Easybuild: Building Software with Ease
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Free and Open Source Software for Computational Chemistry Education
Free and Open Source Software for Computational Chemistry Education Susi Lehtola∗,y and Antti J. Karttunenz yMolecular Sciences Software Institute, Blacksburg, Virginia 24061, United States zDepartment of Chemistry and Materials Science, Aalto University, Espoo, Finland E-mail: [email protected].fi Abstract Long in the making, computational chemistry for the masses [J. Chem. Educ. 1996, 73, 104] is finally here. We point out the existence of a variety of free and open source software (FOSS) packages for computational chemistry that offer a wide range of functionality all the way from approximate semiempirical calculations with tight- binding density functional theory to sophisticated ab initio wave function methods such as coupled-cluster theory, both for molecular and for solid-state systems. By their very definition, FOSS packages allow usage for whatever purpose by anyone, meaning they can also be used in industrial applications without limitation. Also, FOSS software has no limitations to redistribution in source or binary form, allowing their easy distribution and installation by third parties. Many FOSS scientific software packages are available as part of popular Linux distributions, and other package managers such as pip and conda. Combined with the remarkable increase in the power of personal devices—which rival that of the fastest supercomputers in the world of the 1990s—a decentralized model for teaching computational chemistry is now possible, enabling students to perform reasonable modeling on their own computing devices, in the bring your own device 1 (BYOD) scheme. In addition to the programs’ use for various applications, open access to the programs’ source code also enables comprehensive teaching strategies, as actual algorithms’ implementations can be used in teaching. -
Nix on SHARCNET
Nix on SHARCNET Tyson Whitehead May 14, 2015 Nix Overview An enterprise approach to package management I a package is a specific piece of code compiled in a specific way I each package is entirely self contained and does not change I each users select what packages they want and gets a custom enviornment https://nixos.org/nix Ships with several thousand packages already created https://nixos.org/nixos/packages.html SHARCNET What this adds to SHARCNET I each user can have their own custom environments I environments should work everywhere (closed with no external dependencies) I several thousand new and newer packages Current issues (first is permanent, second will likely be resolved) I newer glibc requires kernel 2.6.32 so no requin I package can be used but not installed/removed on viz/vdi https: //sourceware.org/ml/libc-alpha/2014-01/msg00511.html Enabling Nix Nix is installed under /home/nixbld on SHARCNET. Enable for a single sessiong by running source /home/nixbld/profile.d/nix-profile.sh To always enable add this to the end of ~/.bash_profile echo source /home/nixbld/profile.d/nix-profile.sh \ >> ~/.bash_profile Reseting Nix A basic reset is done by removing all .nix* files from your home directory rm -fr ~/.nix* A complete reset done by remove your Nix per-user directories rm -fr /home/nixbld/var/nix/profile/per-user/$USER rm -fr /home/nixbld/var/nix/gcroots/per-user/$USER The nix-profile.sh script will re-create these with the defaults next time it runs. Environment The nix-env commands maintains your environments I query packages (available and installed) I create a new environment from current one by adding packages I create a new environment from current one by removing packages I switching between existing environments I delete unused environements Querying Packages The nix-env {--query | -q} .. -
User Manual for the Uppsala Quantum Chemistry Package UQUANTCHEM V.35
