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Parallel Matlab Workshop

Class type: Programming Language
Class date: 2017-10-25

This workshop will describe how to use Matlab to leverage the parallel computing capabilities of modern CPU architectures, including those of Virginia Tech’s supercomputers. Users will learn how to use parfor, spmd, and distributed array constructs to parallelize Matlab code, best practices for doing so, how to run parallel jobs locally, and how to run them on Virginia Tech’s supercomputers.

A variety of example codes will be provided for student use.

*Attendees are expected to be familiar with Matlab basics, but will not need any experience with parallel programming.

Slides: ARC_Matlab_2017Oct25
Parfor Codes: ARC_Matlab_2017Oct25_parfor_codes
SPMD Codes: ARC_Matlab_2017Oct25_spmd_codes

Experiments in Matlab: Iterations

Class type: Introduction
Class date: 2017-03-01

This presentation is an informal introduction to iteration and Matlab.
It shows how the idea of iteration is used in computing, and how Matlab
can implement iteration using for and while loops.

Slides: Download

Parallel Matlab Workshop

Class type: Programming Language
Class date: 2017-01-19

This workshop will describe how to use Matlab to leverage the parallel computing capabilities of modern CPU architectures, including those of Virginia Tech’s supercomputers. Users will learn how to use parfor, spmd, and distributed array constructs to parallelize Matlab code, best practices for doing so, how to run parallel jobs locally, and how to run them on Virginia Tech’s supercomputers.

A variety of example codes will be provided for student use. Attendees are expected to be familiar with Matlab basics, but will not need any experience with parallel programming.

Slides: Matlab_2017Jan19
Parfor Codes: Matlab_2017Jan19_parfor_codes
SPMD Codes: Matlab_2017Jan19_spmd_codes

Parallel Matlab Workshop

Class type: Programming Language
Class date: 2016-09-27

This workshop will describe how to use Matlab to leverage the parallel computing capabilities of modern CPU architectures, including those of Virginia Tech’s supercomputers. Users will learn how to use parfor, spmd, and distributed array constructs to parallelize Matlab code, best practices for doing so, how to run parallel jobs locally, and how to run them on Virginia Tech’s supercomputers. A variety of example codes will be provided for student use. Attendees are expected to be familiar with Matlab basics, but will not need any experience with parallel programming.

Slides: matlab_2016sept27
Parfor Codes: matlab_2016sept27_parfor_codes
SPMD Codes: matlab_2016sept27_spmd_codes

Parallel Matlab III: Single Program Multiple Data

Class type: Programming Language
Class date: 2015-11-05

This short course is the third in a three-part series on parallel programming in Matlab. This course focuses on Single Program Multiple Data (SPMD) constructs. We discuss SPMD workspace(s), the scope of variables and composite arrays. Construction and use of distributed (and codistributed) arrays is covered along with data exchange among the multiple workers. A variety of example codes are available for student use. Attendees are expected to have attended part II (parfor) and be familiar with the basic syntax and structure of Matlab code.

Slides: Matlab_III_SPMD_2015Nov05

Parallel Matlab II: Parfor

Class type: Programming Language
Class date: 2015-10-21

This short course is the second in a three-part series on parallel programming in Matlab. We focus on parallel for (“parfor”) loops, the most basic way to parallelize Matlab code, and walk through several examples that illustrate the use of parfor. We also discuss how to identify bottlenecks (candidates for parallelism) and limitations on the use of parfor. A variety of example codes are available for student use. Attendees are expected to be familiar with the basic syntax and structure of Matlab code.

Slides: Matlab_II_2015Oct21
Codes: Matlab_II_2015Oct21_codes

Parallel Matlab Workshop

Class type: Programming Language
Class date: 2015-09-18

This workshop will describe how to use Matlab to leverage the parallel computing capabilities of modern CPU architectures, including those of Virginia Tech’s supercomputers. Users will learn how to use parfor, spmd, and distributed array constructs to parallelize Matlab code, best practices for doing so, how to run parallel jobs locally, and how to run them on Virginia Tech’s supercomputers. A variety of example codes will be provided for student use. Attendees are expected to be familiar with Matlab basics, but will not need any experience with parallel programming.

Slides: Matlab_Workshop_2015Sept18

Parallel Matlab I: Introduction and VT Resources

Class type: Programming Language
Class date: 2015-09-16

This short course is the first in a three-part series on parallel programming in Matlab. This course presents an overview of Matlab Parallel Computing constructs and the applications of each. It discusses several ways to run parallel jobs in Matlab and finally discusses migrating those jobs to Virginia Tech’s Ithaca supercomputer. Attendees are expected to be familiar with Matlab basics, but will not need any experience with cluster computing.

Slides: Matlab_I_2015Sept16
Code: Matlab_I_2015Sept16_code