticism), 1985, 2002 (with object-orientated support), and 2014 (adopted IEEE 754 standard for floating point computation). Features, Issues, and Opportunities COBOL has an English-like syntax, making it easy to learn, but it appears verbose. Program structures are expressed in statements rather than blocks, it has no error checking on subroutine calls. It lacks standard libraries (resulting in c300 reserved words), and poor consistency among its many dialects. However it has excellent screen support, decimal arithmetic, and good performance. Modern versions do have built-in XML support and support for OOP. COBOL is disliked by many because it's a domain-specific language (business, finance, and administration for large companies and government = lots of data crunching), and it was relatively isolated from computer science as a discipline. Features, Issues, and Opportunities Not taught extensively at universities. "The use of COBOL cripples the mind; its teaching should, therefore, be regarded as a criminal offense." (Edsger Dijkstra, 1975). -
Integral Estimation in Quantum Physics
INTEGRAL ESTIMATION IN QUANTUM PHYSICS by Jane Doe A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematical Physics Department of Mathematics The University of Utah May 2016 Copyright c Jane Doe 2016 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Jane Doe has been approved by the following supervisory committee members: Cornelius L´anczos , Chair(s) 17 Feb 2016 Date Approved Hans Bethe , Member 17 Feb 2016 Date Approved Niels Bohr , Member 17 Feb 2016 Date Approved Max Born , Member 17 Feb 2016 Date Approved Paul A. M. Dirac , Member 17 Feb 2016 Date Approved by Petrus Marcus Aurelius Featherstone-Hough , Chair/Dean of the Department/College/School of Mathematics and by Alice B. Toklas , Dean of The Graduate School. ABSTRACT Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. -
CALENDAR SIG = Special Interest Group
November 2017 Visit our website at www.pcs4me.com Ken Johnson, Newsletter Editor CALENDAR SIG = Special Interest Group This Week's Schedule November 11 - Saturday - 1:10-2:50 PM General Meeting - Leader: Ray Carlson Location: Prescott Public Library; Founders Suite A & B First Hour: Software Updates in Protective Categories Ray Carlson will discuss how any good software is regularly updated to eliminate bugs but also to add new features. He will look at some of the new features in certain types of software. The discussion will be limited to software that is free and highly recommended. Topics included will be recovering lost data and files, password managers, and newer antivirus programs. Second Hour: Phil Ball will present Tips and Tricks with insights into various topics that assist with regular computer activity. In addition to the presentations, the following are typical events which take place at our General meet- ings: 1) We hold an informal Flea Market in which you are encouraged to bring in your excess computer equip- ment or software and make them available for others to enjoy at no charge. Please deposit give-away items on the table in the back marked "Free Stuff." Any items left here at the end of the meeting are subject to dis- posal. 2) If you have items that are just too good to give away, you may set up a separate table and hold your own sale. 3) We conduct a raffle of gift cards at the end of the meeting, so make sure to get a pair of tickets from who- ever is in charge and place one on the item you'd like to win. -
Automatic Performance Tuning of Sparse Matrix Kernels
Automatic Performance Tuning of Sparse Matrix Kernels by Richard Wilson Vuduc B.S. (Cornell University) 1997 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor James W. Demmel, Chair Professor Katherine A. Yelick Professor Sanjay Govindjee Fall 2003 The dissertation of Richard Wilson Vuduc is approved: Chair Date Date Date University of California, Berkeley Fall 2003 Automatic Performance Tuning of Sparse Matrix Kernels Copyright 2003 by Richard Wilson Vuduc 1 Abstract Automatic Performance Tuning of Sparse Matrix Kernels by Richard Wilson Vuduc Doctor of Philosophy in Computer Science University of California, Berkeley Professor James W. Demmel, Chair This dissertation presents an automated system to generate highly efficient, platform- adapted implementations of sparse matrix kernels. These computational kernels lie at the heart of diverse applications in scientific computing, engineering, economic modeling, and information retrieval, to name a few. Informally, sparse kernels are computational oper- ations on matrices whose entries are mostly zero, so that operations with and storage of these zero elements may be eliminated. The challenge in developing high-performance im- plementations of such kernels is choosing the data structure and code that best exploits the structural properties of the matrix|generally unknown until application run-time|for high-performance on the underlying machine architecture (e.g., memory hierarchy con- figuration and CPU pipeline structure). We show that conventional implementations of important sparse kernels like sparse matrix-vector multiply (SpMV) have historically run at 10% or less of peak machine speed on cache-based superscalar architectures. -
Gnucobol Grammar
The GnuCOBOL 3.2-early-dev Grammar for r3407 Edward Hart [email protected] December 27, 2019 COBOL is an industry language and is not the property of any company or group of companies, or of any organisation or group of organisations. No warranty, expressed or implied, is made by any contributor, or by the CODASYL COBOL Committee,1 as to the accuracy and functioning of the programming system and language. Moreover, no responsibility is assumed by any contributor, or by the com- mittee, in connection therewith. The authors and copyright holders of the copyrighted materials used herein are: • FLOW-MATIC [trademark of Sperry Rand Corporation] Programming for the UNI- VAC ® I and II Data Automation Systems, copyrighted 1958, 1959 by Sperry Rand Corporation,2 • IBM Commercial Translator, Form No. F28-8013, copyrighted 1959 by IBM, and • FACT, DSI 27A5260-2760, copyrighted 1960 by Minneapolis-Honeywell. They have specially authorised the use of this material, in whole or in part, in the COBOL specifications. Such authorisation extends to the reproduction and use of COBOL specifications in programming manuals or similar publications. This work is typeset in Roboto. Copyright © 2019 Edward Hart Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. Your attention is drawn to the copy of the license in AppendixA. The moral rights of the author have been asserted.