User manual for the Uppsala Quantum Chemistry package UQUANTCHEM V.35 by Petros Souvatzis Uppsala 2016 Contents 1 Introduction 6 2 Compiling the code 7 3 What Can be done with UQUANTCHEM 9 3.1 Hartree Fock Calculations . 9 3.2 Configurational Interaction Calculations . 9 3.3 M¨ollerPlesset Calculations (MP2) . 9 3.4 Density Functional Theory Calculations (DFT)) . 9 3.5 Time Dependent Density Functional Theory Calculations (TDDFT)) . 10 3.6 Quantum Montecarlo Calculations . 10 3.7 Born Oppenheimer Molecular Dynamics . 10 4 Setting up a UQANTCHEM calculation 12 4.1 The input files . 12 4.1.1 The INPUTFILE-file . 12 4.1.2 The BASISFILE-file . 13 4.1.3 The BASISFILEAUX-file . 14 4.1.4 The DENSMATSTARTGUESS.dat-file . 14 4.1.5 The MOLDYNRESTART.dat-file . 14 4.1.6 The INITVELO.dat-file . 15 4.1.7 Running Uquantchem . 15 4.2 Input parameters . 15 4.2.1 CORRLEVEL ................................. 15 4.2.2 ADEF ..................................... 15 4.2.3 DOTDFT ................................... 16 4.2.4 NSCCORR ................................... 16 4.2.5 SCERR .................................... 16 4.2.6 MIXTDDFT .................................. 16 4.2.7 EPROFILE .................................. 16 4.2.8 DOABSSPECTRUM ............................... 17 4.2.9 NEPERIOD .................................. 17 4.2.10 EFIELDMAX ................................. 17 4.2.11 EDIR ..................................... 17 4.2.12 FIELDDIR .................................. 18 4.2.13 OMEGA .................................... 18 2 CONTENTS 3 4.2.14 NCHEBGAUSS ................................. 18 4.2.15 RIAPPROX .................................. 18 4.2.16 LIMPRECALC (Only openmp-version) . 19 4.2.17 DIAGDG ................................... 19 4.2.18 NLEBEDEV .................................. 19 4.2.19 MOLDYN ................................... 19 4.2.20 DAMPING ................................... 19 4.2.21 XLBOMD .................................. -
Python Tools in Computational Chemistry (And Biology)
Python Tools in Computational Chemistry (and Biology) Andrew Dalke Dalke Scientific, AB Göteborg, Sweden EuroSciPy, 26-27 July, 2008 “Why does ‘import numpy’ take 0.4 seconds? Does it need to import 228 libraries?” - My first Numpy-discussion post (paraphrased) Your use case isn't so typical and so suffers on the import time end of the balance. - Response from Robert Kern (Others did complain. Import time down to 0.28s.) 52,000 structures PDB doubles every 2½ years HEADER PHOTORECEPTOR 23-MAY-90 1BRD 1BRD 2 COMPND BACTERIORHODOPSIN 1BRD 3 SOURCE (HALOBACTERIUM $HALOBIUM) 1BRD 4 EXPDTA ELECTRON DIFFRACTION 1BRD 5 AUTHOR R.HENDERSON,J.M.BALDWIN,T.A.CESKA,F.ZEMLIN,E.BECKMANN, 1BRD 6 AUTHOR 2 K.H.DOWNING 1BRD 7 REVDAT 3 15-JAN-93 1BRDB 1 SEQRES 1BRDB 1 REVDAT 2 15-JUL-91 1BRDA 1 REMARK 1BRDA 1 .. ATOM 54 N PRO 8 20.397 -15.569 -13.739 1.00 20.00 1BRD 136 ATOM 55 CA PRO 8 21.592 -15.444 -12.900 1.00 20.00 1BRD 137 ATOM 56 C PRO 8 21.359 -15.206 -11.424 1.00 20.00 1BRD 138 ATOM 57 O PRO 8 21.904 -15.930 -10.563 1.00 20.00 1BRD 139 ATOM 58 CB PRO 8 22.367 -14.319 -13.591 1.00 20.00 1BRD 140 ATOM 59 CG PRO 8 22.089 -14.564 -15.053 1.00 20.00 1BRD 141 ATOM 60 CD PRO 8 20.647 -15.054 -15.103 1.00 20.00 1BRD 142 ATOM 61 N GLU 9 20.562 -14.211 -11.095 1.00 20.00 1BRD 143 ATOM 62 CA GLU 9 20.192 -13.808 -9.737 1.00 20.00 1BRD 144 ATOM 63 C GLU 9 19.567 -14.935 -8.932 1.00 20.00 1BRD 145 ATOM 64 O GLU 9 19.815 -15.104 -7.724 1.00 20.00 1BRD 146 ATOM 65 CB GLU 9 19.248 -12.591 -9.820 1.00 99.00 1 1BRD 147 ATOM 66 CG GLU 9 19.902 -11.351 -10.387 1.00 99.00 1 1BRD 148 ATOM 67 CD GLU 9 19.243 -10.169 -10.980 1.00 99.00 1 1BRD 149 ATOM 68 OE1 GLU 9 18.323 -10.191 -11.782 1.00 99.00 1 1BRD 150 ATOM 69 OE2 GLU 9 19.760 -9.089 -10.597 1.00 99.00 1 1BRD 151 ATOM 70 N TRP 10 18.764 -15.737 -9.597 1.00 20.00 1BRD 152 ATOM 71 CA TRP 10 18.034 -16.884 -9.090 1.00 20.00 1BRD 153 ATOM 72 C TRP 10 18.843 -17.908 -8.318 1.00 20.00 1BRD 154 ATOM 73 O TRP 10 18.376 -18.310 -7.230 1.00 20.00 1BRD 155 . -
Downloads." the Open Information Security Foundation
