COMP 322: Fundamentals of Parallel Programming (Spring

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2025)

Course Syllabus

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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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:

• Module 1 handout (Parallelism)
• Module 2 handout (Concurrency)

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• 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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Week	Day	Date (

2022

2025)	Lecture	Assigned Reading	Assigned Videos (see Canvas site for video links)	In-class Worksheets	Slides	Work Assigned	Work Due	Worksheet Solutions

 

1	Mon	Jan

10

13	Lecture 1: Introduction

  

worksheet1

lec1-slides

 

 

WS1-solution

 

 

	Wed	Jan

12

15	Lecture 2:  Functional Programming

GList.java 

worksheet2

lec02-slides

 

 

Fri

WS2-solution

  

Fri

Jan

14

17	Lecture 3: Higher order functions

  

worksheet3

lec3-slides

 

 

WS3-solution

 

2	Mon	Jan

17

20	No class: MLK

         

	Wed	Jan

19

22	Lecture 4: Lazy Computation

LazyList.java

Lazy.java 

worksheet4

lec4-slides

  

WS4-solution

 

 

	Fri	Jan

21

24	Lecture 5: Java Streams

  worksheet5

worksheet5

lec5

lec5

-slides

Homework 1

 

WS5-solution

 

3	Mon	Jan

24

27

Lecture 6: Map Reduce with Java Streams

Module 1: Section 2.4

Topic 2.4 Lecture, Topic 2.4 Demonstration

worksheet6

lec6-slides

 

 

 

WS6-solution

 

Wed

Jan

26

29

Lecture 7: Futures

Module 1: Section 2.1

Topic 2.1 Lecture , Topic 2.1 Demonstration

worksheet7

lec7-slides

  

WS7-solution

 

 

	Fri	Jan

28

31	Lecture 8:  Async, Finish, Computation Graphs

, Ideal Parallelism

Module 1: Sections 1.

2

1, 1.

3

2

Topic 1.

2

1 Lecture, Topic 1.

2

1 Demonstration, Topic 1.

3

2 Lecture, Topic 1.

3

2 Demonstration

worksheet8

lec8

lec8-slides

  

WS8-solution

  

4	Mon

 Jan 31

Feb 03

Lecture 9: Ideal Parallelism, Data-Driven Tasks

Module 1: Section 1.

1

3, 4.5

 

Topic 1.

1

3 Lecture, Topic 1.

1

3 Demonstration, Topic 4.5 Lecture, Topic 4.5 Demonstration

worksheet9

lec9-

slides    

slides

WS9-solution

 

Wed

Feb

02

05	Lecture 10: Event-based programming model

 

   

worksheet10

lec10-slides

 

Homework 1

WS10-solution

  

	Fri	Feb

04

07	Lecture 11: GUI programming

as an example of event-based,
futures/callbacks in GUI programming

, Scheduling/executing computation graphs

Module 1: Section 1.4

Topic 1.4 Lecture , Topic 1.4 Demonstration

   

worksheet11

lec11-slides

Homework 2

Homework 1 

WS11-solution
5	Mon	Feb

07

10	Lecture 12:

Scheduling/executing computation graphs

Abstract performance metrics, Parallel Speedup, Amdahl's Law

Module 1: Section 1.

4

5

Topic 1.

4

5 Lecture , Topic 1.

4

5 Demonstration

worksheet12

lec12-slides

 

WS12-solution

   

 

Wed

	Wed	Feb 12

Feb 09

Lecture 13:

Parallel Speedup, Critical Path, Amdahl's Law

Accumulation and reduction. Finish accumulators

Module 1: Section

1

2.

5

3

Topic

1

2.

5

3 Lecture

,

Topic

1

2.

5

 

3 Demonstration

worksheet13

lec13-slides

   

	WS13-solution

Fri

Feb

11

14	No class: Spring Recess

 

6

 

Mon

       6

Mon

Feb 14

Feb 17

Lecture 14: Data Races, Functional & Structural Determinism

Lecture 14: Accumulation and reduction. Finish accumulators

Module 1:

Section

Sections 2.5, 2.

3

6

Topic 2.

3 Lecture

5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.6 Lecture,  Topic 2.

