Difference between revisions of "GPU610/DPS915"
(→Course Material) |
|||
| Line 11: | Line 11: | ||
*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. | *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:// | + | * [https://ict.senecacollege.ca/course/gpu610 Course Outline] |
</td> | </td> | ||
<td> | <td> | ||
| Line 26: | Line 26: | ||
*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. | *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:// | + | * [https://ict.senecacollege.ca/course/dps915 Course Outline] |
</td> | </td> | ||
<td> | <td> | ||
| Line 54: | Line 54: | ||
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w9.html Coalesced Memory Access] | *# [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] | *# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w10.html CUDA to OpenCL] | ||
| − | * Grading - The due date for each workshop is noted in | + | * Grading - The due date for each workshop is noted in MySeneca. The penalty for late submission is 20% of the workshop mark; 50% for very late submission. |
== Assignments == | == Assignments == | ||
| Line 63: | Line 63: | ||
== Evaluation == | == Evaluation == | ||
| − | * Assignments and Presentation | + | * Assignments and Presentation 20% |
| − | * Workshops | + | * Workshops 30% |
| − | * | + | * Option 1: Tests 50% |
| − | * Exam | + | * Option 2: Tests 35% + Exam 15% |
= Resources = | = Resources = | ||
Revision as of 18:49, 6 January 2017
GPU610/DPS915 | Student List | Group and Project Index | Student Resources | Glossary
Please help make this page resourceful for all GPU610/DPS915 students to use!
Contents
Course Material
GPU610 - Parallel Programming Fundamentals
|
|
DPS915 - Introduction to Parallel Programming
|
|
External Links
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 Moodle.
- Detail Specifications
- Grading - The due date for each workshop is noted in MySeneca. The penalty for late submission is 20% of the workshop mark; 50% for very late submission.
Assignments
Evaluation
- Assignments and Presentation 20%
- Workshops 30%
- Option 1: Tests 50%
- Option 2: Tests 35% + Exam 15%
Resources
- Software Support
- CUDA Toolkit
- Get Visual Studio 2013 | Select Software Downloads | Go To Visual Studio 2013 Ultimate 2.82GB | Download iso | Burn, if error burn again | Finally, install
