Difference between revisions of "GPU621/DPS921"
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| − | {{GPU621/DPS921 Index | | + | {{GPU621/DPS921 Index | 20217}} |
Please help make this page resourceful for all GPU621/DPS921 students to use! | Please help make this page resourceful for all GPU621/DPS921 students to use! | ||
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== GPU621/DPS921 - Parallel Algorithms and Programming Techniques == | == GPU621/DPS921 - Parallel Algorithms and Programming Techniques == | ||
*Large data and compute-intensive problems benefit from parallel solutions. Modern hardware has parallel processing capabilities in varying degrees. Students study a set of industry-standard parallel patterns and learn how to implement parallel algorithms on multi-processor accelerators, shared memory systems and distributed systems using a range of programming models. | *Large data and compute-intensive problems benefit from parallel solutions. Modern hardware has parallel processing capabilities in varying degrees. Students study a set of industry-standard parallel patterns and learn how to implement parallel algorithms on multi-processor accelerators, shared memory systems and distributed systems using a range of programming models. | ||
| − | * [https:// | + | * [https://ict.senecacollege.ca/course/gpu621 GPU621 Course Outline] |
| − | * [https:// | + | * [https://ict.senecacollege.ca/course/dps921 DPS921 Course Outline] |
== Instructor == | == Instructor == | ||
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* 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 Moodle]. | * 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 Moodle]. | ||
* Detail Specifications | * Detail Specifications | ||
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w1.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w1.html Platforms] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w2.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w2.html False Sharing] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w3.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w3.html Prefix Scan] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w4.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w4.html Convolution] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w5.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w5.html Threading Building Blocks] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w6.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w6.html Vectorization] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w7.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w7.html Fork Join] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w8.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w8.html Data Decomposition] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w9.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w9.html Scatter Gather] |
| − | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w10.html | + | *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w10.html Optimization] |
| − | + | * Grading - The due date for each workshop is noted in MySeneca. The penalty for late submission is 30% of the workshop mark. | |
| − | * Grading - The due date for each workshop is noted in | ||
== Evaluation == | == Evaluation == | ||
| − | * | + | * Project 20% |
| − | * Workshops | + | * Workshops 30% |
| − | * | + | * Tests 50% |
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Latest revision as of 19:43, 1 September 2021
GPU621/DPS921 | Participants | Groups and Projects | Resources | Glossary
Please help make this page resourceful for all GPU621/DPS921 students to use!
Contents
Course Material
GPU621/DPS921 - Parallel Algorithms and Programming Techniques
- Large data and compute-intensive problems benefit from parallel solutions. Modern hardware has parallel processing capabilities in varying degrees. Students study a set of industry-standard parallel patterns and learn how to implement parallel algorithms on multi-processor accelerators, shared memory systems and distributed systems using a range of programming models.
- GPU621 Course Outline
- DPS921 Course Outline
Instructor
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 30% of the workshop mark.
Evaluation
- Project 20%
- Workshops 30%
- Tests 50%
