ECE408 / CS483 / CSE408:
Applied Parallel Programming
Summer 2025

Announcements

• Welcome to ECE408 / CS483 / CSE408! I am looking forward to working with you!
• Follow this link ASAP to get your accounts on Delta and Github set up for use--do so NO LATER THAN the first day of class so that you can get Lab 0 done on time.
• We will use Canvas for distributing grade information (only).
• Join Piazza to follow further announcements and discussions.
• Exams will be held online. You will need a working camera and an internet connection. For dates and times, please see the course timeline.
• Please read the course policy on use of outside tools, including AI.
• Here is the Zoom link for the lectures (log in to Zoom, then follow the link; UPDATED after first lecture).

Course Information

• The textbook is shown on this web page (Amazon). Illinois students have free access through this link. You can also find the third edition, and the fifth edition may come out soon.
• Timeline
• Assignments (labs/MPs) and final project will be distributed, completed, and graded using NCSA's Delta system and Github (see second announcement at top of page, just after the welcome, for directions).
• To request an extension for a lab or project checkpoint (other than the last), fill out this form before the deadline.
• Quizzes and exams will be on PrairieLearn.

Staff and Office Hours

Office hours will start in the first week of classes.

Steve Lumetta		lumetta@illinois.edu	Tu 9 a.m.-11 a.m. (Zoom link)
Hanwen "Howie" Liu		hanwenl4@illinois.edu	Sat 2 p.m.-4 p.m. (Zoom link)

Exam Study Materials

Note that your exams will be taken through PrairieLearn, so the format will not be the same as those provided here.

• Exam 1
• Prof. Lumetta's exam from Spring 2019; solve first, discuss with friends, then look here. 3.6 was meant to ask about tile_P rather than mask_P.
• 2012 practice exam
• Fall 2016 exam
• Fall 2017 exam
• Study Guide from S19
• Exam 2
• Prof. Lumetta's exam from Spring 2019; sorry, no solution is available; please note that your exam will be quite different in format.
• 2012 practice exam
• Fall 2016 exam (with solutions)
• Fall 2017 exam (with solutions)
• Study Guide from S19

Lecture Videos and Slides

The slides below are in order of presentation, but the numbering does not generally correspond to lectures. Recordings will appear in MediaSpace if you search, or just follow the links below (you may need to log in, but otherwise they're public).

• Exam 1 Material
• Slide Deck 1: Introduction (x4)
• Recording: Lecture 1 -- Monday 16 June (slide deck 1)
• Slide Deck 2: CUDA Introduction (x4)
• Slide Deck 3: CUDA Parallelism Model (x4)
• Recording: Lecture 2 -- Wednesday 18 June (slide decks 1, 2, and 3)
• Slide Deck 4: CUDA Memory Model (x4)
• Recording: Lecture 3 -- Monday 23 June (slide decks 3 and 4)
• Slide Deck 5: CUDA Tiled Matrix Multiplication (x4)
• Slide Deck 6: More on Tiling (x4)
• Recording: Lecture 4 -- Wednesday 25 June (slide decks 5 and 6)
• Slide Deck 7: Dynamic Random Access Memory (DRAM) (x4)
• Slide Deck 8: Convolution and Constant Memory (x4)
• Recording: Lecture 5 -- Monday 30 June (slide decks 7 and 8)
• Recording: Lecture 6 -- Wednesday 2 July (slide decks 8 and 9)
• *** REMAINING SLIDE MATERIAL WILL BE COVERED ON EXAM 2 ***
• Exam 2 Material
• Slide Deck 9: Tiled Convolution (x4)
• Recording: Lecture 6 -- Wednesday 2 July (slide decks 8 and 9)
• Slide Deck 10: Tiled Convolution Analysis (x4)
• Slide Deck 11: Reduction Trees (x4)
• Recording: Lecture 7 -- Monday 7 July (slide decks 9, 10, and 11)
• Slide Deck 12: Parallel Prefix, or Scan (x4)
• Recording: Lecture 8 -- Wednesday 9 July (slide decks 11 and 12)
• Slide Deck 13: Atomic Operations and Histograms (x4)
• Recording: Lecture 9 -- Monday 14 July (slide decks 12 and 13)
• Slide Deck 14: Parallel Sparse Methods (x4)
• Slide Deck 15: Parallel Sparse Methods (Part 2) (x4)
• Recording: Lecture 10 -- Wednesday 16 July (slide decks 13, 14, and 15)
• Slide Deck 16: Machine and Deep Learning (x4)
• Recording: Lecture 11 -- Monday 21 July (slide decks 15 and 16)
• Slide Deck 17: Feedforward Networks and Gradient Descent (x4)
• Slide Deck 18: Computation in Deep Neural Networks (x4)
• Recording: Lecture 12 -- Wednesday 23 July (slide decks 17 and 18)
• Slide Deck 19: GPUs in the PC Architecture (x4)
• Recording: Lecture 13 -- Monday 28 July (slide decks 18 and 19)
• Slide Deck 20: GPU Data Transfer (x4)
• Recording: Guest Lecture by Samiran Kawtikwar (and slide decks 19 and 20) -- Wednesday 30 July 2025
• Recording: Last Summer's Guest Lecture by Kun Wu -- Tuesday 23 July 2024
• Slide Deck 21: Tensor Operations (x4)
• Slide Deck 22: Alternatives to CUDA (x4)
• Recording: Lecture 15 -- Monday 4 August (slide decks 20, 21, and 22)
• Recording: Lecture 16 -- Wednesday 6 August (slide deck 22)
• Additional Untested Material
• Extra Slide Deck 1: A Historical Perspective (x4)
• Extra Slide Deck 2: Generalizing Parallelism (x4)
• Recording: Lecture 16 -- Wednesday 6 August (slide decks X1 and X2)

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