GPU610/DPS915

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Course Descriptions

GPU610 - Parallel Programming Fundamentals

  • 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.
  • Course Outline

DPS915 - Introduction to Parallel 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 and develop a CPU+GPU application for a client.

Common Material

External Links

The Project

  • The course project is a three-stage, team assignment. Each team consists of 3 members. In the first stage your team evaluates 6 applications and selects 3 for continued work. The evaluation includes profiling to identify the hot spots in each application. Each team member is responsible for 2 of the candidate applications. The second stage refactors the applications to use the GPU, including shared memory. The third and final stage optimizes the performance. Each team presents the results of its work during the final week of the semester.
  • Detail Specifications
    1. Selection and Assessment
    2. GPU Programming
    3. Optimization
  • Grading
    • The penalty for late submission is 30% of the assignment mark. The penalty for resubmission, in the event that the original submission was not

workable is 50%. The due dates are posted in Moodle. All submissions are to be made through Moodle. 

NV CUDA Teaching Center Small.jpg

Evaluation

  • Assignment 30%
  • Workshops 20%
  • Test 20%
  • Exam 30%

Final Submission Requirements

  • Under construction

Resources

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