GPU621/DPS921

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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

• Chris Szalwinski

External Links

• Course Web Site – Lecture Notes
• Course Web Site – Timeline

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
  1. Platforms
  2. False Sharing
  3. Prefix Scan
  4. Convolution
  5. Threading Building Blocks
  6. Vectorization
  7. Fork Join
  8. Data Decomposition
  9. Scatter Gather
  10. Optimization
• 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%

• Wikis
  • How To edit Wiki pages
  • How To edit Wiki Cheatsheet