3  

6 Demonstration

worksheet14

lec14-slides

    

WS14-solution
	Wed	Feb

16

19	Lecture 15:

Recursive Task Parallelism    

Limitations of Functional parallelism. Abstract vs. real performance. Cutoff Strategy

worksheet15

lec15-slides

 

 

    

	Homework 2	WS15-solution
	Fri	Feb

18Module 1: Section 1.1Topic 1.1 Lecture , Topic 1.1 Demonstrationworksheet16

21	Lecture 16:

 Lightweight task parallelism. Finish/async

Recursive Task Parallelism

worksheet16

lec16-slides

Homework 3

Homework 2  

	WS16-solution
7	Mon	Feb

21

24	Lecture 17: Midterm Review

   

lec17-slides

 

	Wed

   

 

Wed

Feb 23

Lecture 18: Limitations of Functional parallelism.
Abstract vs. real performance. Cutoff Strategy

   lec18-slides    

 

Fri

Feb 25 Lecture 19: Data Races, Functional & Structural Determinism

Feb 26	Lecture 18: Midterm Review				lec18-slides
	Fri	Feb 28	Lecture 19:  Fork/Join programming model		Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration	worksheet19	lec19-slides			WS19-solution
8	Mon	Mar 03	Lecture 20: Data-Parallel Programming model. Loop-Level Parallelism, Loop Chunking	Module 1: Sections

2

3.

5

1, 3.2, 3.

6

3

Topic

2

3.

5 Lecture

1 Lecture, Topic 3.1 Demonstration , Topic 3.2 Lecture,  Topic 3.

5

2 Demonstration, Topic

2

3.

6

3 Lecture,

Topic 2

Topic 3.

6

3 Demonstration

worksheet19

worksheet20

lec19

lec20-slides

 

WS20-solution

  

8

Mon

	Wed	Mar 05

Feb 28

Lecture

20: Confinement & Monitor Pattern. Critical sections
Global lock Module 2: Sections 5.1, 5.2, 5.6 Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5

21: Barrier Synchronization with Phasers	Module 1: Sections 3.4	Topic 3.4 Lecture, Topic 3.4 Demonstration	worksheet21	lec21-slides			WS21-solution
	Fri	Mar 07	Lecture 22:Stencil computation. Point-to-point Synchronization with Phasers	Module 1: Sections 4.2, 4.3	Topic 4.2 Lecture, Topic 4.2 Demonstration, Topic

5

4.

6

3 Lecture, Topic

5

4.

6

3 Demonstration

worksheet20

worksheet22

l ec20

lec22-slides

         

 

Wed

Mar 02

Lecture 21: N-Body problem, applications and implementations

  worksheet21lec21-slides    

 

Fri

Mar 04

Lecture 22: Fork/Join programming model. OS Threads. Scheduler Pattern

			WS22-solution
9	Mon	Mar 10	Lecture 23: Fuzzy Barriers with Phasers	Module 1: Section 4.1	Topic 4.1 Lecture, Topic 4.1 Demonstration	worksheet23	lec23-slides		Homework 3 (CP 1)	WS23-solution
	Wed	Mar 12	Lecture 24: Confinement & Monitor Pattern. Critical sections Global lock	Module 2: Sections

2

5.

7

1, 5.2

.8

Topic

2

5.

7

1 Lecture, Topic

2

5.

7

1 Demonstration, Topic 5.2

.8

Lecture, Topic 5.2

.8

Demonstration,

Topic 5.6 Lecture, Topic 5.6 Demonstration

worksheet24

lec24

worksheet22lec22

-slides

Homework 4

Homework 3

  

		WS24-solution
	Fri	Mar 14	Lecture 25:  Atomic variables, Synchronized statements

9

Mon

Mar 07

Lecture 23:  Locks, Atomic variables

Module 2: Sections 5.4, 7.

3

2

Topic

7

5.

3 Lecture worksheet23

4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture

worksheet25

lec25

lec23

-slides

 

WS25-solution

 

	Mon

 

Mar 17

No class: Spring Break

 

	Wed	Mar

09

19

Lecture 24: Parallel Spanning Tree, other graph algorithms

  worksheet24 lec24-slides 

 

  

 

Fri

Mar 11

No class: Spring Break
	Fri	Mar 21	No class: Spring Break
10	Mon	Mar 24	Lecture 26: Java Threads and Locks

 Lecture 25: Linearizability of Concurrent Objects

Module 2: Sections 7.

4

1, 7.3

Topic 7.1 Lecture, Topic 7.

4

3 Lecture

worksheet25

worksheet26

lec25

lec26-slides

 

 

  

