Local stageout update

Size: px
Start display at page:

Download "Local stageout update"

Transcription

1 Local stageout update Subir Sarkar, Frank Würthwein, Johannes Mülmenstädt August 9, 2010

2 Big picture Local stageout requires the following pieces to be viable end-to-end: CRAB support (see Subir 7/26/2010) Proper permissions at sites (see Subir 7/26/2010) Enough space and automated cleanup at sites An offline tool to do the local stageout recovery (this talk) Local stageout update 1

3 Why do we believe this will help? J. Letts tested the entire matrix of T2 T2 connections for 3rd party transfers some time ago. He found that 10% of all connections failed on a given day. He found that of those 10%, again 10% failed when tried the next day. We thus hypothesize that user level retry of the stageout can bring the remote stageout error rate from 10% to 1% to 0.1%... via a simple set of successive tries within the one week that the sites are obliged to keep the local stageout files. This talk describes the tool we want to give to the users as part of the crab client deployment in order to do those retries as they see fit. Local stageout update 2

4 The tool The tool is a python script that will be distributed in the bin/ area of CRAB, starting with Logic behind the script: 1. Parse the fjr s in a CRAB project directory 2. If the remote stageout failed but local stageout succeeded (exit code 60308), figure out the PFN at the local site and the intended PFN at the remote site 3. Attempt an lcg-cp from the local to the remote site 4. If the copy succeeds, rewrite the fjr to indicate success and wrapper exit code 0 (keeping a backup of the fjr) 5. If any step fails, skip to the next fjr This program can be run iteratively, because on the next invocation it will only attempt to copy the failed files Parsing of fjr s, invocation of external commands etc. are all wrapped in error handling code so that if something goes wrong, the error is reported (and nothing bad is done to the fjr) Local stageout update 3

5 Invocation Basic usage message is printed if no arguments are given: [ jmuelmen ]. / r e t r y s t a g e o u t. py usage : r e t r y s t a g e o u t. py c <crab d i r e c t o r y > [ dry run n ] [ q u i e t q ] [ v e r b o s e v vv vvv ] Supported arguments: c (Mandatory) CRAB project directory to parse dry run, n Do not copy anything, only print a list of local PFN s that need to be copied quiet, q Print only error messages or the list of PFN s produced by n verbose, v, vv, vvv Be verbose. The first level of verbosity prints what the program is doing and whether external commands succeeded; second level also prints the output of external commands; third level runs the external commands in verbose mode, if available Local stageout update 4

6 Example: normal-verbosity, with a single failed job [ jmuelmen ]. / r e t r y s t a g e o u t. py c ttw madgraph Spring10 START3X V26 S09 v1 r e t r y s t a g e o u t. py : p r o c e s s i n g f j r ttw madgraph Spring10 START3X V26 S09 v1 / r e s / c r a b f j r 6. xml r e t r y s t a g e o u t. py : f j r ttw madgraph Spring10 START3X V26 S09 v1 / r e s / c r a b f j r 6. xml i n d i c a t e s remote s t a g e out f a i l u r e with l o c a l copy r e t r y s t a g e o u t. py : c o p y i n g from l o c a l : srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ phedex / s t o r e /temp/ u s e r / jmuelmen / c r a b t e s t i n g 2 / n t u p l e 6 1. r o o t to remote : srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ s t o r e / u s e r / jmuelmen / c r a b t e s t i n g 2 / n t u p l e 6 1. r o o t r e t r y s t a g e o u t. py : r e w r i t i n g f j r to i n d i c a t e remote s t a g e o u t s u c c e s s r e t r y s t a g e o u t. py : backup path i s ttw madgraph Spring10 START3X V26 S09 v1 / r e s / r e t r y b a c k u p r e t r y s t a g e o u t. py : o l d f j r w i l l be backed up to ttw madgraph Spring10 START3X V26 S09 v1 / r e s / r e t r y b ackup / c r a b f j r 6. xml r e t r y s t a g e o u t. py : a l l f j r s p r o c e s s e d, e x i t i n g (The quiet version of that would have been no output at all, unless there had been an error.) Local stageout update 5

7 Example: a quiet dry run [ jmuelmen ]. / r e t r y s t a g e o u t. py n q c ttw madgraph Spring10 START3X V26 S09 v1 r e t r y s t a g e o u t. py : f i l e s t h a t need to be c o p i e d : srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ phedex / s t o r e /temp/ u s e r / jmuelmen / c r a b t e s t i n g 2 / n t u p l e 6 1. r o o t Since no error occurred, the only output is the list of PFN s that need to be copied Local stageout update 6

