COMP 322: Fundamentals of Parallel Programming (Spring
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2022)
InstructorInstructors: | Mackale Joyner, DH 2063 Zoran Budimlić, DH 3003 | Head TAs: | Adrienne Li, Austin Hushower, Claire Xu, Diep Hoang, Hunena Badat, Maki Yu, Mantej Singh, Rose Zhang, Victor Song, Yidi Wang | ||
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Admin Assistant: | Annepha Hurlock, annepha@rice.edu , DH 3122, 713-348-5186 | Undergraduate TAs: |
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Piazza site: | Piazza site: | https://piazza.com/class/khclqrtu2133zo (Piazza is the preferred medium for all course communications) | Cross-listing: | ELEC 323 | |
Lecture location: | Fully OnlineHerzstein Amphitheater (online 1st 2 weeks) | Lecture times: | MWF 1:30pm 00pm - 21:25pm50pm | ||
Lab locations: | Fully OnlineKeck 100 (online 1st 2 weeks) | Lab times: | Tu 1Mon 3:30pm 00pm - 23:25pm, Th 50pm (Austin, Claire) Wed 4:50pm 30pm - 5:45pm20pm (Hunena, Mantej, Yidi, Victor, Rose, Adrienne, Diep, Maki) |
Course Syllabus
A summary PDF file containing the course syllabus for the course can be found here. Much of the syllabus information is also included below in this course web site, along with some additional details that are not included in the syllabus.
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The desired learning outcomes fall into three major areas (course modules):
1) Parallelism: functional programming, Java streams, creation and coordination of parallelism (async, finish), abstract performance metrics (work, critical paths), Amdahl's Law, weak vs. strong scaling, data races and determinism, data race avoidance (immutability, futures, accumulators, dataflow), deadlock avoidance, abstract vs. real performance (granularity, scalability), collective & point-to-point synchronization (phasers, barriers), parallel algorithms, systolic algorithms.
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3) Locality & Distribution: memory hierarchies, locality, cache affinity, data movement, message-passing (MPI), communication overheads (bandwidth, latency), MapReduce, accelerators, GPGPUs, CUDA, OpenCL.
To achieve these learning outcomes, each class period will include time for both instructor lectures and in-class exercises based on assigned reading and videos. The lab exercises will be used to help students gain hands-on programming experience with the concepts introduced in the lectures.
To ensure that students gain a strong knowledge of parallel programming foundations, the classes and homeworks homework will place equal emphasis on both theory and practice. The programming component of the course will mostly use the Habanero-Java Library (HJ-lib) pedagogic extension to the Java language developed in the Habanero Extreme Scale Software Research project at Rice University. The course will also introduce you to real-world parallel programming models including Java Concurrency, MapReduce, MPI, OpenCL and CUDA. An important goal is that, at the end of COMP 322, you should feel comfortable programming in any parallel language for which you are familiar with the underlying sequential language (Java or C). Any parallel programming primitives that you encounter in the future should be easily recognizable based on the fundamentals studied in COMP 322.
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- Module 1 handout (Parallelism)
- Module 2 handout (Concurrency)There is no lecture handout for Module 3 (Distribution and Locality). The instructors will refer you to optional resources to supplement the lecture slides and videos.
There are also a few optional textbooks that we will draw from during the course. You are encouraged to get copies of any or all of these books. They will serve as useful references both during and after this course:
- Fork-Join Parallelism with a Data-Structures Focus (FJP) by Dan Grossman (Chapter 7 in Topics in Parallel and Distributed Computing)
- Java Concurrency in Practice by Brian Goetz with Tim Peierls, Joshua Bloch, Joseph Bowbeer, David Holmes and Doug Lea