		WS26-solution
	Wed	Mar 26	Lecture 27: Read-Write Locks,  Soundness and progress guarantees	Module 2: Section 7.3	Topic 7.3 Lecture, Topic 7.5 Lecture	worksheet27	lec27-slides		Homework 3 (CP 2)	WS27-solution
	Fri	Mar 28	Lecture 28: Dining Philosophers Problem		Topic 7.6 Lecture	worksheet28	lec28-slides			WS28-solution
11	Mon	Mar 31	Lecture 29:  Linearizability of Concurrent Objects	Module 2: Sections 7.4	Topic 7.4 Lecture	worksheet29	lec29-slides			WS29-solution
	Wed	Apr 02	Lecture 30:  Parallel Spanning Tree, other graph algorithms			worksheet30	lec30-slides			WS30-solution
	Fri	Apr 04	No class
12	Mon	Apr 07	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
	Wed	Apr 09	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	Homework 4	Homework 3 (All)	WS32-solution
	Fri	Apr 11	Lecture 33: Task Affinity and locality. Memory hierarchy			worksheet33	lec33-slides			WS33-solution
13	Mon	Apr 14	Lecture 34: Eureka-style Speculative Task Parallelism			worksheet34	lec34-slides			WS34-solution
	Wed	Apr 16	Lecture 35: Scan Pattern. Parallel Prefix Sum			worksheet35	lec35-slides		Homework 4 (CP 1)	WS35-solution
	Fri	Apr 18	Lecture 36: Scan Pattern. Parallel Prefix Sum cont.				lec36-slides
14	Mon	Apr 21	Lecture 37: Parallel Prefix Sum applications			worksheet37	lec37-slides			WS37-solution
	Wed	Apr 23	Lecture 38: Course Review (Lectures 19-34)				lec38-slides		Homework 4 (All)
	Fri	Apr 25	Lecture 39: Course Review (Lectures 19-34)				lec39-slides

 

Mon

Mar 14

No class: Spring Break

     

 

   WedMar 16No class: Spring Break    

 

   

 

Fri

Mar 18

No class: Spring Break

     

 

  

10

Mon

Mar 21

Lecture 26: Java Locks - Soundness and progress guarantees

Module 2: 7.5Topic 7.5 Lecture worksheet26lec26-slides     

 

Wed

Mar 23

Lecture 27: Dining Philosophers Problem

Module 2: 7.6Topic 7.4 Lecture Topic 7.6 Lecture worksheet27lec27-slides

 

   

 

Fri

Mar 25

Lecture 28: Read-Write Pattern. Read-Write Locks. Fairness & starvation

Module 2: 7.3, 7.5Topic 7.3 Lecture, Topic 7.5 Lecture, worksheet28lec28-slides

 

 

 

  

11

Mon

Mar 28

Lecture 29: Task Affinity and locality. Memory hierarchy

  worksheet29lec29-slides

 

 

  

 

Wed

Mar 30

Lecture 30: Reactor Pattern. Web servers

  worksheet30lec30-slides

 

   

 

Fri

Apr 01

Lecture 31: Scan Pattern. Parallel Prefix Sum, uses and algorithms

  worksheet31lec31-slidesHomework 5

Homework 4

  

12

Mon

Apr 04

Lecture 32: Data-Parallel Programming model. Loop-Level Parallelism, Loop ChunkingModule 1: Sections 3.1, 3.2, 3.3Topic 3.1 Lecture , Topic 3.1 Demonstration , Topic 3.2 Lecture,  Topic 3.2 Demonstration, Topic 3.3 Lecture,  Topic 3.3 Demonstrationworksheet32lec32-slides

 

 

  

 

Wed

Apr 06

Lecture 33: Barrier Synchronization with phasers

Module 1: Section 3.4

Topic 3.4 Lecture ,   Topic 3.4 Demonstration

worksheet33lec33-slides

 

   

 

Fri

Apr 08

Lecture 34:  Stencil computation. Point-to-point Synchronization with Phasers

Module 1: Section 4.2, 4.3Topic 4.2 Lecture ,   Topic 4.2 Demonstration, Topic 4.3 Lecture,  Topic 4.3 Demonstrationworksheet34lec34-slides 

 

  

13

Mon

Apr 11

Lecture 35: Message-Passing programming model with ActorsModule 2: 6.1, 6.2

Topic 6.1 Lecture ,   Topic 6.1 Demonstration ,   Topic 6.2 Lecture, Topic 6.2 Demonstration

worksheet35lec35-slides

 

 

   WedApr 13Lecture 36: Active Object Pattern. Combining Actors with task parallelism Module 2: 6.3, 6.4

Topic 6.3 Lecture ,   Topic 6.3 Demonstration ,   Topic 6.4 Lecture, Topic 6.4 Demonstration

worksheet36lec36-slides     FriApr 15Lecture 37: Eureka-style Speculative Task Parallelism  worksheet37lec37-slides    14MonApr 18Lecture 38: Overview of other models and frameworks   lec38-slides     WedApr 20Lecture 39: Course Review (Lectures 19-38)   lec39-slides     FriApr 22Lecture 40: Course Review (Lectures 19-38)   lec40-slides Homework 5  

Lab Schedule

Grading, Honor Code Policy, Processes and Procedures

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Labs must be submitted by the following Wednesday at 4:30pmFriday at 4pm.  Labs must be checked off by a TA.

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