NAG Training Courses
Training Course: NAG Toolbox for MATLAB®
Seminar 1: 'Multicore Demystified'
Seminar 2: Banking on Monte Carlo with GPUs
Teaching Lab Room 5205 and Lecture Theatre Room 6301.
James Clerk Maxwell Building, Mayfield Road, Edinburgh EH9 3JZ
For directions, go to www.ed.ac.uk/maps
9th June 2010
|9.30am - 12.30pm
1.30pm - 4.00pm
4.00pm - 5.00pm
|Using the NAG Toolbox for MATLAB
'Multicore Demystified' an introduction to Multicore Programming and the NAG Library for SMP & Multicore
'Banking on Monte Carlo with GPUs'
This event is free of charge; however, places are strictly limited. In order to guarantee your place, please register your attendance in advance by completing the Registration Form below.
TRAINING COURSE 1: Using the NAG Toolbox for MATLAB
We will show how using the Toolbox can enhance your work, and show specific demonstrations of the solving of problems. Attendees will have the opportunity to get 'hands-on' with the Toolbox and direct questions to the experts who develop the Toolbox and the NAG Libraries.
We will be using University of Edinburgh workstations for this course.
If you would like to Bring Your Own Laptop please ensure NAG Toolbox for MATLAB is installed and working before your arrival.
SEMINAR 1: ‘Multicore Demystified’
An Introduction to Multicore Programming and the NAG Library for SMP & multicore
In this lecture we aim to demystify programming your multicore machine. We give an introduction to the terminology and what it really means. We show how you can get the most out of your machine with a brief introduction to the programming language OpenMP. We also show you how to get the most out of the NAG Library for SMP and multicore with performance hints and tips.
SEMINAR 2: Banking on Monte Carlo 4-5 'Banking on Monte Carlo with GPUs'
Monte Carlo simulation is one of the most important numerical methods in financial derivative pricing and risk management. Due to the increasing sophistication of exotic derivative models, Monte Carlo becomes the method of choice for numerical implementations because of its flexibility in high-dimensional problems. The choice of computing platform and the exploitation of parallelism offers further efficiency gains. We review possibilities opened up by the advent of programmable graphics processing units (GPUs) on the overall performance of Monte Carlo and quasi-Monte Carlo methods.
If you are interested in holding a NAG related training course at your organisation please email us at firstname.lastname@example.org for more information. In addition to the above training courses we also offer other training courses. NAG regularly hosts training courses for those working on the UK's national supercomputing service HECToR. For more information on HECToR Training Courses visit http://www.hector.ac.uk/cse/training/