- Principles of Parallel Programming by Calvin Lin and Lawrence Snyder
- The Art of Multiprocessor Programming by Maurice Herlihy and Nir Shavit
Lecture Schedule
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Finally, here are some additional resources that may be helpful for you:
- Slides titled "MPI-based Approaches for Java" by Bryan Carpenter
Week | Day | Date (2022 |
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Lecture Schedule
Week | Day | Date (2021) | Lecture | Assigned Reading | Assigned Videos (see Canvas site for video links) | In-class Worksheets | Slides | Work Assigned | Work Due | Worksheet Solutions | |||||||||||||
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1 | Mon | Jan 2510 | Lecture 1: Task Creation and Termination (Async, Finish) | Module 1: Section 1.1 | Topic 1.1 Lecture, Topic 1.1 DemonstrationIntroduction |
| worksheet1 | lec1-slides | worksheet1 | lec1-slides |
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| WS1-solution | ||||||||||
| Wed | Jan 2712 | Lecture 2: Computation Graphs, Ideal Parallelism | Module 1: Sections 1.2, 1.3 | Topic 1.2 Lecture, Topic 1.2 Demonstration, Topic 1.3 Lecture, Topic 1.3 Demonstration | worksheet2 | lec2-slides | Homework 1 |
| Functional Programming | GList.java | worksheet2 | lec02-slides |
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| WS2-solution | |||||||
Fri | Jan 2914 | Lecture 3: Abstract Performance Metrics, Multiprocessor Scheduling | Module 1: Section 1.4 | Topic 1.4 Lecture, Topic 1.4 Demonstration | worksheet3 | Higher order functions | worksheet3 | lec3-slides lec3-slides |
| WS3-solution | |||||||||||||
2 | Mon | Jan 17 | No class: MLK | ||||||||||||||||||||
| Wed | Jan 19 | Lecture 4: Lazy Computation | LazyList.java Lazy.java | Feb 01 | Lecture 4: Parallel Speedup and Amdahl's Law | Module 1: Section 1.5 | Topic 1.5 Lecture, Topic 1.5 Demonstration | worksheet4 | lec4-slides | Quiz for Unit 1 | WS4-solution | |||||||||||
| WedFri | Feb 03Jan 21 | Lecture 5: | Future Tasks, Functional Parallelism ("Back to the Future")Java Streams | Module 1: Section 2.1 | Topic 2.1 Lecture, Topic 2.1 Demonstrationworksheet5 | lec5-slides | Homework 1 | WS5-solution | ||||||||||||||
3 | FriMon | Feb 05Jan 24 | Lecture 6: Finish Accumulators Map Reduce with Java Streams | Module 1: Section 2.34 | Topic 2.3 4 Lecture, Topic 2.3 4 Demonstration | worksheet6 | lec6-slides |
| WS6-solution | ||||||||||||||
| 3Wed | MonJan 26 | Feb 08 | Lecture 7: | Map ReduceFutures | Module 1: Section 2.41 | Topic 2. | 41 Lecture , Topic 2. | 41 Demonstration | worksheet7 | lec7-slidesHomework 2 |
| Homework 1 | WS7-solution | |||||||||
| WedFri | Feb 10Jan 28 | Lecture 8: Data Races, Functional & Structural Determinism Computation Graphs, Ideal Parallelism | Module 1: Section Sections 1.2.5, 21.63 | Topic 1.2 .5 Lecture, Topic 1.2 .5 Demonstration, Topic 21.6 3 Lecture, Topic 21.6 3 Demonstration | worksheet8 | lec8-slides | Quiz for Unit 1 | WS8-solution | ||||||||||||||
4 | Mon
| Fri | Feb 12 | Jan 31 | Lecture 9: Java’s Fork/Join LibraryAsync, Finish, Data-Driven Tasks | Module 1: Sections 2Section 1. 71, 24. 85
| Topic 21. 7 Lecture1 Lecture, Topic 1.1 Demonstration, Topic 24. 8 Lecture5 Lecture, Topic 4.5 Demonstration | worksheet9 | lec9-slidesslides | Quiz for Unit 2 | WS9-solution | ||||||||||||
4 | MonWed | Feb | 1502 | Lecture 10: | Loop-Level Parallelism, Parallel Matrix Multiplication Event-based programming model
| Module 1: Sections 3.1, 3.2 | Topic 3.1 Lecture , Topic 3.1 Demonstration , Topic 3.2 Lecture, Topic 3.2 Demonstration | worksheet10 | lec10-slides | WS10-solution | |||||||||||||
WedFri | Feb 17Spring "Sprinkle" Day (no class)04 | Lecture 11: GUI programming as an example of event-based, futures/callbacks in GUI programming | worksheet11 | lec11-slides | Homework 2 | Homework 1 | WS11-solution | ||||||||||||||||