8 Example: extreme verbosity And we mean extreme... (note that -vvv also causes lcg-cp to become verbose, for example) Trying SURL srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ phedex / s t o r e /temp/ u s e r / jmuelmen / c r [ jmuelmen ]. / r e t r y s t a g e o u t. py vvv c ttw madgraph Spring10 START3X V26 S09 v1 r e t r y s t a g e o u t. py : e x e c u t i n g command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / nodes r e t r y s t a g e o u t. py : command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / nodes e x i t s t a t r e t r y s t a g e o u t. py : command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / nodes output : < r e t r y s t a g e o u t. py : e x e c u t i n g command : / b i n / l s ttw madgraph Spring10 START3X V26 S09 v1 / r e s /. xml r e t r y s t a g e o u t. py : command : / b i n / l s ttw madgraph Spring10 START3X V26 S09 v1 / r e s /. xml e x i t s t a t u s : 0 r e t r y s t a g e o u t. py : command : / b i n / l s ttw madgraph Spring10 START3X V26 S09 v1 / r e s /. xml output : ttw m r e t r y s t a g e o u t. py : p r o c e s s i n g f j r ttw madgraph Spring10 START3X V26 S09 v1 / r e s / c r a b f j r 6. xml r e t r y s t a g e o u t. py : f j r ttw madgraph Spring10 START3X V26 S09 v1 / r e s / c r a b f j r 6. xml i n d i c a t e s remote s t a g e o r e t r y s t a g e o u t. py : l o c a l s t a g e o u t nodename = T2 US UCSD r e t r y s t a g e o u t. py : e x e c u t i n g command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / l f n 2 p f n? n r e t r y s t a g e o u t. py : command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / l f n 2 p f n? node=t r e t r y s t a g e o u t. py : command : wget O q h t t p : / / cmsweb. c e r n. ch / phedex / d a t a s v c / xml / prod / l f n 2 p f n? node=t r e t r y s t a g e o u t. py : e x e c u t i n g command : grep e x p o r t e n d p o i n t = ttw madgraph Spring10 START3X V26 S09 v1 / j o b r e t r y s t a g e o u t. py : command : grep e x p o r t e n d p o i n t = ttw madgraph Spring10 START3X V26 S09 v1 / j o b /CMSS r e t r y s t a g e o u t. py : command : grep e x p o r t e n d p o i n t = ttw madgraph Spring10 START3X V26 S09 v1 / j o b /CMSS r e t r y s t a g e o u t. py : c o p y i n g from l o c a l : srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ phedex / r e t r y s t a g e o u t. py : e x e c u t i n g command : lcg cp v D srmv2 srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/ r e t r y s t a g e o u t. py : command : lcg cp v D srmv2 srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoo r e t r y s t a g e o u t. py : command : lcg cp v D srmv2 srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoo Using g r i d c a t a l o g : prod l f c shared c e n t r a l. c e r n. ch VO name : cms Checksum type : None Source SE type : SRMv2 Source SRM Request Token : get : D e s t i n a t i o n SE type : SRMv2 D e s t i n a t i o n SRM Request Token : put : Source URL : srm : / / bsrm 1. t2. ucsd. edu :8443/ srm/v2 / s e r v e r?sfn=/hadoop /cms/ phedex / s t o r e /temp/ u s e r / jmuelmen / c r Local stageout update 7

9 Tests Various failure modes were tested on small sets of files missing permissions no proxy corrupted fjr s... and the like Every call to an external program is wrapped in error-checking code Error handling is simple: print the error message and skip to the next file In addition, the tool passed some stress tests over the weekend: MB ROOT files from MIT and Nebraska to Pisa GB ROOT files from UCSD to Pisa passed both tests Local stageout update 8

10 Conclusion We have developed a tool which can be used in conjunction with local stageout The tool copies files from the local to the remote SE if the fjr s indicate that remote stageout failed The tool is robust against failure at any of the various steps of the procedure It can be used incrementally to retry the copying of files that did not succeed on the previous pass It is ready for inclusion in CRAB Local stageout update 9

Lab 6: Linear Algebra

Lab 6: Linear Algebra 6.1 Introduction Lab 6: Linear Algebra This lab is aimed at demonstrating Python s ability to solve linear algebra problems. At the end of the assignment, you should be able to write code that sets up

More information

Clojure Concurrency Constructs, Part Two. CSCI 5828: Foundations of Software Engineering Lecture 13 10/07/2014

Clojure Concurrency Constructs, Part Two. CSCI 5828: Foundations of Software Engineering Lecture 13 10/07/2014 Clojure Concurrency Constructs, Part Two CSCI 5828: Foundations of Software Engineering Lecture 13 10/07/2014 1 Goals Cover the material presented in Chapter 4, of our concurrency textbook In particular,

More information

1 Opening URLs. 2 Regular Expressions. 3 Look Back. 4 Graph Theory. 5 Crawler / Spider

1 Opening URLs. 2 Regular Expressions. 3 Look Back. 4 Graph Theory. 5 Crawler / Spider 1 Opening URLs 2 Regular Expressions 3 Look Back 4 Graph Theory 5 Crawler / Spider Sandeep Sadanandan (TU, Munich) Python For Fine Programmers June 5, 2009 1 / 14 Opening URLs The module used for opening

More information

Data to Datafordeleren

Data to Datafordeleren Data to Datafordeleren Infrastructure, architecture and design FME World tour Copenhagen 21 May 2015 SIDE 1 Who am I Peter Laulund Certified FME professional since 2007 Works at Geodatastyrelsen - The

More information

Building a Lightweight High Availability Cluster Using RepMgr

Building a Lightweight High Availability Cluster Using RepMgr Building a Lightweight High Availability Cluster Using RepMgr Stephan Müller June 29, 2018 Schedule Introduction Postgres high availability options Write ahead log and streaming replication Built-in tools

More information

Presuppositions (introductory comments)

Presuppositions (introductory comments) 1 Presuppositions (introductory comments) Some examples (1) a. The person who broke the typewriter was Sam. b. It was Sam who broke the typewriter. c. John screwed up again. d. John likes Mary, too. e.

More information

Lecture 5. September 4, 2018 Math/CS 471: Introduction to Scientific Computing University of New Mexico

Lecture 5. September 4, 2018 Math/CS 471: Introduction to Scientific Computing University of New Mexico Lecture 5 September 4, 2018 Math/CS 471: Introduction to Scientific Computing University of New Mexico 1 Review: Office hours at regularly scheduled times this week Tuesday: 9:30am-11am Wed: 2:30pm-4:00pm

More information

Dynamics of the Atmosphere GEMPAK Lab 3. 3) In-class exercise about geostrophic balance in the real atmosphere.

