ESS116 ESS 116 Introduction to Data Analysis in Earth Science Image Credit: NASA Instructor: Mathieu Morlighem E-mail: mmorligh@uci.edu (include ESS116 in subject line) Office Hours: 3218 Croul Hall, Friday 2:00 pm – 3:00 pm This content is protected and may not be shared uploaded or distributed Course introduction Syllabus review Why this class matters Logistics […]
Parallel Programming in C with the Message Passing Interface Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Parallel Programming in C with MPI and OpenMP Michael J. Quinn Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Chapter 17 Shared-memory Programming Copyright © The McGraw-Hill Companies, Inc. Permission
PowerPoint Presentation Basics in programming 4.3.2019 Object-orientated programming So far we have been here This is were we are going To build today’s complex software it is just not enough to put together a sequence of programming statements and sets of procedures and modules We need to incorporate construction techniques and program structures that are
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Programming Languages CSCI 4430 & CSCI 6969 Binding and Scoping Read: Scott, Chapter 3.1, 3.2 and 3.3.1, 3.3.2 and 3.3.6 1 1 Programming Languages CSCI 4430, A. Milanova 2 Lecture Outline Notion of binding time Object lifetime and storage management An aside: Stack Smashing 101 Scoping Static scoping Dynamic scoping Notion of Binding Time Binding
Linux UNIX and LINUX CSE 2421 1 Developed from 1969-1971 at AT&T Bell Laboratories (Ken Thompson/Dennis Ritchie/Brian Kernighan/Douglas McIIroy/Joe Ossanna) Written largely in C (some assembly language code as well) C was originally developed as a programming language to write the Unix OS, which was a multi-user, multi-tasking OS. Proprietary (requires a license for use)
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In [1]: rdd = sc.parallelize([1, 2, 3, 3]) In [4]: rdd.map(lambda x: [x, x+1]).collect() Out[4]: [[1, 2], [2, 3], [3, 4], [3, 4]] In [5]: rdd.flatMap(lambda x: [x, x+1]).collect() Out[5]: [1, 2, 2, 3, 3, 4, 3, 4] In [6]: rdd1 = sc.parallelize([1, 2, 0.5, 0.1, 5, 0.2], 4) In [2]: rdd1.collect() Out[2]: [1, 2, 0.5, 0.1, 5, 0.2] In [3]:
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CS267: Introduction 09/27/2011 CS4961 CS4961 Parallel Programming Lecture 10: Introduction to SIMD Mary Hall September 27, 2011 CS4961 Today’s Lecture Conceptual understanding of SIMD Practical understanding of SIMD in the context of multimedia extensions Slide source: Sam Larsen, PLDI 2000, http://people.csail.mit.edu/slarsen/ Jaewook Shin, my former PhD student 09/27/2011 CS4961 CS4961 SIMD and MIMD Architectures: What’s
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DNDS6013 Scientific Python: 4th Class¶ Central European University, Winter 2019/2020¶ Instructor: Márton Pósfai, TA: Luis Natera Orozco Emails: posfaim@ceu.edu, natera_luis@phd.ceu.edu Plan for today¶ • Continue with city data • Dictionaries • Numpy • (Plotting with matplotlib) Don’t forget about our slack channel. But first, solving problems from last week¶ Solutions cannot be hidden: Solution. “`python
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tnt_fortran_array2d_utils.h File Reference Main Page Namespace List Compound List File List Namespace Members Compound Members File Members Copyright By PowCoder代写 加微信 powcoder tnt_fortran_array2d_utils.h File Reference #include Go to the source code of this file. Namespaces namespace TNT Generated at Thu Jun 26 17:26:14 2003 for Template Numerical
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Red: no coding-exam Section 1 Introduction: Programming languages, programming basics, data types, operators, expressions, control structures (sequential, conditional and iterated execution), vector/array operations, input/output, plots, style, floating-point representation of real numbers, numerical errors. Copyright By PowCoder代写 加微信 powcoder · Slide 1.1 and 1.2 · Numerical Recipes, Chapter 1 · Tools from Stochastic Analysis, Chapter 1
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