5 | FriMon | Feb | 1907 | Lecture | 11: Iteration Grouping (Chunking), Barrier Synchronization12: Scheduling/executing computation graphs Abstract performance metrics | Module 1: Sections 3.3, 3Section 1.4 | Topic | 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.1.4 Lecture | , | Topic | 31.4 Demonstration | worksheet11worksheet12 | lec11lec12-slides | Quiz for Unit 2 | WS12-solution | ||||||||
| 5 | MonWed | Feb 2209 | Lecture 12: Parallelism in Java Streams, Parallel Prefix Sums 13: Parallel Speedup, Critical Path, Amdahl's Law | Module 1: Section 31.75 | Topic Topic 3.7 Java Streams1.5 Lecture , Topic 31. 7 Java Streams5 Demonstration | worksheet12worksheet13 | lec12lec13-slides | WS13-solution | ||||||||||||||
| WedFri | Feb | 2411 | No class: Spring Recess
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6 | Mon | Feb 14 | Lecture 14: Accumulation and reduction. Finish accumulators | Module 1: Section 2.3 | Topic 2.3 Lecture Topic 2.3 Demonstration | worksheet14 | lec14-slides | WS14-solution | |||||||||||||||
| Wed | Feb 16 | Lecture 15: Recursive Task Parallelism | worksheet15 | lec15-slides |
| WS15-solution | ||||||||||||||||
Fri | Feb 18 | Lecture 16: Data Races, Functional & Structural Determinism | Module 1: Sections 2.5, 2.6 | Topic 2.5 Lecture , Topic 2.5 Demonstration, Topic 2 | Lecture 13: Iterative Averaging Revisited, SPMD pattern | Module 1: Sections 3.5, 3.6 | Topic 3.5 Lecture , Topic 3.5 Demonstration , Topic 3.6 Lecture, Topic 32.6 Demonstration | worksheet13worksheet16 | lec13lec16-slides | Homework 3 (includes one intermediate checkpoint) Quiz for Unit 3 | Homework 2 | WS16-solution | |||||||||||
7 | FriMon | Feb 2621 | Lecture 1417: Data-Driven Tasks | Module 1: Sections 4.5 | Topic 4.5 Lecture Topic 4.5 Demonstration | worksheet14 | lec14-slidesMidterm Review | lec17-slides | |||||||||||||||
| 6Wed | Mon | Mar 01 | Spring "Sprinkle" Day (no class)Feb 23 | Lecture 18: Limitations of Functional parallelism. | worksheet18 | lec18-slides | WS18-solution | |||||||||||||||
| WedFriMar 03 | Feb 25 | Lecture 15: Point-to-point Synchronization with Phasers | Module 1: Section 4.2, 4.3 | Topic 4.2 Lecture , Topic 4.2 Demonstration, Topic 4.3 Lecture, Topic 4.3 Demonstration | worksheet15 | 19: Fork/Join programming model. OS Threads. Scheduler Pattern | Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration, | worksheet19 | lec19lec15-slides | WS19-solution | ||||||||||||
8 | FriMon | Mar 05Feb 28 | Lecture 16: Pipeline Parallelism, Signal Statement, Fuzzy Barriers | Module 1: Sections 4.4, 4.1 | Topic 4.4 Lecture , Topic 4.4 Demonstration, Topic 4.1 Lecture, Topic 4.1 Demonstration | worksheet16 | lec16-slides | Quiz for Unit 4 | Quiz for Unit 3 | ||||||||||||||
7 | Mon | Mar 08 | Lecture 17: Midterm Review | lec17-slides | |||||||||||||||||||
| Wed | Mar 10 | Lecture 18: Abstract vs. Real Performance | worksheet18 | lec18-slides | ||||||||||||||||||
20: Confinement & Monitor Pattern. Critical sections | Module 2: Sections 5.1, 5.2, 5.6 | Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration | worksheet20 | lec20-slides | WS20-solution | ||||||||||||||||||
| Wed | Mar 02 | Lecture 21: Atomic variables, Synchronized statements |
| Fri | Mar 12 | Lecture 19: Critical Sections, Isolated construct (start of Module 2) | Module 2: Sections 5. 14, 57.2 , 5.6, | Topic 5.1 4 Lecture, Topic 5.1 4 Demonstration, Topic 57.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration | worksheet19 | lec19-slides | Homework 3, Checkpoint-1 | 8 | worksheet21 | lec21-slides | WS21-solution | |||||||
| Fri | Mar 04 | Lecture 22: Parallel Spanning Tree, other graph algorithms | worksheet22 | lec22-slides | Homework 4 | Homework 3 | WS22-solution | |||||||||||||||
9 | Mon | Mar 07 | Lecture 23: Java Threads and Locks | Mon | Mar 15 | Lecture 20: Parallel Spanning Tree algorithm, Atomic variables | Module 2: Sections 57.3, 5.4, 5.5 | Topic 5.3 Demonstration, Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 5.5 Lecture, Topic 5.5 Demonstration | worksheet20 | 1, 7.3 | Topic 7.1 Lecture, Topic 7.3 Lecture | worksheet23 | lec23lec20-slides |
| WS23-solution | ||||||||
