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{{GPU610/DPS915 Index | 2012320191}}
Please help make this page resourceful for all GPU610/DPS915 students to use!
= Course Descriptions Material =
== GPU610 - Parallel Programming Fundamentals ==
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*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.
* [https://scsict.senecac.onsenecacollege.ca/course/gpu610 Course Outline]</td><td>[[Image:NV_CUDA_Teaching_Center_Small.jpg]]</td></tr></table>
== DPS915 - Introduction to Parallel Programming ==
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*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.
* [https://scsict.senecac.onsenecacollege.ca/course/dps915 Course Outline]</td><td>[[Image:NV_CUDA_Teaching_Center_Small.jpg]]</td></tr></table>
== External Links ==
* [https://scs.senecac.on.ca/~gpu610/pages/content/index.html Course Web Site – Lecture Notes]
* [https://cs.senecac.on.ca/~gpu610/pages/timeline.html Course Web Site – Timeline]
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== The 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 [https://open.senecac.on.ca/cms/course/view.php?id=342 536 Moodle].
* Detail Specifications
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w1.html Initial AssessmentProfile]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w2.html Linear Algebra using BLAS]
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w3.html Device Query and Selection]
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w4.html A Simple Device OperationcuBLAS]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w5.html Dot ProductThrust]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w6.html Matrix ProductA Simple Kernel]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w7.html Matrix Product using ThrustReduction]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w8.html Matrix Product using cuBlasThread Divergence]*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w9.html Matrix Product using StreamsCoalesced Memory Access]
*# [https://scs.senecac.on.ca/~gpu610/pages/workshops/w10.html CUDA to OpenCL]
* Grading - The due date for each workshop is noted in MySeneca. The penalty for late submission is 20% of the workshop mark; 50% for very late submission.
== The Project Assignments ==<table><tr><td> * 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*# [https://scs.senecac.on.ca/~gpu610/pages/assignments/a1.html Selection Select and AssessmentAssess]*# [https://scs.senecac.on.ca/~gpu610/pages/assignments/a2.html GPU ProgrammingParallelize]*# [https://scs.senecac.on.ca/~gpu610/pages/assignments/a3.html OptimizationOptimize]* GradingThe 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 [https://open.senecac.on.ca/cms/course/view.php?id=342 Moodle]. All submissions are to be made through [https://open.senecac.on.ca/cms/course/view.php?id=342 Moodle]. </td><td>[[Image:NV_CUDA_Teaching_Center_Small.jpg]]</td></tr></table>
== Evaluation ==
* Assignment 30Assignments and Presentation 20%* Workshops 2030%* Test 20Option 1: Tests 50%* Option 2: Tests 35% + Exam 3015% == Final Submission Requirements ==* Under construction<!-- When ready to submit your project:# Finalize your modifications in trunk.# Create a directory in trunk called: '''"SubmissionLogs"'''# For each member of the team create a text file named as '''"YourSenecaEmailId.txt"''' in the '''"SubmissionLogs"''' directory. In this text file, in a point form, specify in detail, all the tasks you have done for the group project.# Branch (copy) the whole project including the SubmissionLogs directory and its text files into tags directory under '''"prj1.0"'''.# If final adjustments are needed after these steps, repeat everything from step one but branch the trunk into a new directory in tags as '''prj1.1, prj1.2''', etc.#:(for marking purposes, your instructor will consider your last revision as your submission)-->
= Resources =
* Software Support
** [http://developer.nvidia.com/cuda-downloads CUDA Toolkit]
** Get [https://inside.senecacollege.ca/its/software/index.html Visual Studio 2017] | Select Software Downloads | Go To Visual Studio 2013 Ultimate 2.82GB | Download iso | Burn, if error burn again | Finally, install
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* Wikis
** [http://en.wikipedia.org/wiki/Wikipedia:How_to_edit_a_page How To edit Wiki pages]
** [http://en.wikipedia.org/wiki/Wikipedia:Cheatsheet How To edit Wiki Cheatsheet]
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** [http://svnbook.red-bean.com/ SVN book at red-bean.com] or download [https://cs.senecac.on.ca/~fardad.soleimanloo/oop344/notes/svn-book.pdf the PDF from here].
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