Dynamics of the Atmosphere GEMPAK Lab 3. 3) In-class exercise about geostrophic balance in the real atmosphere. Dynamics of the Atmosphere GEMPAK Lab 3 Goals of this lab: 1) Learn about Linux scripts. 2) Learn how to combine levels in GEMPAK functions. 3) In-class exercise about geostrophic balance in the real atmosphere.

More information

A GUI FOR EVOLVE ZAMS

A GUI FOR EVOLVE ZAMS A GUI FOR EVOLVE ZAMS D. R. Schlegel Computer Science Department Here the early work on a new user interface for the Evolve ZAMS stellar evolution code is presented. The initial goal of this project is

More information

Scripting Languages Fast development, extensible programs

Scripting Languages Fast development, extensible programs Scripting Languages Fast development, extensible programs Devert Alexandre School of Software Engineering of USTC November 30, 2012 Slide 1/60 Table of Contents 1 Introduction 2 Dynamic languages A Python

More information

Chapter 1. Root Finding Methods. 1.1 Bisection method

Chapter 1. Root Finding Methods. 1.1 Bisection method Chapter 1 Root Finding Methods We begin by considering numerical solutions to the problem f(x) = 0 (1.1) Although the problem above is simple to state it is not always easy to solve analytically. This

More information

lightcurve Data Processing program v1.0

lightcurve Data Processing program v1.0 lightcurve Data Processing program v1.0 Build 8/22/2012 Using Lightcurve... 1 Lightcurve Command Line Parameters... 2 Lightcurve Outputs and Files... 3 Lightcurve Examples... 3 Data File Formats... 4 Lightcurve

More information

) (d o f. For the previous layer in a neural network (just the rightmost layer if a single neuron), the required update equation is: 2.

) (d o f. For the previous layer in a neural network (just the rightmost layer if a single neuron), the required update equation is: 2. 1 Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.034 Artificial Intelligence, Fall 2011 Recitation 8, November 3 Corrected Version & (most) solutions

More information

Abstract parsing: static analysis of dynamically generated string output using LR-parsing technology

Abstract parsing: static analysis of dynamically generated string output using LR-parsing technology Abstract parsing: static analysis of dynamically generated string output using LR-parsing technology Kyung-Goo Doh 1, Hyunha Kim 1, David A. Schmidt 2 1. Hanyang University, Ansan, South Korea 2. Kansas

More information

Monte Carlo Status. Bradley Yale. Spring 2017 Collaboration Meeting 05/04/2017

Monte Carlo Status. Bradley Yale. Spring 2017 Collaboration Meeting 05/04/2017 Monte Carlo Status Bradley Yale Spring 2017 Collaboration Meeting 05/04/2017 MC Status Summary MadGraph5 is now used for all tridents A more efficient background ( tritrig-wab-beam ) is available for acceptance/reach

More information

CS 124 Math Review Section January 29, 2018

CS 124 Math Review Section January 29, 2018 CS 124 Math Review Section CS 124 is more math intensive than most of the introductory courses in the department. You re going to need to be able to do two things: 1. Perform some clever calculations to

More information

Mathematical Logic Part One

Mathematical Logic Part One Mathematical Logic Part One Question: How do we formalize the defnitions and reasoning we use in our proofs? Where We're Going Propositional Logic (Today) Basic logical connectives. Truth tables. Logical

More information

Lecture 10: Gentzen Systems to Refinement Logic CS 4860 Spring 2009 Thursday, February 19, 2009

Lecture 10: Gentzen Systems to Refinement Logic CS 4860 Spring 2009 Thursday, February 19, 2009 Applied Logic Lecture 10: Gentzen Systems to Refinement Logic CS 4860 Spring 2009 Thursday, February 19, 2009 Last Tuesday we have looked into Gentzen systems as an alternative proof calculus, which focuses

More information

CS425: Algorithms for Web Scale Data

CS425: Algorithms for Web Scale Data CS425: Algorithms for Web Scale Data Most of the slides are from the Mining of Massive Datasets book. These slides have been modified for CS425. The original slides can be accessed at: www.mmds.org Challenges

More information

Overlay Transport Virtualization (OTV) Unicast-Mode Transport Infrastructure Deployment

Overlay Transport Virtualization (OTV) Unicast-Mode Transport Infrastructure Deployment Overlay Transport Virtualization (OTV) Unicast-Mode Transport Infrastructure Deployment July 24, 2012 ALL DESIGNS, SPECIFICATIONS, STATEMENTS, INFORMATION, AND RECOMMENDATIONS (COLLECTIVELY, "DESIGNS")

More information

Web GIS Deployment for Administrators. Vanessa Ramirez Solution Engineer, Natural Resources, Esri

Web GIS Deployment for Administrators. Vanessa Ramirez Solution Engineer, Natural Resources, Esri Web GIS Deployment for Administrators Vanessa Ramirez Solution Engineer, Natural Resources, Esri Agenda Web GIS Concepts Web GIS Deployment Patterns Components of an On-Premises Web GIS Federation of Server

More information

1 Recap: Interactive Proofs

1 Recap: Interactive Proofs Theoretical Foundations of Cryptography Lecture 16 Georgia Tech, Spring 2010 Zero-Knowledge Proofs 1 Recap: Interactive Proofs Instructor: Chris Peikert Scribe: Alessio Guerrieri Definition 1.1. An interactive

More information

COMS 6100 Class Notes

COMS 6100 Class Notes COMS 6100 Class Notes Daniel Solus September 20, 2016 1 General Remarks The Lecture notes submitted by the class have been very good. Integer division seemed to be a common oversight when working the Fortran