Performance Testing Suricata The Effect of Configuration Variables On Offline Suricata Performance A Project Completed for CS 6266 Under Jonathon T. Giffin, Assistant Professor, Georgia Institute of Technology by Winston H Messer Project Advisor: Matt Jonkman, President, Open Information Security Foundation December 2011 Messer ii Abstract The Suricata IDS/IPS engine, a viable alternative to Snort, has a multitude of potential configurations. A simplified automated testing system was devised for the purpose of performance testing Suricata in an offline environment. Of the available configuration variables, seventeen were analyzed independently by testing in fifty-six configurations. Of these, three variables were found to have a statistically significant effect on performance: Detect Engine Profile, Multi Pattern Algorithm, and CPU affinity. Acknowledgements In writing the final report on this endeavor, I would like to start by thanking four people who made this project possible: Matt Jonkman, President, Open Information Security Foundation: For allowing me the opportunity to carry out this project under his supervision. Victor Julien, Lead Programmer, Open Information Security Foundation and Anne-Fleur Koolstra, Documentation Specialist, Open Information Security Foundation: For their willingness to share their wisdom and experience of Suricata via email for the past four months. John M. Weathersby, Jr., Executive Director, Open Source Software Institute: For allowing me the use of Institute equipment for the creation of a suitable testing -
FFV1, Matroska, LPCM (And More)
MediaConch Implementation and policy checking on FFV1, Matroska, LPCM (and more) Jérôme Martinez, MediaArea Innovation Workshop ‑ March 2017 What is MediaConch? MediaConch is a conformance checker Implementation checker Policy checker Reporter Fixer What is MediaConch? Implementation and Policy reporter What is MediaConch? Implementation report: Policy report: What is MediaConch? General information about your files What is MediaConch? Inspect your files What is MediaConch? Policy editor What is MediaConch? Public policies What is MediaConch? Fixer Segment sizes in Matroska Matroska “bit flip” correction FFV1 “bit flip” correction Integration Archivematica is an integrated suite of open‑source software tools that allows users to process digital objects from ingest to access in compliance with the ISO‑OAIS functional model MediaConch interfaces Graphical interface Web interface Command line Server (REST API) (Work in progress) a library (.dll/.so/.dylib) MediaConch output formats XML (native format) Text HTML (Work in progress) PDF Tweakable! (with XSL) Open source GPLv3+ and MPLv2+ Relies on MediaInfo (metadata extraction tool) Use well‑known open source libraries: Qt, sqlite, libevent, libxml2, libxslt, libexslt... Supported formats Priorities for the implementation checker Matroska FFV1 PCM Can accept any format supported by MediaInfo for the policy checker MXF + JP2k QuickTime/MOV Audio files (WAV, BWF, AIFF...) ... Supported formats Can be expanded By plugins Support of PDF checker: VeraPDF plugin Support of TIFF checker: DPF Manager plugin You use another checker? Let us know By internal development More tests on your preferred format is possible It depends on you! Versatile Several input formats are accepted FFV1 from MOV or AVI Matroska with other video formats (Work in progress) Extraction of a PDF or TIFF aachement from a Matroska container and analyze with a plugin (e.g. -
Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers
1 Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers Mukelabai Mukelabai, Stefan Strüder, Daniel Strüber, Thorsten Berger Abstract—Software defects are a major nuisance in software development and can lead to considerable financial losses or reputation damage for companies. To this end, a large number of techniques for predicting software defects, largely based on machine learning methods, has been developed over the past decades. These techniques usually rely on code-structure and process metrics to predict defects at the granularity of typical software assets, such as subsystems, components, and files. In this paper, we