COMP 322: Fundamentals of Parallel Programming (Spring

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2025)

Course Syllabus

Course Syllabus

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

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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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  

 

 

slides

WS1-solution

  

	Wed	Jan

12

15	Lecture 2:  Functional Programming

GList.java 

worksheet2

lec02-slides

 

 

WS2-solution

  

	Fri	Jan

14

17	Lecture 3: Higher order functions

 

worksheet3

worksheet3 

lec3-

slides   

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

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:

Async, Finish

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

  

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	Feb

09

12	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	Feb

14

17	Lecture 14:

Accumulation and reduction. Finish accumulators

Data Races, Functional & Structural Determinism

Module 1:

Section

Sections 2.5, 2.

3

6	Topic 2.5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.

3

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

WS15

-solution

  

	Fri	Feb

18

21	Lecture 16:

Data Races, Functional & Structural DeterminismModule 1: Sections 2.5, 2.6Topic 2.5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.6 Lecture,  Topic 2.6 Demonstration

Recursive Task Parallelism

worksheet16

lec16-slides

Homework 3

Homework 27

WS16-solution

 

7	Mon	Feb

21

24	Lecture 17: Midterm Review

   

lec17-slides

     

	Wed	Feb

23  worksheet18

26	Lecture 18:

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

Midterm Review

lec18-slides

  WS18-solution 

 

	Fri	Feb

25 

28	Lecture 19:  Fork/Join programming model

. OS Threads. Scheduler Pattern

Topic 2.

 Module 1: Sections 2.7, 2.8Topic 2.

7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration

, 

worksheet19

lec19-slides

    

		WS19-solution
8	Mon

Feb 28

Mar 03

Lecture 20:

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

Data-Parallel Programming model. Loop-Level Parallelism, Loop Chunking

Module 1: Sections 3.1, 3.2, 3.3

Topic 3.1 Lecture, Topic

5

3.1 Demonstration , Topic

5

3.2 Lecture,

Topic 5

Topic 3.2 Demonstration, Topic

5

3.

6

3 Lecture,

Topic 5

Topic 3.

6

3 Demonstration

worksheet20

lec20-slides

        

 

		WS20-solution
	Wed	Mar

02

05	Lecture 21:

  Atomic variables, Synchronized statements

Barrier Synchronization with Phasers

Module

2

1: Sections

5

3.4	Topic 3.4 Lecture,

7.2Topic 5.4 Lecture, Topic 5

Topic 3.4 Demonstration

, Topic 7.2 Lecture 

worksheet21

lec21-slides

    

WS21-solution
	Fri	Mar

04

07	Lecture 22:

Parallel Spanning Tree, other graph algorithms   worksheet22lec22-slidesHomework 4

Homework 3

  

9

Mon

Mar 07

Lecture 23: Java Threads and Locks

Module 2: Sections 7.1, 7

Stencil computation. Point-to-point Synchronization with Phasers

Module 1: Sections 4.2, 4.3

Topic

7

4.

1 Lecture

2 Lecture, Topic 4.2 Demonstration, Topic

7

4.3 Lecture

, Topic 4.3 Demonstration

worksheet22

lec22

worksheet23 lec23

-slides

 

WS22-solution

 

9

  

Mon

Mar 10

 

Wed

Mar 09

Lecture

24: N-Body problem, applications and implementations 

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 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			WS24-solution
	Fri	Mar 14	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	lec25-slides			WS25-solution
	Mon	Mar 17

  worksheet24 lec24-slides 

 

  

 

Fri

Mar 11

 Lecture 25: Linearizability of Concurrent ObjectsModule 2: 7.4Topic 7.4 Lectureworksheet25lec25-slides 

 

   

Mon

Mar 14

No class: Spring Break

     

 

   WedMar 16

No class: Spring Break

 

	Wed

  

 

   

Mar 19

No class: Spring Break

 

	Fri	Mar

18

21	No class: Spring Break

 

10

 Java Locks -

Mon

   

 

  

10

Mon

Mar 21

Lecture 26:

Mar 24	Lecture 26: Java Threads and Locks	Module 2: Sections 7.1, 7.3	Topic 7.1 Lecture, Topic 7.3 Lecture	worksheet26	lec26-slides			WS26-solution
	Wed	Mar 26	Lecture 27: Read-Write Locks,

Soundness and progress guarantees

Module 2: Section 7.

5

3	Topic 7.3 Lecture, Topic 7.5 Lecture

worksheet26

worksheet27

lec26

lec27-slides

    

 

Wed

Mar 23

	Homework 3 (CP 2)	WS27-solution
	Fri	Mar 28	Lecture 28

Lecture 27

: Dining Philosophers Problem

Module 2: 7.6

Topic 7.

4 Lecture Topic 7.

6 Lecture

worksheet27

worksheet28

lec27

lec28-slides

 

WS28-solution

 

11

  

 

Fri

Mon

Mar 31

Mar 25

Lecture

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

29:  Linearizability of Concurrent Objects

Module 2: Sections 7.

3, 7.5

4

Topic 7.

3 Lecture, Topic 7.5 Lecture,

4 Lecture

worksheet29

lec29

worksheet28lec28

-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

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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