edX site | Autograder Guide |
COMP 322: Fundamentals of Parallel Programming (Spring
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2023)
Instructor: | Mackale Joyner, DH 2063 |
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| TAs: |
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| Mohamed Abead, Chase Hartsell, Taha Hasan, Harrison Huang, Jerry Jiang, Jasmine Lee, Michelle Lee, Hung Nguyen, Quang Nguyen, Ryan Ramos, Oscar Reynozo, Delaney Schultz, Tina Wen, Raiyan Zannat, Kailin Zhang | |
Piazza site: |
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spring2023/comp322 (Piazza is the preferred medium for all course communications) | Cross-listing: | ELEC 323 |
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Lecture location: | Herzstein Amphitheater |
Lecture times: | MWF 1:00pm - 1:50pm | |
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Lab locations: | Mon (Herzstein Amp), Tue (Keck 100 |
) | Lab times: | Mon 3:00pm - 3:50pm (Raiyan, Oscar, Mohamed, Ryan, Michelle, Taha) |
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Tue 4: |
00pm - |
4: |
50pm (Tina, Delaney, Chase, Hung, Jerry, Kailin, Jasmine) |
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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There are no required textbooks for the class. Instead, lecture handouts are provided for each module as follows. You are expected to read the relevant sections in each lecture handout before coming to the lecture. We will also provide a number of references in the slides and handouts.The links to the latest versions of the lecture handouts are included below:
There
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There are also a few 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
Finally, here are some additional resources that may be helpful for you:
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Lecture Schedule
Week | Day | Date ( |
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2023) | Lecture | Assigned Reading | Assigned Videos (see Canvas site for video links) | In-class Worksheets | Slides | Work Assigned | Work Due |
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| Worksheet Solutions | ||
|---|---|---|
1 | Mon | Jan |
09 | Lecture 1: |
Introduction | worksheet1 | lec1- |
| slides | WS1-solution |
Wed | Jan |
11 | Lecture 2: |
Functional Programming | worksheet2 |
| lec02-slides |
Homework 1
| WS2-solution | ||
| Fri | Jan |
| 13 | Lecture 3: |
| Higher order functions | worksheet3 |
| lec3- |
2
Mon
Jan 17
Lecture 4: Parallel Speedup and Amdahl's Law
Wed
Jan 19
| slides | WS3-solution | ||||||||||
2 | Mon | Jan 16 | No class: MLK | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
Wed | Jan 18 | Lecture 4: Lazy Computation | worksheet4 | lec4-slides | WS4-solution | ||||||
Fri | Jan 20 | Lecture 5: Java Streams | worksheet5 | lec5-slides | Homework 1 | WS5-solution | |||||
| 3 | Mon | Jan 23 | Lecture 6: Map Reduce with Java Streams |
| Module 1: Section 2. |
| 4 | Topic 2. |
| 4 Lecture, Topic 2. |
| 4 Demonstration |
| worksheet6 |
| lec6-slides |
Fri
Jan 21
| WS6-solution | |||
Wed | Jan 25 | Lecture 7: Futures |
| Module 1: Section 2. |
| 1 | Topic 2. |
| 1 Lecture , Topic 2. |
| 1 Demonstration |
| worksheet7 |
| lec7-slides |
| WS7-solution | |||
Fri | Jan 27 | Lecture 8: Async, Finish, Computation Graphs |
| Module 1: |
| Sections 1.1, 1.2 | Topic |
| 1. |
| 1 Lecture, Topic 1.1 Demonstration, Topic 1.2 Lecture, Topic 1. |
| 2 Demonstration |
| worksheet8 |
| lec8-slides |
| WS8-solution |
4 |
|---|
| Mon |
| Jan 30 |
Wed
Jan 26
| Lecture 9: Ideal Parallelism, Data-Driven Tasks | Module 1: Section |
1. |
3, |
4. |
5 | Topic |
1. |
3 Lecture, Topic |
1. |
3 Demonstration, Topic |
4. |
5 Lecture, Topic |
4. |
5 Demonstration |
worksheet9 |
| lec9- |
Homework 2
Fri
Jan 28
Lecture 9: Java’s Fork/Join Library
4
Mon
Feb 07
Wed
Feb 09
Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization
Topic 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.4 Lecture , Topic 3.4 Demonstration
Fri
Feb 11
Lecture 12: Data-Driven Tasks
Module 1: Sections 4.5
Topic 4.5 Lecture Topic 4.5 Demonstration
Mon
Feb 14
Wed
Lecture 13: Parallelism in Java Streams, Parallel Prefix Sums
Homework 3 (includes one intermediate checkpoint)
Lecture 14: Iterative Averaging Revisited, SPMD pattern
7
Mon
Feb 21
Lecture 17: Midterm Review
Wed
Feb 23
Lecture 18: Limitations of Functional parallelism.