More information

Python. Tutorial. Jan Pöschko. March 22, Graz University of Technology

Python. Tutorial. Jan Pöschko. March 22, Graz University of Technology Tutorial Graz University of Technology March 22, 2010 Why? is: very readable easy to learn interpreted & interactive like a UNIX shell, only better object-oriented but not religious about it slower than

More information

MONTE CARLO METHODS IN SEQUENTIAL AND PARALLEL COMPUTING OF 2D AND 3D ISING MODEL

MONTE CARLO METHODS IN SEQUENTIAL AND PARALLEL COMPUTING OF 2D AND 3D ISING MODEL Journal of Optoelectronics and Advanced Materials Vol. 5, No. 4, December 003, p. 971-976 MONTE CARLO METHODS IN SEQUENTIAL AND PARALLEL COMPUTING OF D AND 3D ISING MODEL M. Diaconu *, R. Puscasu, A. Stancu

More information

ORBIT Code Review and Future Directions. S. Cousineau, A. Shishlo, J. Holmes ECloud07

ORBIT Code Review and Future Directions. S. Cousineau, A. Shishlo, J. Holmes ECloud07 ORBIT Code Review and Future Directions S. Cousineau, A. Shishlo, J. Holmes ECloud07 ORBIT Code ORBIT (Objective Ring Beam Injection and Transport code) ORBIT is an object-oriented, open-source code started

More information

Robert D. Borchert GIS Technician

Robert D. Borchert GIS Technician QA/QC: AM/FM: A Checklist Confirmed for fit Quality Methods and Control Actions Robert D. Borchert GIS Technician This just goes to show that QA/QC is important. Robert D. Borchert GIS Technician Did you

More information

Software Testing Lecture 2

Software Testing Lecture 2 Software Testing Lecture 2 Justin Pearson September 25, 2014 1 / 1 Test Driven Development Test driven development (TDD) is a way of programming where all your development is driven by tests. Write tests

More information

Exam 3, Math Fall 2016 October 19, 2016

Exam 3, Math Fall 2016 October 19, 2016 Exam 3, Math 500- Fall 06 October 9, 06 This is a 50-minute exam. You may use your textbook, as well as a calculator, but your work must be completely yours. The exam is made of 5 questions in 5 pages,

More information

Your Second Physics Simulation: A Mass on a Spring

Your Second Physics Simulation: A Mass on a Spring Your Second Physics Simulation: A Mass on a Spring I. INTRODUCTION At this point I think everybody has a working bouncing ball program. In these programs the ball moves under the influence of a very simple

More information

Appendix 4 Weather. Weather Providers

Appendix 4 Weather. Weather Providers Appendix 4 Weather Using weather data in your automation solution can have many benefits. Without weather data, your home automation happens regardless of environmental conditions. Some things you can

More information

MITOCW MITRES2_002S10nonlinear_lec05_300k-mp4

MITOCW MITRES2_002S10nonlinear_lec05_300k-mp4 MITOCW MITRES2_002S10nonlinear_lec05_300k-mp4 The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources

More information

from Euclid to Einstein

from Euclid to Einstein WorkBook 2. Space from Euclid to Einstein Roy McWeeny Professore Emerito di Chimica Teorica, Università di Pisa, Pisa (Italy) A Pari New Learning Publication Book 2 in the Series WorkBooks in Science (Last

More information

Coordination. Failures and Consensus. Consensus. Consensus. Overview. Properties for Correct Consensus. Variant I: Consensus (C) P 1. v 1.

Coordination. Failures and Consensus. Consensus. Consensus. Overview. Properties for Correct Consensus. Variant I: Consensus (C) P 1. v 1. Coordination Failures and Consensus If the solution to availability and scalability is to decentralize and replicate functions and data, how do we coordinate the nodes? data consistency update propagation

More information

Deep-dive into PyMISP MISP - Malware Information Sharing Platform & Threat Sharing

Deep-dive into PyMISP MISP - Malware Information Sharing Platform & Threat Sharing Deep-dive into PyMISP MISP - Malware Information Sharing Platform & Threat Sharing Team CIRCL http://www.misp-project.org/ Twitter: @MISPProject MISP Training @ Helsinki 20180423 Context MISP is complex

More information

Parameter identification of damage parameters of LS-DYNA GURSON material model from a tensile test. Lectures. Johannes Will

Parameter identification of damage parameters of LS-DYNA GURSON material model from a tensile test. Lectures. Johannes Will Lectures Parameter identification of damage parameters of LS-DYNA GURSON material model from a tensile test Johannes Will presented at the Weimar Optimization and Stochastic Days 2009 Source: www.dynardo.de/en/library

More information

COMP Assignment 1 Solutions

COMP Assignment 1 Solutions COMP 409 - Assignment 1 Solutions 1 Show that there are no formulas of length 2,3, or 6, but that every other length is possible. Let p, q and r be atomic propositions. Then p is a formula of length 1,

More information

Problem Decomposition: One Professor s Approach to Coding

Problem Decomposition: One Professor s Approach to Coding Problem Decomposition: One Professor s Approach to Coding zombie[1] zombie[3] Fewer Buuuuugs zombie[4] zombie[2] zombie[5] zombie[0] Fundamentals of Computer Science I Overview Problem Solving Understand

More information

COMP 204. Exceptions continued. Yue Li based on material from Mathieu Blanchette, Carlos Oliver Gonzalez and Christopher Cameron

COMP 204. Exceptions continued. Yue Li based on material from Mathieu Blanchette, Carlos Oliver Gonzalez and Christopher Cameron COMP 204 Exceptions continued Yue Li based on material from Mathieu Blanchette, Carlos Oliver Gonzalez and Christopher Cameron 1 / 27 Types of bugs 1. Syntax errors 2. Exceptions (runtime) 3. Logical errors