systematically investigate feature-oriented defect prediction: predicting defects at the granularity of features—domain-entities that abstractly represent software functionality and often cross-cut software assets. Feature-oriented prediction can be beneficial, since: (i) particular features might be more error-prone than others, (ii) characteristics of features known as defective might be useful to predict other error-prone features, and (iii) feature-specific code might be especially prone to faults arising from feature interactions. We explore the feasibility and solution space for feature-oriented defect prediction. We design and investigate scenarios, metrics, and classifiers. Our study relies on 12 software projects from which we analyzed 13,685 bug-introducing and corrective commits, and systematically generated 62,868 training and test datasets to evaluate the designed classifiers, metrics, and scenarios. The datasets were generated based on the 13,685 commits, 81 releases, and 24, 532 permutations of our 12 projects depending on the scenario addressed. We covered scenarios, such as just-in-time (JIT) and cross-project defect prediction. -
Creating Custom Debian Live for USB FD with Encrypted Persistence
Creating Custom Debian Live for USB FD with Encrypted Persistence INTRO Debian is a free operating system (OS) for your computer. An operating system is the set of basic programs and utilities that make your computer run. Debian provides more than a pure OS: it comes with over 43000 packages, precompiled software bundled up in a nice format for easy installation on your machine. PRE-REQ * Debian distro installed * Free Disk Space (Depends on you) Recommended Free Space >20GB * Internet Connection Fast * USB Flash Drive atleast 4GB Installing Required Softwares on your distro: Open Root Terminal or use sudo: $ sudo apt-get install debootstrap syslinux squashfs-tools genisoimage memtest86+ rsync apt-cacher-ng live-build live-config live-boot live-boot-doc live-config-doc live-manual live-tools live-manual-pdf qemu-kvm qemu-utils virtualbox virtualbox-qt virtualbox-dkms p7zip-full gparted mbr dosfstools parted Configuring APT Proxy Server (to save bandwidth) Start apt-cacher-ng service if not running # service apt-cacher-ng start Edit /etc/apt/sources.list with your favorite text editor. Terminal # nano /etc/apt/sources.list Output: (depends on your APT Mirror configuration) deb http://security.debian.org/ jessie/updates main contrib non-free deb http://http.debian.org/debian jessie main contrib non-free deb http://ftp.debian.org/debian jessie main contrib non-free Add “localhost:3142” : deb http://localhost:3142/security.debian.org/ jessie/updates main contrib non-free deb http://localhost:3142/http.debian.org/debian jessie main contrib non-free deb http://localhost:3142/ftp.debian.org/debian jessie main contrib non-free Press Ctrl + X and Y to save changes Terminal # apt-get update # apt-get upgrade NOTE: BUG in Debian Live. -
Release 0.11 Todd Gamblin
Spack Documentation Release 0.11 Todd Gamblin Feb 07, 2018 Basics 1 Feature Overview 3 1.1 Simple package installation.......................................3 1.2 Custom versions & configurations....................................3 1.3 Customize dependencies.........................................4 1.4 Non-destructive installs.........................................4 1.5 Packages can peacefully coexist.....................................4 1.6 Creating packages is easy........................................4 2 Getting Started 7 2.1 Prerequisites...............................................7 2.2 Installation................................................7 2.3 Compiler configuration..........................................9 2.4 Vendor-Specific Compiler Configuration................................ 13 2.5 System Packages............................................. 16 2.6 Utilities Configuration.......................................... 18 2.7 GPG Signing............................................... 20 2.8 Spack on Cray.............................................. 21 3 Basic Usage 25 3.1 Listing available packages........................................ 25 3.2 Installing and uninstalling........................................ 42 3.3 Seeing installed packages........................................ 44 3.4 Specs & dependencies.......................................... 46 3.5 Virtual dependencies........................................... 50 3.6 Extensions & Python support...................................... 53 3.7 Filesystem requirements........................................ -