| Wed | Mar 1709 | Lecture 21: Actors24: Java Locks - Soundness and progress guarantees | Module 2: 6.1, 6.27.5 | Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet21 | 7.5 Lecture | worksheet24 | lec24lec21-slides |
| WS24-solution | ||||||||||||
| Fri | Mar 1911Lecture 22: Actors (contd) | Lecture 25: Dining Philosophers Problem | Module 2: 6.3, 6.4, 6.57.6 | Topic 67.3 Lecture, Topic 6 .3 Demonstration, Topic 6.4 Lecture , Topic 6.4 Demonstration, Topic 6.5 Lecture, Topic 6.5 Demonstration | worksheet22 | worksheet25 | lec25lec22-slides | Quiz for Unit 4 |
| WS25-solution | ||||||||||||
9 | Mon | Mar | 2214 | Lecture 23: Actors (contd) | Module 2: 6.6 | Topic 6.6 Lecture, Topic 6.6 Demonstration | lec23-slides | Quiz for Unit 5No class: Spring Break |
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Wed | Mar 24 | Lecture 24: Java Threads, Java synchronized statement | Module 2: 7.1, 7.2 | Topic 7.1 Lecture, Topic 7.2 Lecture | Mar 16 | No class: Spring Break | lec24-slides |
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| Fri | Mar | 2618 | Spring "Sprinkle" Day (no class)No class: Spring Break |
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10 | Mon | Mar 29 | Lecture 25: Java Threads, Java synchronized statement (contd), wait/notify | Module 2: 7.1, 7.2 | Topic 7.1 Lecture, Topic 7.2 Lecture | lec25 | 21 | Lecture 26: N-Body problem, applications and implementations | worksheet26 | lec26-slides | WS26-solution | ||||||||||||
| Wed | Mar 31 | Lecture 26: Java Threads (exercise) | 23 | Lecture 27: Read-Write Locks, Linearizability of Concurrent Objects | Module 2: 7.3, 7.4 | Topic 7.3 Lecture, Topic 7.4 Lecture | worksheet27 | lec27-slides |
| lec26-handout | Homework 3 (all)WS27-solution | |||||||||||
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| Fri | Apr 02Mar 25 | Lecture | 27: Java Locks 28: Message-Passing programming model with Actors | Module 2: 6.1, 6.2 | Topic 6.1 Lecture, Topic 6.1 Demonstration, Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet28 | lec28-slides |
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| WS28-solution | Module 2: 7.3 | Topic 7.3 Lecture | lec27-slides | Quiz for Unit 6 | Quiz for Unit 5 | ||||||
11 | Mon | Apr 05Mar 28 | Lecture 29: Active Object Pattern. Combining Actors with task parallelism | Module 2: 6.3, 6 28: Linearizability of Concurrent ObjectsModule 2: 7.4 | Topic | 76.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture | , Topic 6.4 Demonstration | worksheet29 | lec29-slides | lec28-slides | Homework 4 (includes one intermediate checkpoint) |
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| WS29-solution | |||||||||
| WedApr | 07Mar 30 | Lecture 29: Java Locks (exercise)30: Task Affinity and locality. Memory hierarchy | worksheet30 | lec29lec30-handout slides |
| WS30-solution | ||||||||||||||||
| Fri | Apr 0901 | Lecture 30: Safety and Liveness Properties, Java Synchronizers, Dining Philosophers Problem | Module 2: 7.5, 7.6 | Topic 7.5 Lecture, Topic 7.6 Lecture | lec30-slides | Quiz for Unit 7 | Quiz for Unit 6 | 31: Data-Parallel Programming model. Loop-Level Parallelism, Loop Chunking | Module 1: Sections 3.1, 3.2, 3.3 | Topic 3.1 Lecture, Topic 3.1 Demonstration , Topic 3.2 Lecture, Topic 3.2 Demonstration, Topic 3.3 Lecture, Topic 3.3 Demonstration | worksheet31 | lec31-slides | Homework 5 | Homework 4 | WS31-solution | |||||||
12 | Mon | Apr 1204 | Lecture 31: Message Passing Interface (MPI), (start of Module 3) | Topic 8.1 Lecture, Topic 8.2 Lecture, Topic 8.3 Lecture | 32: Barrier Synchronization with Phasers | Module 1: Section 3.4 | Topic 3.4 Lecture, Topic 3.4 Demonstration | worksheet32 | lec32lec31-slides |
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| WS32-solution | |||||||||||
| Wed | Apr 1406 | Lecture 32: Message Passing Interface (MPI, contd) | Topic 8.4 Lecture | lec32-slides | Homework 4 Checkpoint-1 | 33: Stencil computation. Point-to-point Synchronization with Phasers | Module 1: Section 4.2, 4.3 | Topic 4.2 Lecture, Topic 4.2 Demonstration, Topic 4.3 Lecture, Topic 4.3 Demonstration | worksheet33 | lec33-slides |
| WS33-solution | ||||||||||