More information

MATERIAL MECHANICS, SE2126 COMPUTER LAB 3 VISCOELASTICITY. k a. N t

MATERIAL MECHANICS, SE2126 COMPUTER LAB 3 VISCOELASTICITY. k a. N t MATERIAL MECHANICS, SE2126 COMPUTER LAB 3 VISCOELASTICITY N t i Gt () G0 1 i ( 1 e τ = α ) i= 1 k a k b τ PART A RELAXING PLASTIC PAPERCLIP Consider an ordinary paperclip made of plastic, as they more

More information

GFC_DEFRAG: FREE SPACE DEFRAGMENTATION UTILITY PACKAGE

GFC_DEFRAG: FREE SPACE DEFRAGMENTATION UTILITY PACKAGE T E C H N I C A L N O T E GFC_DEFRAG: FREE SPACE DEFRAGMENTATION UTILITY PACKAGE Prepared By David Kurtz, Go-Faster Consultancy Ltd. Technical Note Version 1.01 Tuesday 5 February 2013 (E-mail: david.kurtz@go-faster.co.uk,

More information

Distributed Systems Principles and Paradigms

Distributed Systems Principles and Paradigms Distributed Systems Principles and Paradigms Chapter 6 (version April 7, 28) Maarten van Steen Vrije Universiteit Amsterdam, Faculty of Science Dept. Mathematics and Computer Science Room R4.2. Tel: (2)

More information

15-451/651: Design & Analysis of Algorithms September 13, 2018 Lecture #6: Streaming Algorithms last changed: August 30, 2018

15-451/651: Design & Analysis of Algorithms September 13, 2018 Lecture #6: Streaming Algorithms last changed: August 30, 2018 15-451/651: Design & Analysis of Algorithms September 13, 2018 Lecture #6: Streaming Algorithms last changed: August 30, 2018 Today we ll talk about a topic that is both very old (as far as computer science

More information

Hypothesis testing I. - In particular, we are talking about statistical hypotheses. [get everyone s finger length!] n =

Hypothesis testing I. - In particular, we are talking about statistical hypotheses. [get everyone s finger length!] n = Hypothesis testing I I. What is hypothesis testing? [Note we re temporarily bouncing around in the book a lot! Things will settle down again in a week or so] - Exactly what it says. We develop a hypothesis,

More information

Proof: If (a, a, b) is a Pythagorean triple, 2a 2 = b 2 b / a = 2, which is impossible.

Proof: If (a, a, b) is a Pythagorean triple, 2a 2 = b 2 b / a = 2, which is impossible. CS103 Handout 07 Fall 2013 October 2, 2013 Guide to Proofs Thanks to Michael Kim for writing some of the proofs used in this handout. What makes a proof a good proof? It's hard to answer this question

More information

NE 204 mini-syllabus (weeks 4 8)

NE 204 mini-syllabus (weeks 4 8) NE 24 mini-syllabus (weeks 4 8) Instructor: John Burke O ce: MCS 238 e-mail: jb@math.bu.edu o ce hours: by appointment Overview: For the next few weeks, we will focus on mathematical models of single neurons.

More information

Analysis of Planar Truss

Analysis of Planar Truss Analysis of Planar Truss Although the APES computer program is not a specific matrix structural code, it can none the less be used to analyze simple structures. In this example, the following statically

More information

Elite Galaxy Online. API Documentation v Elite Galaxy Online. All rights reserved

Elite Galaxy Online. API Documentation v Elite Galaxy Online. All rights reserved Elite Galaxy Online API Documentation v2.1 Contents 1. Version Control... 3 2. Overview of Elite Galaxy Online API... 4 3. Retrieving Data from Elite Galaxy Online... 5 3.1. Retrieving Star System Data...

More information

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich March 16, 2015

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich March 16, 2015 Nicola Chiapolini, March 16, 2015 1 / 31 git Tutorial Nicola Chiapolini Physik-Institut University of Zurich March 16, 2015 Based on talk by Emanuele Olivetti https://github.com/emanuele/introduction_to_git.git

More information

Replication cluster on MariaDB 5.5 / ubuntu-server. Mark Schneider ms(at)it-infrastrukturen(dot)org

Replication cluster on MariaDB 5.5 / ubuntu-server. Mark Schneider ms(at)it-infrastrukturen(dot)org Mark Schneider ms(at)it-infrastrukturen(dot)org 2012-05-31 Abstract Setting of MASTER-SLAVE or MASTER-MASTER replications on MariaDB 5.5 database servers is neccessary for higher availability of data and

More information

ArcGIS GeoAnalytics Server: An Introduction. Sarah Ambrose and Ravi Narayanan

ArcGIS GeoAnalytics Server: An Introduction. Sarah Ambrose and Ravi Narayanan ArcGIS GeoAnalytics Server: An Introduction Sarah Ambrose and Ravi Narayanan Overview Introduction Demos Analysis Concepts using GeoAnalytics Server GeoAnalytics Data Sources GeoAnalytics Server Administration

More information

Computability Crib Sheet

Computability Crib Sheet Computer Science and Engineering, UCSD Winter 10 CSE 200: Computability and Complexity Instructor: Mihir Bellare Computability Crib Sheet January 3, 2010 Computability Crib Sheet This is a quick reference

More information

CHEOPS Feasibility Checker Guidelines

CHEOPS Feasibility Checker Guidelines CHEOPS Feasibility Checker Guidelines Open a terminal and run the following commands (USERNAME as provided by the SOC - UNIGE): ssh X USERNAME@isdc-nx00.isdc.unige.ch ssh X USERNAME@tichpsmps00 /cheops_sw/mps_test/bin/mps_client

