MATLAB and Simulink Seminars

Build and Execute Parallel Applications in MATLAB

Overview

MATLAB helps you obtain deeper scientific and clinical insights by giving you the ability to analyze and visualize ever increasing amounts of data.  Whether you’re analyzing data, developing algorithms or creating models, MATLAB is designed for the way you think and the work you do.

Join us for this complimentary MATLAB instructional session on Thursday, March 28, 2019 given by a MathWorks Application Engineer.  Our objective is to help you become as successful and productive as possible building and executing parallel applications using our tools.  

               Registration is recommended for headcount.

Highlights

  • Program parallel applications in MATLAB
  • Analyze big data sets and solve large scale problems
  • Run parallel applications interactively and as batch jobs 
  • Employ multicore processors and GPUs to speed up your computations
  • Off-loading processor-intensive tasks to clusters and cloud computing services

Agenda

Time Title
9:00-10:30 AM

Large-scale simulations and data processing tasks can take an unreasonably long time to complete or require a lot of computer memory. You can speed up these tasks with multicore computers, GPUs, computer clusters and cloud computing services. MathWorks parallel computing products let you use these resources from MATLAB without making major changes to your computing environment or workflow.

In this session we show how to program parallel applications in MATLAB. We introduce high-level programming constructs to easily create parallel applications without low-level programming and show how to offload processor-intensive tasks on a computing resource of your choice—multicore computers, GPUs, or larger resources such as HPC clusters and cloud computing services.

Learning objectives:

  • Program parallel applications in MATLAB
  • Analyze big data sets and solve large scale problems
  • Run parallel applications interactively and as batch jobs 
  • Employ multicore processors and GPUs to speed up your computations
  • Off-loading processor-intensive tasks to clusters and cloud computing services

Registration closed