The rapidly changing capabilities of modern Graphics Processing Units (GPUs) mean that developers need to understand how to combine parallel-programming techniques with the traditional interactive rendering pipeline exposed by OpenGL and Direct3D. This course demonstrates how to combine traditional rendering Application Programming Interfaces (APIs) with advanced parallel computation using OpenCL (Open Computing Language), a cross-platform API for programming parallel systems such as GPUs. The course presenters are experts on general-purpose GPU computation and advanced rendering from academia and industry, and have presented papers and tutorials on the topic at SIGGRAPH, Graphics Hardware, Supercomputing, and elsewhere. This tutorial provides an introduction to the OpenCL API, and presents multiple example application.

Level
Intermediate

Intended Audience
Developers who wish to use OpenCL to leverage GPUs and multi-core systems with an open, cross-platform API.

Prerequisites
Understanding of C and C++ programming and OpenGL would be helpful.

Course Schedule
9:00-9:15 - Introductions and Opening Remarks (Justin Hensley)
9:15-10:15 - OpenCL Overview and Introductory Examples (Derek Gerstmann)
10:15-10:45 - OpenCL C++ bindings and Graphics Interop (Justin Hensley)

Presenter(s)
Justin Hensley is a Senior Member of Technical Staff in AMD's Office of the CTO, focusing on parallel programming using graphics processors. Since joining AMD, he has been involved with projects such as face recognition, depth extraction, and game physics. Recently, he has been involved with driving the compute requirements of next generation-graphics processors. He received his PhD in Computer Science from the University of North Carolina at Chapel Hill in 2007. He also holds an MS in Electrical Engineering and a BS in Electrical Engineering and Computer Science Engineering from the University of California, Davis.

Derek Gerstmann is a research fellow at the University of Western Australia, focusing on visualization and data analysis for the BioImaging Initiative, co-funded by the Western Australian Supercomputer Program (WASP) and the Centre for Microscopy, Characterization and Analysis (CMCA). His knowledge and experience in parallel and distributed computation comes from a diverse professional career, including engineering positions at AMD/ATI, Apple, and Weta Digital. He received his MS from the National Centre for Computer Animation (NCCA) at Bournemouth University, UK and his BS from the University of Washington

Jason Yang is a Member of Technical Staff in AMD's Office of the CTO currently focused on GPGPU research. Major projects he has been involved in include H.264 and VC-1 shader decoding and custom anti- aliasing with edge detection. Recently, he worked on AMD's Stream Computing SDK. He received his PhD in Computer Science and his BS in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2005 and 1999 respectively.