More information

How to write maths (well)

How to write maths (well) How to write maths (well) Dr Euan Spence 29 September 2017 These are the slides from a talk I gave to the new first-year students at Bath, annotated with some of the things I said (which appear in boxes

More information

Heuristic Alignment and Searching

Heuristic Alignment and Searching 3/28/2012 Types of alignments Global Alignment Each letter of each sequence is aligned to a letter or a gap (e.g., Needleman-Wunsch). Local Alignment An optimal pair of subsequences is taken from the two

More information

The following syntax is used to describe a typical irreducible continuum element:

The following syntax is used to describe a typical irreducible continuum element: ELEMENT IRREDUCIBLE T7P0 command.. Synopsis The ELEMENT IRREDUCIBLE T7P0 command is used to describe all irreducible 7-node enhanced quadratic triangular continuum elements that are to be used in mechanical

More information

Univariate Normal Distribution; GLM with the Univariate Normal; Least Squares Estimation

Univariate Normal Distribution; GLM with the Univariate Normal; Least Squares Estimation Univariate Normal Distribution; GLM with the Univariate Normal; Least Squares Estimation PRE 905: Multivariate Analysis Spring 2014 Lecture 4 Today s Class The building blocks: The basics of mathematical

More information

Lecture 4 Implementing material models: using usermat.f. Implementing User-Programmable Features (UPFs) in ANSYS ANSYS, Inc.

Lecture 4 Implementing material models: using usermat.f. Implementing User-Programmable Features (UPFs) in ANSYS ANSYS, Inc. Lecture 4 Implementing material models: using usermat.f Implementing User-Programmable Features (UPFs) in ANSYS 1 Lecture overview What is usermat.f used for? Stress, strain and material Jacobian matrix

More information

Communication Engineering Prof. Surendra Prasad Department of Electrical Engineering Indian Institute of Technology, Delhi

Communication Engineering Prof. Surendra Prasad Department of Electrical Engineering Indian Institute of Technology, Delhi Communication Engineering Prof. Surendra Prasad Department of Electrical Engineering Indian Institute of Technology, Delhi Lecture - 41 Pulse Code Modulation (PCM) So, if you remember we have been talking

More information

Bayesian Updating with Continuous Priors Class 13, Jeremy Orloff and Jonathan Bloom

Bayesian Updating with Continuous Priors Class 13, Jeremy Orloff and Jonathan Bloom Bayesian Updating with Continuous Priors Class 3, 8.05 Jeremy Orloff and Jonathan Bloom Learning Goals. Understand a parameterized family of distributions as representing a continuous range of hypotheses

More information

CPSC 467: Cryptography and Computer Security

CPSC 467: Cryptography and Computer Security CPSC 467: Cryptography and Computer Security Michael J. Fischer Lecture 18 November 3, 2014 CPSC 467, Lecture 18 1/43 Zero Knowledge Interactive Proofs (ZKIP) Secret cave protocol ZKIP for graph isomorphism

More information

FACTORS AFFECTING CONCURRENT TRUNCATE

FACTORS AFFECTING CONCURRENT TRUNCATE T E C H N I C A L N O T E FACTORS AFFECTING CONCURRENT TRUNCATE DURING BATCH PROCESSES Prepared By David Kurtz, Go-Faster Consultancy Ltd. Technical Note Version 1.00 Thursday 2 April 2009 (E-mail: david.kurtz@go-faster.co.uk,

More information

Knowledge Discovery and Data Mining 1 (VO) ( )

Knowledge Discovery and Data Mining 1 (VO) ( ) Knowledge Discovery and Data Mining 1 (VO) (707.003) Map-Reduce Denis Helic KTI, TU Graz Oct 24, 2013 Denis Helic (KTI, TU Graz) KDDM1 Oct 24, 2013 1 / 82 Big picture: KDDM Probability Theory Linear Algebra

More information

Arup Nanda Starwood Hotels

Arup Nanda Starwood Hotels Arup Nanda Starwood Hotels Why Analyze The Database is Slow! Storage, CPU, memory, runqueues all affect the performance Know what specifically is causing them to be slow To build a profile of the application

More information

Robust Programs with Filtered Iterators

Robust Programs with Filtered Iterators Robust Programs with Filtered Iterators Jiasi Shen, Martin Rinard MIT EECS & CSAIL 1 Standard Scenario Input file Program Output 2 Structured Input Units Input Input unit Input unit Input unit unit Program

More information

Finding the Nucleoli of Large Cooperative Games: A Disproof with Counter-Example

Finding the Nucleoli of Large Cooperative Games: A Disproof with Counter-Example Finding the Nucleoli of Large Cooperative Games: A Disproof with Counter-Example Holger I. MEINHARDT arxiv:1603.00226v1 [cs.gt] 1 Mar 2016 March 6, 2016 Nguyen and Thomas (2016) claimed that they have

More information

Discrete Mathematics and Probability Theory Fall 2013 Vazirani Note 1

Discrete Mathematics and Probability Theory Fall 2013 Vazirani Note 1 CS 70 Discrete Mathematics and Probability Theory Fall 013 Vazirani Note 1 Induction Induction is a basic, powerful and widely used proof technique. It is one of the most common techniques for analyzing

More information

PHP-Einführung - Lesson 4 - Object Oriented Programming. Alexander Lichter June 27, 2017

PHP-Einführung - Lesson 4 - Object Oriented Programming. Alexander Lichter June 27, 2017 PHP-Einführung - Lesson 4 - Object Oriented Programming Alexander Lichter June 27, 2017 Content of this lesson 1. Recap 2. Why OOP? 3. Git gud - PHPStorm 4. Include and Require 5. Classes and objects 6.

