Enrollment Closed. Class limit reached.

Curriculum Overview

will provide a foundation for:

• Developing parallel-programming skills in OpenMP and MPI
• Understanding performance aspects of the AMD Architecture
• Using batch system: SGE
• Optimizing code
• Code debugging

Labs for the training will include access to Ranger for:

• Compiling and running example codes
• Porting your own codes
• Discussion and hands-on assistance from instructors
• Collaborative discussions with colleagues who have interest in parallel computing

Location

Bobst Library, Lower Level I
Computer Center PC Classroom #2
70 Washington Square South
New York, NY 10012
(212) 998-2500

Please visit the following links for additional information.
General Directions to NYU: http://www.nyu.edu/about/travel.html
Address and Map to the Bobst Library: http://library.nyu.edu/about/bobstmap.html

Parking Information: http://www.nyu.edu/about/parking.html.

Accommodations

Class attendees traveling to the training are responsible for arranging and paying for their own travel, daily expenses, and hotel accommodations. Arrangements have been made, however, for a special rate and a block of 14 rooms at the Washington Square Hotel (ask for group number 20608). Reservations must be made by January 18, 2008; after that date, rooms are available on a first come, first served basis.

Please see the following URL for the contact information for other housing options. Be sure to ask for the “NYU rate” when making reservations at any of these hotels.

http://www.nyu.edu/about/hotels.html

Agenda

Day 1: 8:15 am - 5:00 pm
Time	Day 1
8:15 am	Registration
8:30 am	Welcome & TACC Overview
8:45 am	Introduction to Parallel Computing
9:45 am	Break
10:00 am	Rocks/Linux (x86_64) Programming Env.
11:00 am	Lab
12:00 pm	Lunch
1:00 pm	Intro to Programming with OpenMP
2:00 pm	Lab
3:00 pm	Break
3:15 pm	Programming with MPI
4:15 pm	Lab

Day 2: 8:30 am - 5:00 pm
Time	Day 2
8:30 am	HPC Hardware Overview
9:30 am	Hybrid Programming with OpenMP & MPI
10:30 am	Break
10:45 pm	Lab
12:00 pm	Lunch
1:00 pm	Optimization and Scalability for HPC
2:30 pm	Lab
3:00 pm	Break
3:15 pm	Profiling and Debugging
4:00 pm	Lab