| Fri | Apr 1608 | Lecture 33: Message Passing Interface (MPI, contd) | Topic 8.5 Lecture, Topic 8 Demonstration Video | 34: Fuzzy Barriers with Phasers | Module 1: Section 4.1 | Topic 4.1 Lecture, Topic 4.1 Demonstration | worksheet34 | lec34lec33-slides |
| WS34-solution | ||||||||||||
13 | Mon | Apr 1911 | Lecture 34: Task Affinity with Places35: Eureka-style Speculative Task Parallelism |
| worksheet35 | lec34lec35-slides | Quiz for Unit 8 | Quiz for Unit 7 |
| WS35-solution | |||||||||||||
Wed | Apr | 2113 | Lecture | 35: Eureka-style Speculative Task Parallelism36: Scan Pattern. Parallel Prefix Sum |
| worksheet36 | lec35lec36-slides | WS36-solution | |||||||||||||||
Fri | Apr | 2415 | Lecture | 3637: | Algorithms based onParallel Prefix | (Scan) operationsSum applications | worksheet37 | lec36lec37-slides | |||||||||||||||
14 | Mon | Apr | 26TBD18 | Lecture 38: Overview of other models and frameworks | lec38-slides | ||||||||||||||||||
Wed | Apr 2820 | Lecture 3839: Course Review (Lectures 19-3438) | lec38lec39-slides | Homework 4 (all) | |||||||||||||||||||
Fri | Apr 30TBD22 | Lecture 40: Course Review (Lectures 19-38) | lec40-slides | Quiz for Unit 8 | Homework 5 |
Lab Schedule
Lab # | Date (20212022) | Topic | Handouts | Examples | 0|||||||||||
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1 | Jan 10 | Infrastructure | Setupsetup | lab0-handout | 1 | Jan 26 | Async-Finish Parallel Programming with abstract metrics | lab1-handout | - | Feb 02 | No lab this week | ||||
2 | Feb 09 | FuturesJan 17 | Functional Programming | lab2-handout | |||||||||||
3 | Feb 16 | Jan 24 | Java Streams Cutoff Strategy and Real World Performance | lab3-handout | |||||||||||
4 | Feb 23Jan 31 | DDFsFutures | lab4- | handouthandout | |||||||||||
5 | Mar 02 | No lab this week | Feb 07 | Data-Driven Tasks | lab5-handout | ||||||||||
56 | Mar 09 | Loop-level Parallelism | lab5-handout | lab5-intro | - | Mar 16Feb 14 | Async / Finish | lab6-handout | |||||||
- | Feb 21 | No lab this week ( | Spring "Sprinkle" DayMidterm) | ||||||||||||
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| Isolated Statement and Atomic Variables | Feb 28 | Recursive Task Cutoff Strategy | lab7-handout | ||||||||||
-8 | Mar 07 | Actors | Java Threads | lab8-handout | |||||||||||
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| Mar 14 | No lab this week (Spring Break)Java Threads, Java Locks | ||||||||||||
9 | Mar 21 | Concurrent Lists | lab9-handout | ||||||||||||
10 | Mar 28 | Actors | lab10-handout | ||||||||||||
11 | Apr 04 | Loop Parallelism | lab11-handout | Message Passing Interface (MPI) | - |
| Apache Spark | ||||||||
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| Apr 11 | No lab this weekEureka-style Speculative Task Parallelism | ||||||||||||
- | Java's ForkJoin Framework | Apr 18 | No lab this week |
Grading, Honor Code Policy, Processes and Procedures
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The slip day policy for COMP 322 is similar to that of COMP 321. All students will be given 3 slip days to use throughout the semester. When you use a slip day, you will receive up to 24 additional hours to complete the assignment. You may use these slip days in any way you see fit (3 days on one assignment, 1 day each on 3 assignments, etc.). Slip days will be tracked using the README.md file. Other than slip days, no extensions will be given unless there are exceptional circumstances (such as severe sickness, not because you have too much other work). Such extensions must be requested and approved by the instructor (via e-mail, phone, or in person) before the due date for the assignment. Last minute requests are likely to be denied.
Labs must be submitted by the following Wednesday at 4:30pm. Labs must be checked off by a TA by the following Monday at 11:59pm.
Worksheets should be completed by the deadline listed in Canvas before the start of the following class (for full credit) so that solutions to the worksheets can be discussed in the next class.
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