More information

Simplicity of A5 Brute Force Method!

Simplicity of A5 Brute Force Method! Simplicity of A5 Brute Force Method! Step 1: List all the elements of A5. i (12)(12) (135) (13)(35) (12354) (12)(23)(35)(54) (12)(34) (12)(34) (145) (14)(45) (13425) (13)(34)(42)(25) (12)(35) (12)(35)

More information

Introduction to Computer Tools and Uncertainties

Introduction to Computer Tools and Uncertainties Experiment 1 Introduction to Computer Tools and Uncertainties 1.1 Objectives To become familiar with the computer programs and utilities that will be used throughout the semester. To become familiar with

More information

Comp 11 Lectures. Mike Shah. July 26, Tufts University. Mike Shah (Tufts University) Comp 11 Lectures July 26, / 40

Comp 11 Lectures. Mike Shah. July 26, Tufts University. Mike Shah (Tufts University) Comp 11 Lectures July 26, / 40 Comp 11 Lectures Mike Shah Tufts University July 26, 2017 Mike Shah (Tufts University) Comp 11 Lectures July 26, 2017 1 / 40 Please do not distribute or host these slides without prior permission. Mike

More information

Extended Introduction to Computer Science CS1001.py. Lecture 8 part A: Finding Zeroes of Real Functions: Newton Raphson Iteration

Extended Introduction to Computer Science CS1001.py. Lecture 8 part A: Finding Zeroes of Real Functions: Newton Raphson Iteration Extended Introduction to Computer Science CS1001.py Lecture 8 part A: Finding Zeroes of Real Functions: Newton Raphson Iteration Instructors: Benny Chor, Amir Rubinstein Teaching Assistants: Yael Baran,

More information

Program Analysis Part I : Sequential Programs

Program Analysis Part I : Sequential Programs Program Analysis Part I : Sequential Programs IN5170/IN9170 Models of concurrency Program Analysis, lecture 5 Fall 2018 26. 9. 2018 2 / 44 Program correctness Is my program correct? Central question for

More information

Improving the Testing Rate of Electronic Circuit Boards

Improving the Testing Rate of Electronic Circuit Boards Electronic Circuit August 19, 2011 Problem statement Acculogic Inc. manufactures systems for testing (ECBs). The systems are almost entirely automatic but require some human input. The clients of Acculogic

More information

Concurrent HTTP Proxy Server. CS425 - Computer Networks Vaibhav Nagar(14785)

Concurrent HTTP Proxy Server. CS425 - Computer Networks Vaibhav Nagar(14785) Concurrent HTTP Proxy Server CS425 - Computer Networks Vaibhav Nagar(14785) Email: vaibhavn@iitk.ac.in August 31, 2016 Elementary features of Proxy Server Proxy server supports the GET method to serve

More information

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich June 8, 2015

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich June 8, 2015 Nicola Chiapolini, June 8, 2015 1 / 36 git Tutorial Nicola Chiapolini Physik-Institut University of Zurich June 8, 2015 Based on talk by Emanuele Olivetti https://github.com/emanuele/introduction_to_git

More information

Paper 3F: Reading and Understanding in Chinese

Paper 3F: Reading and Understanding in Chinese Write your name here Surname Other names Edexcel GSE entre Number andidate Number hinese Paper 3F: Reading and Understanding in hinese Wednesday 22 May 2013 fternoon Time: 45 minutes You do not need any

More information

Assignment 2 Atomic-Level Molecular Modeling

Assignment 2 Atomic-Level Molecular Modeling Assignment 2 Atomic-Level Molecular Modeling CS/BIOE/CME/BIOPHYS/BIOMEDIN 279 Due: November 3, 2016 at 3:00 PM The goal of this assignment is to understand the biological and computational aspects of macromolecular

More information

VPython Class 2: Functions, Fields, and the dreaded ˆr

VPython Class 2: Functions, Fields, and the dreaded ˆr Physics 212E Classical and Modern Physics Spring 2016 1. Introduction VPython Class 2: Functions, Fields, and the dreaded ˆr In our study of electric fields, we start with a single point charge source

More information

Lab 1: Empirical Energy Methods Due: 2/14/18

Lab 1: Empirical Energy Methods Due: 2/14/18 Lab 1: Empirical Energy Methods Due: 2/14/18 General remarks on scientific scripting Scientific scripting for managing the input and output data is an important component of modern materials computations,

More information

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich January 26, 2015

git Tutorial Nicola Chiapolini Physik-Institut University of Zurich January 26, 2015 Nicola Chiapolini, January 26, 2015 1 / 36 git Tutorial Nicola Chiapolini Physik-Institut University of Zurich January 26, 2015 Based on talk by Emanuele Olivetti https://github.com/emanuele/introduction_to_git.git

More information

Let us distinguish two kinds of annoying trivialities that occur in CoS derivations (the situation in the sequent calculus is even worse):

Let us distinguish two kinds of annoying trivialities that occur in CoS derivations (the situation in the sequent calculus is even worse): FORMALISM B Alessio Guglielmi (TU Dresden) 20.12.2004 AG13 In this note (originally posted on 9.2.2004 to the Frogs mailing list) I would like to suggest an improvement on the current notions of deep inference,

More information

Lecture Notes on Inductive Definitions

Lecture Notes on Inductive Definitions Lecture Notes on Inductive Definitions 15-312: Foundations of Programming Languages Frank Pfenning Lecture 2 August 28, 2003 These supplementary notes review the notion of an inductive definition and give

