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{{GPU610/DPS915 Index | 2013120191}}
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*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.
* [https://scsict.senecac.onsenecacollege.ca/course/gpu610 Course Outline]
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*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.
* [https://scsict.senecac.onsenecacollege.ca/course/dps915 Course Outline]
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== Workshops ==
* The workshops provide timely opportunities to implement some of the material covered during the lectures. Each workshop is graded and all submissions are through [https://open.senecac.on.ca/cms/course/view.php?id=438 536 Moodle].
* Detail Specifications
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w1.html Initial Profile]
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w9.html Coalesced Memory Access]
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w10.html CUDA to OpenCL]
* Grading - The due date for each workshop is noted in [https://openMySeneca.senecac.on.ca/cms/course/view.php?id=438 Moodle]. The penalty for late submission is 5020% of the workshop mark; 50% for very late submission.
== Assignments ==
== Evaluation ==
* Assignments and Presentation 3020%* Workshops 2030%* Test 20Option 1: Tests 50%* Option 2: Tests 35% + Exam 3015%
= Resources =
* Software Support
** [http://developer.nvidia.com/cuda-downloads CUDA Toolkit]
** Get [https://inside.senecacollege.ca/its/software/index.html Visual Studio 2012 Ultimate2017] | Select Software Downloads | Go To Visual Studio 2012 2013 Ultimate 12.49GB 82GB | Download iso | Burn, if error burn again | Finally , install
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