Abstract vs. real performance. Cutoff Strategy
Fri
Lecture 19: Data Races, Functional & Structural Determinism
8
Mon
Feb 28
| slides | WS9-solution | ||||||||||
| Wed | Feb 01 | Lecture 10: Event-based programming model | worksheet10 | lec10-slides | Homework 1 | WS10-solution | |||||
| Fri | Feb 03 | Lecture 11: GUI programming, Scheduling/executing computation graphs | Module 1: Section 1.4 | Topic 1.4 Lecture , Topic 1.4 Demonstration | worksheet11 | lec11-slides | Homework 2 | WS11-solution | |||
| 5 | Mon | Feb 06 | Lecture 12: Abstract performance metrics, Parallel Speedup, Amdahl's Law | Module 1: Section 1.5 | Topic 1.5 Lecture , Topic 1.5 Demonstration | worksheet12 | lec12-slides | WS12-solution | |||
Wed | Feb 08 | Lecture 13: Accumulation and reduction. Finish accumulators | Module 1: Section 2.3 | Topic 2.3 Lecture Topic 2.3 Demonstration | worksheet13 | lec13-slides | WS13-solution | ||||
Fri | Feb 10 | No class: Spring Recess | |||||||||
| 6 | Mon | Feb 13 | Lecture 14: Data Races, Functional & Structural Determinism | Module 1: Sections 2.5, 2.6 | Topic 2.5 Lecture , Topic 2.5 Demonstration, Topic 2.6 Lecture, Topic 2.6 Demonstration | worksheet14 | lec14-slides | WS14-solution | |||
Wed | Feb 15 | Lecture 15: Limitations of Functional parallelism. | worksheet15 | lec15-slides | Homework 2 | WS15-solution | |||||
| Fri | Feb 17 | Lecture 16: Recursive Task Parallelism | worksheet16 | lec16-slides | Homework 3 | WS16-solution | |||||
7 | Mon | Feb 20 | Lecture 17: Midterm Review | lec17-slides | |||||||
Wed | Feb 22 | Lecture 18: Midterm Review | lec18-slides | ||||||||
Fri | Feb 24 | Lecture 19: 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 | worksheet19 | lec19-slides | WS19-solution | ||||
8 | Mon | Feb 27 | Lecture 20: Barrier Synchronization with Phasers | Module 1: Sections 3.4 | Topic 3.4 Lecture, Topic 3.4 Demonstration | worksheet20 | lec20-slides | WS20-solution | |||
Wed | Mar 01 | Lecture 21:Stencil computation. Point-to-point Synchronization with Phasers | Module 1: Sections 4.2, 4.3 | Topic 4.2 Lecture, Topic 4.2 Demonstration, Topic 4.3 Lecture, Topic 4.3 Demonstration | worksheet21 | lec21-slides | WS21-solution | ||||
Fri | Mar 03 | Lecture 22: Fuzzy Barriers with Phasers | Module 1: Section 4.1 | Topic 4.1 Lecture, Topic 4.1 Demonstration | worksheet22 | lec22-slides | WS22-solution | ||||
9 | Mon | Mar 06 | Lecture 23: Fork/Join programming model. OS Threads. Scheduler Pattern | Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration | worksheet23 | lec23-slides | Homework 3 (CP 1) | WS23-solution | |||
Wed | Mar 08 | Lecture 24: Confinement & Monitor Pattern. Critical sections | Module 2: Sections 5.1, 5.2 |
| Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration |
| worksheet24 |
| lec24-slides |
Wed
Mar 02
Lecture 21: N-Body problem, applications and implementations
Fri
Mar 04
Lecture 22: Fork/Join programming model. OS Threads. Scheduler Pattern
| WS24-solution | |||||
Fri | Mar 10 | Lecture 25: Atomic variables, Synchronized statements | Module 2: Sections 5.4, 7.2 | Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 |
| Lecture |
| worksheet25 |
Quiz for Unit 4
9
Mon
Mar 07
Lecture 23: Locks, Atomic variables
Topic 7.3 Lecture
Wed
Mar 09
Lecture 24: Parallel Spanning Tree, other graph algorithms
Homework 3, Checkpoint-1
Fri
Mar 11
Quiz for Unit 5
Mon
Spring Break
Fri
Mar 18
Spring Break
10
Mon
Mar 21
Lecture 26: Java Locks - Soundness and progress guarantees
Wed
Mar 23
Lecture 27: Dining Philosophers Problem
Fri
Mar 25
Lecture 28: Read-Write Pattern. Read-Write Locks. Fairness & starvation
Quiz for Unit 7
11
Mon
Mar 28
Lecture 29: Task Affinity and locality. Memory hierarchy
Quiz for Unit 6
Wed
Mar 30
Lecture 30: Reactor Pattern. Web servers
Fri
Apr 01
Lecture 31: Scan Pattern. Parallel Prefix Sum, uses and algorithms
Quiz for Unit 7
12
Mon
Apr 04
Homework 4 Checkpoint-1
Wed
Apr 06
Lecture 33: Barrier Synchronization with phasers
Topic 3.4 Lecture , Topic 3.4 Demonstration
Fri
Apr 08
Lecture 34: Stencil computation. Point-to-point Synchronization with Phasers
Quiz for Unit 8
13
Mon
Apr 11
Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration
Topic 6.3 Lecture , Topic 6.3 Demonstration , Topic 6.4 Lecture, Topic 6.4 Demonstration
Lab Schedule
| lec25-slides | WS25-solution | ||||||||||
Mon | Mar 13 | No class: Spring Break | |||||||||
| Wed | Mar 15 | No class: Spring Break | |||||||||
Fri | Mar 17 | No class: Spring Break | |||||||||
10 | Mon | Mar 20 | Lecture 26: Parallel Spanning Tree, other graph algorithms | worksheet26 | lec26-slides | WS26-solution | |||||
Wed | Mar 22 | Lecture 27: Java Threads and Locks | Module 2: Sections 7.1, 7.3 | Topic 7.1 Lecture, Topic 7.3 Lecture | worksheet27 | lec27-slides | Homework 3 (CP 2) | WS27-solution | |||
Fri | Mar 24 | Lecture 28: Java Locks - Soundness and progress guarantees | Module 2: Section 7.5 | Topic 7.5 Lecture | worksheet28 | lec28-slides | WS28-solution | ||||
11 | Mon | Mar 27 | Lecture 29: Dining Philosophers Problem | Module 2: Section 7.6 | Topic 7.6 Lecture | worksheet29 | lec29-slides | WS29-solution | |||
Wed | Mar 29 | Lecture 30: Read-Write Locks, Linearizability of Concurrent Objects | Module 2: Sections 7.3, 7.4 | Topic 7.3 Lecture, Topic 7.4 Lecture | worksheet30 | lec30-slides | WS30-solution | ||||
Fri | Mar 31 | Lecture 31: Message-Passing programming model with Actors | Module 2: Sections 6.1, 6.2 | Topic 6.1 Lecture, Topic 6.1 Demonstration, Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet31 | lec31-slides | WS31-solution | ||||
12 | Mon | Apr 03 | No class | Homework 4 | Homework 3 (All) | ||||||
Wed | Apr 05 | Lecture 32: Active Object Pattern. Combining Actors with task parallelism | Module 2: Sections 6.3, 6.4 | Topic 6.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture, Topic 6.4 Demonstration | worksheet32 | lec32-slides | WS32-solution | ||||
Fri | Apr 07 | Lecture 33: Task Affinity and locality. Memory hierarchy | worksheet33 | lec33-slides | WS33-solution | ||||||
13 | Mon | Apr 10 | Lecture 34: Eureka-style Speculative Task Parallelism | worksheet34 | lec34-slides | WS34-solution | |||||
| Wed | Apr 12 | Lecture 35: Scan Pattern. Parallel Prefix Sum | worksheet35 | lec35-slides | Homework 4 (CP 1) | WS35-solution | |||||
| Fri | Apr 14 | Lecture 36: Parallel Prefix Sum applications | worksheet36 | lec36-slides | WS36-solution | ||||||
| 14 | Mon | Apr 17 | Lecture 37: Overview of other models and frameworks | lec37-slides | |||||||
| Wed | Apr 19 | Lecture 38: Course Review (Lectures 19-34) | lec38-slides | Homework 4 (All) | |||||||
| Fri | Apr 21 | Lecture 39: Course Review (Lectures 19-34) | lec39-slides |
Lab Schedule
Lab # | Date (2023) | Topic | Handouts | Examples |
|---|---|---|---|---|
1 | Jan 09 | Infrastructure setup | lab0-handout lab1-handout | |
| - | Jan 16 | No lab this week (MLK) | ||
| 2 | Jan 23 | Functional Programming | lab2-handout | |
3 | Jan 30 | Futures | lab3-handout | |
| 4 | Feb 06 | Data-Driven Tasks | lab4-handout | |
5 | Feb 13 | Async / Finish | lab5-handout | |
| - | Feb 20 | No lab this week (Midterm Exam) | ||
| 6 | Feb 27 | Loop Parallelism | lab6-handout | image kernels |
| 7 | Mar 06 | Recursive Task Cutoff Strategy | lab7-handout | |
| - | Mar 13 | No lab this week (Spring Break) | ||
| - | Mar 20 | No lab this week | ||
| 8 | Mar 27 | Java Threads | lab8-handout | |
| 9 | Apr 03 | Concurrent Lists | lab9-handout | |
| 10 | Apr 10 | Actors | lab10-handout | |
- | Apr 17 | No lab this week |
Lab #
Date (2021)
Topic
Handouts
Examples
1
Jan 10
Async-Finish Parallel Programming with abstract metrics
2
Jan 24
Futures
3
Feb 07
Cutoff Strategy and Real World Performance
Feb 14
DDFs
Feb 21
No lab this week (Midterm exam)
6
Mar 14
Isolated Statement and Atomic Variables
Apr 04
Actors
-
Apr 11
Message Passing Interface (MPI)
-
Apr 18
Apache Spark
-
Eureka-style Speculative Task Parallelism
Java's ForkJoin Framework
Grading, Honor Code Policy, Processes and Procedures
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Labs must be submitted by the following Monday Wednesday at 114:59pm30pm. Labs must be checked off by a TA.
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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