Wednesday 12 August 2020
IP Policy
Collaborating Institutions

High Performance GPU Computing with NVIDIA CUDA

A half day workshop and discussion forum

Note: workshop is full, attendance allowed for registered participants only, please. Also, there will be no official registration, proceedings will start at 9am.


To be held from 8:45-13:00, Wednesday May 27, in Lecture theatre 3 of the Alan Gilbert Building. A light lunch will be supplied afterwards from 13:00-14:00.

With speakers from NVIDIA and Xenon Systems, this workshop is hosted by the ARC Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS), and the Department of Mathematics and Statistics at the University of Melbourne.


Due to recent advances in GPU hardware and software, so called general purpose GPU computing (GPGPU) is rapidly expanding from niche applications to the mainstream of high performance computing. For HPC researchers, hardware gains have increased the imperative to learn this new computing paradigm, while high level programming languages (in particular, CUDA) have decreased the barrier to entry to this field, so that it is now possible for new developers to rapidly port suitable applications from C/C++ running on CPUs to CUDA running on GPUs. For appropriate applications, GPUs have significant, even dramatic, advantages compared to CPUs in terms of both Dollars/FLOPS and Watts/FLOPS.

This workshop and discussion forum aims to provide a detailed introduction to GPU computing with CUDA and NVIDIA Tesla computing solutions.

CUDA is NVIDIA's exciting parallel computing architecture that is built up on a unified Computing architecture and multiple software components. The architecture consists of an ISA and hardware compute engine. The available software tools include a C compiler and NVIDIA drivers for developers to build applications using C for CUDA, as well as useful libraries for high-performance computing (BLAS, FFT, etc.).

Mark Harris of NVIDIA will provide an introduction to the CUDA architecture, programming model, and the programming environment of C for CUDA, as well as an overview of the Tesla GPU architecture, a live programming demo, and strategies for optimizing CUDA applications for the GPU. Dragan Dimitrovici of Xenon Systems will then briefly discuss the hardware requirements for getting started with CUDA.


Mark Harris (NVIDIA)

Mark Harris is a Senior Developer Technology Engineer at NVIDIA, where he works with developers around the world on software for computer graphics and high-performance computing. His research interests include parallel algorithms, general-purpose computation on GPUs, physically based simulation, real-time rendering, and gastronomy. Mark earned his Ph.D. in computer science from the University of North Carolina at Chapel Hill in 2003 and his B.S. from the University of Notre Dame in 1998. Mark founded and maintains, a web site dedicated to general-purpose computation on GPUs. Mark has recently moved to Brisbane after living in the United Kingdom for five years.

Nathan Clisby (MASCOS)

Nathan Clisby is a research fellow at the ARC Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS), and the Department of Mathematics and Statistics, University of Melbourne. His research interests include statistical mechanics, climate change, and complex systems.

Dragan Dimitrovici (Xenon Systems)

Dragan Dimitrovici is the Founder and driving force of the XENON Technology Group. He founded the company in 1996 at the age of 21, when he recognised the opportunity to sell quality locally assembled computer hardware.

The XENON Technology Group (XTG) which consists of XENON Systems, Mediaproxy and XDT develops mission critical solutions for new and emerging markets within the Defence, Scientific Research, Broadcast, Film and Education industry. Its solutions are tailored to individual customer requirements. Each year XTG invest heavily in research and partners with world-class IT vendors including, NVIDIA, Supermicro, Intel, AMD, Mellanox, Xyratex, Adaptec, AccelerEyes (Jacket for Matlab) & Microsoft.

Dragan studied Information Management at Melbourne University and is a certified Intel Server Integration Specialist. In 2006, Dragan was an Ernst & Young, Entrepreneur of the Year finalist.

Dragan has direct responsibility for the product development and strategy of the company.


9:00 Introduction to NVIDIA CUDA and Tesla (Mark Harris) pdf (2.7 MB)
CUDA and GPU programming: an opportunity for scientists (Nathan Clisby) pdf (1 MB)
CUDA Parallel Programming Model and C for CUDA (Mark Harris) pdf (680 MB)
Live Programming Demo Part 1 (Mark Harris)
10:50 Tea Break
11:10 Live Programming Demo Part 2 (Mark Harris)
CUDA Toolkit and Libraries (Mark Harris) pdf (400 MB)
Optimizing Performance (Mark Harris) long (620 KB) short (500 KB)
CUDA Directions (Mark Harris) pdf (190 KB)
Getting Started - CUDA enabled Hardware Options (Dragan Dimitrovici)
General Q&A
13:00 Light Lunch and Discussion
14:00 Finish


Lecture theatre 3, Level 1 of the Alan Gilbert Building, 161 Barry St.
Lunch will be held in the Executive Lounge, Level 1 of the Alan Gilbert Building.


The Alan Gilbert Building is located at the corner of Grattan St and Barry St, immediately to the south of the Parkville campus of the University of Melbourne (Map).


Please register for the workshop by sending an email to Nathan Clisby (
Registration is free, but required for catering purposes, and the number of participants is limited to 50.

GPU seminar mailing list

We will soon be starting a seminar series on scientific and engineering applications of GPU programming. Please send an email to Nathan Clisby ( if you wish to join the mailing list. Note: many details have yet to be determined, such as the department which will host this seminar.

Xenon Systems MASCOS Dept. of Mathematics and Statistics

MASCOS logo NVIDIA Tesla logo Xenon Systems logo

Created by: nclisby last modification: Thursday 28 of May, 2009 [07:03:46 UTC] by nclisby

Copyright © Centre of Excellence for Mathematics and Statistics of Complex Systems 2007
RSS Wiki rss Calendars