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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• 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 

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 2

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 2.7

 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

5.4, 7.2

3.4

Topic

5

3.4 Lecture, Topic

5worksheet21

3.4 Demonstration

, Topic 7.2 Lecture

worksheet21

lec21-slides

  

WS21-solution

  

	Fri	Mar

04

07	Lecture 22:

Parallel Spanning Tree, other graph algorithms 

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

worksheet22

lec22-slides

WS22-solution

  worksheet22lec22-slidesHomework 4

Homework 3

WS22-solution 

9	Mon	Mar

07

10	Lecture 23:

Java Threads and Locks

Fuzzy Barriers with Phasers

Module

2

1:

Sections 7

Section 4.1

, 7.3

Topic 4

Topic 7

.1 Lecture, Topic

7

4.

3 Lecture  

1 Demonstration

worksheet23

lec23-slides

 

Homework 3 (CP 1)

WS23-solution

  

	Wed	Mar

09

12	Lecture 24:

Java Locks - Soundness and progress guarantees  

Confinement & Monitor Pattern. Critical sections Global lock

Module 2:

7

Sections 5.1, 5.2

Topic

7

5.1 Lecture, Topic 5

Lecture worksheet24 lec24-slides 

.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

11

14	Lecture 25:

Dining Philosophers Problem  

Atomic variables, Synchronized statements

Module 2: Sections 5.4, 7.

6Topic 7.6 Lecture

2

Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture

worksheet25

lec25-slides

 

 

WS25-solution

 

	Mon	Mar 17

 

Mon

Mar 14

No class: Spring Break

     

 

  

	Wed	Mar

16

19	No class: Spring Break

   

 

 

 

   

Fri

Mar

18

21	No class: Spring Break

     

 

  

10	Mon	Mar

21

24	Lecture 26:

N-Body problem, applications and implementations 

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

23

26	Lecture 27: Read-Write Locks,

Linearizability of Concurrent Objects

Soundness and progress guarantees

Module 2: Section 7.3

, 7.4

Topic 7.3 Lecture, Topic 7.

4  

5 Lecture

worksheet27

lec27-slides

 

Homework 3 (CP 2)

WS27-solution

  

	Fri	Mar

25

28	Lecture 28:

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

Dining Philosophers Problem

Topic 7.6 Lecture

worksheet28

lec28-slides

 

 

 

WS28-solution

 

11	Mon	Mar

28

31	Lecture 29:

Active Object Pattern. Combining Actors with task parallelism 

Linearizability of Concurrent Objects

Module 2:

6.3, 6

Sections 7.4

Topic

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

7.4 Lecture

worksheet29

lec29-slides

 

 

 

WS29-solution

 

Wed

Mar 30

Apr 02

Lecture 30:

Task Affinity and locality. Memory hierarchy

Parallel Spanning Tree, other graph algorithms			worksheet30	lec30-slides			WS30-solution
	Fri

  worksheet30lec30-slides

 

 WS30-solution 

 

Fri

Apr 01

Lecture 31: Data-Parallel Programming model. Loop-Level Parallelism, Loop Chunking

Module 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 Demonstrationworksheet31lec31-slidesHomework 5

Homework 4

WS31-solution 

12

Mon

Apr 04

Lecture

32: Barrier Synchronization with phasersModule 1: Section 3.4Topic 3.4 Lecture ,   Topic 3.4 Demonstrationworksheet32lec32-slides

 

 

  

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 07	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
	Wed	Apr 09	Lecture 33: Task Affinity and locality. Memory hierarchy			worksheet33	lec33-slides	Homework 4	Homework 3 (All)	WS33-solution
	Fri	Apr 11	Lecture 34: Eureka-style Speculative Task Parallelism			worksheet34	lec34-slides			WS34-solution
13	Mon	Apr 14	No class: Solar Eclipse
	Wed	Apr 16	Lecture 35: Scan Pattern. Parallel Prefix Sum			worksheet35	lec35-slides		Homework 4 (CP 1)	WS35-solution
	Fri	Apr 18	Lecture 36: Parallel Prefix Sum applications			worksheet36	lec36-slides			WS36-solution
14	Mon	Apr 21	Lecture 37: Overview of other models and frameworks				lec37-slides
	Wed	Apr 23	Lecture 38

 

Wed

Apr 06

Lecture 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

worksheet33lec33-slides

 

   

 

Fri

Apr 08

Lecture 34: Scan Pattern. Parallel Prefix Sum

  worksheet34lec34-slides 

 

  

13

Mon

Apr 11

Lecture 35: Parallel Prefix Sum applications 

 

worksheet35lec35-slides

 

 

   WedApr 13Lecture 36: TBD 

 

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-

38lec39

34)

   

lec38-slides

    

Homework 4 (All)
	Fri	Apr

22

25

Lecture

40

39: Course Review (Lectures 19-

38 

34)

   lec40-slides Homework 5 

lec39-slides

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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