More information

Science Analysis Tools Design

Science Analysis Tools Design Science Analysis Tools Design Robert Schaefer Software Lead, GSSC July, 2003 GLAST Science Support Center LAT Ground Software Workshop Design Talk Outline Definition of SAE and system requirements Use

More information

CS5412: REPLICATION, CONSISTENCY AND CLOCKS

CS5412: REPLICATION, CONSISTENCY AND CLOCKS 1 CS5412: REPLICATION, CONSISTENCY AND CLOCKS Lecture X Ken Birman Recall that clouds have tiers 2 Up to now our focus has been on client systems and the network, and the way that the cloud has reshaped

More information

Introduction to Portal for ArcGIS

Introduction to Portal for ArcGIS Introduction to Portal for ArcGIS Derek Law Product Management March 10 th, 2015 Esri Developer Summit 2015 Agenda Web GIS pattern Product overview Installation and deployment Security and groups Configuration

More information

Multidomain Design and Optimization based on Comsol Multiphysics: Applications for Mechatronic Devices

Multidomain Design and Optimization based on Comsol Multiphysics: Applications for Mechatronic Devices Multidomain Design and Optimization based on Comsol Multiphysics: Applications for Mechatronic Devices A. Bissal 1*, O. Craciun 2, V. Biagini 2, J. Magnusson 3 1 ABB AB Corporate Research, Västerås, Sweden

More information

Note: Please use the actual date you accessed this material in your citation.

Note: Please use the actual date you accessed this material in your citation. MIT OpenCourseWare http://ocw.mit.edu 18.06 Linear Algebra, Spring 2005 Please use the following citation format: Gilbert Strang, 18.06 Linear Algebra, Spring 2005. (Massachusetts Institute of Technology:

More information

Chuck Cartledge, PhD. 21 January 2018

Chuck Cartledge, PhD. 21 January 2018 Big Data: Data Analysis Boot Camp Non-SQL and R Chuck Cartledge, PhD 21 January 2018 1/19 Table of contents (1 of 1) 1 Intro. 2 Non-SQL DBMS Classic Non-SQL databases 3 Hands-on Airport connections as

More information

Example: sending one bit of information across noisy channel. Effects of the noise: flip the bit with probability p.

Example: sending one bit of information across noisy channel. Effects of the noise: flip the bit with probability p. Lecture 20 Page 1 Lecture 20 Quantum error correction Classical error correction Modern computers: failure rate is below one error in 10 17 operations Data transmission and storage (file transfers, cell

More information

Lab 1: Handout GULP: an Empirical energy code

Lab 1: Handout GULP: an Empirical energy code Lab 1: Handout GULP: an Empirical energy code We will be using the GULP code as our energy code. GULP is a program for performing a variety of types of simulations on 3D periodic solids, gas phase clusters,

More information

Study skills for mathematicians

Study skills for mathematicians PART I Study skills for mathematicians CHAPTER 1 Sets and functions Everything starts somewhere, although many physicists disagree. Terry Pratchett, Hogfather, 1996 To think like a mathematician requires

More information

MI-RUB Exceptions Lecture 7

MI-RUB Exceptions Lecture 7 MI-RUB Exceptions Lecture 7 Pavel Strnad pavel.strnad@fel.cvut.cz Dept. of Computer Science, FEE CTU Prague, Karlovo nám. 13, 121 35 Praha, Czech Republic MI-RUB, WS 2011/12 Evropský sociální fond Praha

More information

Using the Prover I: Lee Pike. June 3, NASA Langley Formal Methods Group Using the Prover I:

Using the Prover I: Lee Pike. June 3, NASA Langley Formal Methods Group Using the Prover I: Basic Basic NASA Langley Formal Methods Group lee.s.pike@nasa.gov June 3, 2005 Basic Sequents Basic Sequent semantics: The conjunction of the antecedents above the turnstile implies the disjunction of

More information

Learning from Examples

Learning from Examples Learning from Examples Data fitting Decision trees Cross validation Computational learning theory Linear classifiers Neural networks Nonparametric methods: nearest neighbor Support vector machines Ensemble

More information

Cantera / Stancan Primer

Cantera / Stancan Primer Cantera / Stancan Primer Matthew Campbell; A.J. Simon; Chris Edwards Introduction to Cantera and Stancan Cantera is an open-source, object-oriented software package which performs chemical and thermodynamic

More information

Techniques for Proof Writing

Techniques for Proof Writing Appendix B Techniques for Proof Writing This guide includes some things that I like to keep in mind when I am writing proofs. They will hopefully become second-nature after a while, but it helps to actively

More information

DMDW: A set of tools to calculate Debye-Waller factors and other related quantities using dynamical matrices.

DMDW: A set of tools to calculate Debye-Waller factors and other related quantities using dynamical matrices. DMDW: A set of tools to calculate Debye-Waller factors and other related quantities using dynamical matrices. DMDW is a set of tools developed to calculate Debye-Waller (DW) factors and other related quantities

More information

Lectures about Python, useful both for beginners and experts, can be found at (http://scipy-lectures.github.io).

Lectures about Python, useful both for beginners and experts, can be found at  (http://scipy-lectures.github.io). Random Matrix Theory (Sethna, "Entropy, Order Parameters, and Complexity", ex. 1.6, developed with Piet Brouwer) 2016, James Sethna, all rights reserved. This is an ipython notebook. This hints file is

More information

Introduction to ArcGIS Server Development

Introduction to ArcGIS Server Development Introduction to ArcGIS Server Development Kevin Deege,, Rob Burke, Kelly Hutchins, and Sathya Prasad ESRI Developer Summit 2008 1 Schedule Introduction to ArcGIS Server Rob and Kevin Questions Break 2:15

More information