Revision as of 19:24, 9 January 2013

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Course Material

Modern GPU (Graphics Processing Unit) technology supports massively parallel computations, which complements the serial processing capabilities of CPU technology. This course teaches students how to read, write, and debug programs that use both CPU and GPU technology. Students learn to reorganize existing programs into serial code that runs on the CPU and parallel code that runs on the GPU. Students also study cases that have benefited from CPU+GPU programming.
Course Outline

Modern GPU (Graphics Processing Unit) technology supports massively parallel computations, which complements the serial processing capabilities of CPU technology. This course teaches students how to read, write, and debug programs that use both CPU and GPU technology. Students learn to reorganize existing programs into serial code that runs on the CPU and parallel code that runs on the GPU. Students also study cases that have benefited from CPU+GPU programming and develop a CPU+GPU application for a client.

The workshops provide timely opportunities to implement some of the material covered during the lectures. Each workshop is graded and all submissions are through Moodle.
Detail Specifications
Grading - The window for submission of each workshop is one week plus a day from the date of the workshop period. The penalty for late submission is 50% of the workshop mark.

@@ Line 54: / Line 54: @@
 *# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w9.html Matrix Product using Streams]
 *# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w10.html CUDA to OpenCL]
-* Grading - The window for submission of each workshop is one week.  The penalty for late submission is 50% of the workshop mark.
+* Grading - The window for submission of each workshop is one week plus a day from the date of the workshop period.  The penalty for late submission is 50% of the workshop mark.
 == The Assignments  ==