Northwest Webinar Series: October 2020

Join us for a series of live webinar sessions with our NA Academic Engineering team!

We invite you to attend the following free MATLAB sessions focusing on accelerating and optimizing your MATLAB code and scaling up your applications using clusters and GPU’s.

Register below for your preferred sessions. You can register for as many sessions as you like. Please note that seats are limited and therefore registration is required.

Working with Time & Frequency in MATLAB

Wednesday, October 21, 2020 8:00 am PST
Presenter: Loren Shure
Presented via YouTube Live

In this session we will introduce how to work with signals in MATLAB, including:

Import data from various sources
Analyze signals in the time and frequency domain
Remove noise by designing/applying filters
Build scripts that automatically repeat the analysis
Generate reports and build apps

Accelerating and Optimizing MATLAB Code

Thursday, October 22, 2020 12:00 pm PST
Presenter: Aycan Hacioglu
Presented via Webex

In this session we will discuss and demonstrate simple ways to improve and optimize your code that can boost execution speed by orders of magnitude. We will also address common pitfalls in writing MATLAB code, explore the use of the MATLAB Profiler to find bottlenecks, introduce our Parallel Computing Toolbox to solve computationally and data-intensive problems on multicore computers and clusters, and finally talk about tools to automatically translate your MATLAB code into C.

Highlights include:

Optimizing MATLAB code to boost execution speed
Automatically generating portable C code from MATLAB

» Register

Parallel and GPU Computing with MATLAB

Friday, October 23, 2020 12:00 pm PST
Presenter: Sumit Tandon
Presented via Webex

In this session you will learn how to solve and accelerate computationally and data-intensive problems that are becoming common in the areas of machine learning and deep learning using multicore processors, GPUs, and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize MATLAB applications and run them on multiple processors. We will also discuss how to take advantage of GPUs to speed up computations without low-level programming.

Highlights include:

Toolboxes with built-in support for parallel computing
Creating parallel applications to speed up independent tasks
Scaling up to computer clusters, grid environments or clouds
Employing GPUs to speed up your computations

» Register