Difference between revisions of "GPU621/DPS921"

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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://secure.senecac.on.ca/ssos/findWithoutSemester/GPU6921/SICT GPU621 Course Outline]
+
* [https://ict.senecacollege.ca/course/gpu621 GPU621 Course Outline]
* [https://secure.senecac.on.ca/ssos/findWithoutSemester/DPS921/SICT DPS921 Course Outline]
+
* [https://ict.senecacollege.ca/course/dps921 DPS921 Course Outline]
  
 
== Instructor ==
 
== Instructor ==

Revision as of 15:44, 7 September 2016


GPU621/DPS921 | Participants | Groups and Projects | Resources | Glossary

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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

External Links

Workshops

Evaluation

  • Assignments and Presentation 30%
  • Workshops 20%
  • Test 20%
  • Exam 30%

Resources

  • Current Software Support
    • Matrix
      • Cilk Plus - /usr/local/gcc/gcc-cilk/bin/g++ - version 4.9.0 experimental
      • TBB - /usr/local/gcc/tbb - version 4.1 update 4 (20130613)
    • T2108
      • Matrix Image (as above)
      • CUDA 5.5 July 2013 - supports Visual Studio 2012