Revision as of 16:11, 12 September 2016

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Course Material

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

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.

@@ Line 26: / Line 26: @@
 *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w5.html Threading Building Blocks]
 *# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w6.html Vectorization]
-*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w7.html Data Decomposition]
+*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w7.html Fork Join]
-*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w8.html Scatter Gather]
+*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w8.html Data Decomposition]
-*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w9.html Fork Join]
+*# [https://scs.senecac.on.ca/~gpu621/pages/workshops/w9.html Scatter Gather]
 *# [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 50% of the workshop mark.
+* Grading - The due date for each workshop is noted in MySeneca.  The penalty for late submission is 30% of the workshop mark.
 == Evaluation ==