Pyscf: the Python-Based Simulations of Chemistry Framework
PySCF: The Python-based Simulations of Chemistry Framework Qiming Sun∗1, Timothy C. Berkelbach2, Nick S. Blunt3,4, George H. Booth5, Sheng Guo1,6, Zhendong Li1, Junzi Liu7, James D. McClain1,6, Elvira R. Sayfutyarova1,6, Sandeep Sharma8, Sebastian Wouters9, and Garnet Kin-Lic Chany1 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena CA 91125, USA 2Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA 3Chemical Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA 4Department of Chemistry, University of California, Berkeley, California 94720, USA 5Department of Physics, King's College London, Strand, London WC2R 2LS, United Kingdom 6Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA 7Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, P. R. China 8Department of Chemistry and Biochemistry, University of Colorado Boulder, Boulder, CO 80302, USA 9Brantsandpatents, Pauline van Pottelsberghelaan 24, 9051 Sint-Denijs-Westrem, Belgium arXiv:1701.08223v2 [physics.chem-ph] 2 Mar 2017 Abstract PySCF is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible ∗[email protected] [email protected] 1 computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines. -
Skyfire: Data-Driven Seed Generation for Fuzzing
Skyfire: Data-Driven Seed Generation for Fuzzing Junjie Wang, Bihuan Chen†, Lei Wei, and Yang Liu Nanyang Technological University, Singapore {wang1043, bhchen, l.wei, yangliu}@ntu.edu.sg †Corresponding Author Abstract—Programs that take highly-structured files as inputs Syntax Semantic normally process inputs in stages: syntax parsing, semantic check- Features Rules ing, and application execution. Deep bugs are often hidden in the <?xml version="1.0" application execution stage, and it is non-trivial to automatically encoding="utf- pass pass pass 8"?><xsl:stylesheet version="1.0" Syntax Semantic Application xmlns:xsl="http://www.w3 .org/1999/XSL/Transform" generate test inputs to trigger them. Mutation-based fuzzing gen- ><xsl:output xsl:use- √ attribute- Parsing Checking Execution erates test inputs by modifying well-formed seed inputs randomly sets=""/></xsl:stylesheet> Parsing Semantic or heuristically. Most inputs are rejected at the early syntax pars- Inputs Crashes ing stage. Differently, generation-based fuzzing generates inputs Errors Violations from a specification (e.g., grammar). They can quickly carry the ! ! X fuzzing beyond the syntax parsing stage. However, most inputs fail to pass the semantic checking (e.g., violating semantic rules), Fig. 1: Stages of Processing Highly-Structured Inputs which restricts their capability of discovering deep bugs. In this paper, we propose a novel data-driven seed generation approach, named Skyfire, which leverages the knowledge in the analysis [8, 9] that identifies those interesting bytes to mutate, vast amount of existing samples to generate well-distributed seed symbolic execution [10, 11, 12] that relies on constraint solving inputs for fuzzing programs that process highly-structured inputs. -
Cisco ACE XML Gateway Installation and Administration Guide Software Version 5.1
Cisco ACE XML Gateway Installation and Administration Guide Software Version 5.1 Cisco Systems, Inc. | 170 West Tasman Drive | San Jose, CA 95134-1706 | 800 553-6387 THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS” WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE.IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. CCVP, the Cisco Logo, and the