COMP 322: Fundamentals of Parallel Programming (Spring

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2024)

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  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

2024)	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

08	Lecture 1: Introduction

  

worksheet1

lec1-

slides  

 

 

slides

WS1-solution

 

 

	Wed	Jan

12

10	Lecture 2:  Functional Programming

GList.java 

worksheet2

lec02-slides

 

 

Fri

WS2-solution

  

Fri

Jan

14

12	Lecture 3: Higher order functions

 

worksheet3

worksheet3 

lec3-

slides   

slides

WS3-solution

 

2	Mon	Jan

17

15	No class: MLK

        

 

	Wed	Jan

19

17	Lecture 4: Lazy Computation

LazyList.java

Lazy.java

 

worksheet4

lec4-slides

  

 

WS4-solution

 

Fri

Jan

21

19	Lecture 5: Java Streams

 

worksheet5

 worksheet5

lec5-slides

Homework 1

 

WS5-solution

 

3	Mon	Jan

24

22

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

24

Lecture 7: Futures

Module 1: Section 2.1

Topic 2.1 Lecture , Topic 2.1 Demonstration

worksheet7

lec7-slides

 

 

WS7-solution

  

	Fri	Jan

28

26	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

29	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  

slides

WS9-solution

  

	Wed

Feb 02

Jan 31

Lecture 10: Event-based programming model

 

   

worksheet10

lec10-slides

 

Homework 1

WS10-solution

  

	Fri	Feb

04

02	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

05	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

07	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

09	No class: Spring Recess

         

6	Mon	Feb

14

12	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

14	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

16	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

19	Lecture 17: Midterm Review

   

lec17-slides

     

	Wed	Feb

23  worksheet18

21	Lecture 18:

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

Midterm Review

lec18-slides

  WS18-solution 

 

	Fri	Feb

25 

23	Lecture 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

lec19-slides

  

WS19-solution

 

8	Mon	Feb

28

26	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

Feb 28

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

5

3.4 Demonstration

, Topic 7.2 Lecture

worksheet21

lec21-slides

  

WS21-solution

  

	Fri	Mar

04

01	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

Homework 4

Homework 3

WS22-solution

 

9	Mon	Mar

07

04	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

06	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 Lecture

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

11

08	Lecture 25:

Dining Philosophers Problem  

Atomic variables, Synchronized statements

Module 2: Sections 5.4, 7.

6

2

Topic

7

5.

6 Lectureworksheet25lec25-slides 

4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture

worksheet25

lec25-slides

 

WS25-solution

  

	Mon	Mar

14

11	No class: Spring Break

     

 

  

Wed

Mar

16

13	No class: Spring Break

  

 

  

 

   

Fri

Mar

18

15	No class: Spring Break

     

 

  

10	Mon	Mar

21

18	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

20	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

22	Lecture 28:

Message-Passing programming model with Actors

Dining Philosophers Problem

Topic 7.6 Lecture

worksheet28

lec28-slides

Module 2: 6.1, 6.2Topic 6.1 Lecture, Topic 6.1 Demonstration,   Topic 6.2 Lecture, Topic 6.2 Demonstration worksheet28lec28-slides

 

 

 

WS28-solution

 

11	Mon	Mar

28

25	Lecture 29:

Active Object Pattern. Combining Actors with task parallelism 

Linearizability of Concurrent Objects

Module 2:

6.3, 6

Sections 7.4

Topic

6

7.

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

4 Lecture

worksheet29

worksheet29

lec29-slides

 

 

WS29-solution

  

	Wed	Mar

30

27	Lecture 30:

Task Affinity and locality. Memory hierarchy  

Parallel Spanning Tree, other graph algorithms

worksheet30

lec30-slides

  

WS30-solution

  

	Fri

Apr 01

Mar 29

Lecture 31:

Data

Message-

Parallel Programming model. Loop-Level Parallelism, Loop ChunkingModule 1: Sections 3

Passing programming model with Actors

Module 2: Sections 6.1,

3

6.2

, 3.3

Topic

3

6.1 Lecture, Topic

3

6.1 Demonstration,   Topic

3

6.2 Lecture,

 Topic 3

Topic 6.2 Demonstration

, Topic 3.3 Lecture,  Topic 3.3 Demonstration

worksheet31

lec31-slides

Homework 5

Homework 4

WS31-solution

 

12	Mon	Apr

04

01	Lecture 32:

Barrier Synchronization with Phasers

Active Object Pattern. Combining Actors with task parallelism

Module

1

2:

Section

Sections 6.3, 6.4

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

 Topic 3

Topic 6.4 Demonstration

worksheet32

lec32-slides

 

Homework 4

Homework 3 (All)

 

WS32-solution

  

	Wed	Apr

06

03	Lecture 33:

  Stencil computation. Point-to-point Synchronization with PhasersModule 1: Section 4.2, 4.3

Topic 4.2 Lecture, Topic 4.2 Demonstration, Topic 4.3 Lecture,  Topic 4.3 Demonstration

worksheet33lec33-slides

 

 WS33-solution 

Task Affinity and locality. Memory hierarchy			worksheet33	lec33-slides			WS33-solution
	Fri	Apr 05	Lecture 34

 

Fri

Apr 08

Lecture 34: Fuzzy Barriers with Phasers

Module 1: Section 4.1Topic 4.1 Lecture, Topic 4.1 Demonstrationworksheet34lec34-slides 

 

WS34-solution 

13

Mon

Apr 11

Lecture 35

: Eureka-style Speculative Task Parallelism

 lec35

worksheet34

worksheet35

lec34-slides

 

WS34-solution

 

13

WS35-solution 

Mon

Apr 08

No class: Solar Eclipse

 

	Wed	Apr

13

10

Lecture

36

35: Scan Pattern. Parallel Prefix Sum

 

 

worksheet36

worksheet35

lec35

lec36

-slides

  WS36-solution 

Homework 4 (CP 1)

WS35-solution

 

	Fri	Apr

15

12

Lecture

37

36: Parallel Prefix Sum

applications 

applications

 lec37

worksheet36

worksheet37 

lec36-slides

   

WS36-solution
14	Mon	Apr

18

15

Lecture

38lec38

37: Overview of other models and frameworks

   

lec37-slides

     

	Wed	Apr

20

17

Lecture

39

38: Course Review (Lectures 19-

38lec39

34)

   

lec38-slides

    

Homework 4 (All)
	Fri	Apr

22

19

Lecture

40

39: Course Review (Lectures 19-

38lec40

34)

   

lec39-slides

 Homework 5  

Lab Schedule

Grading, Honor Code Policy, Processes and Procedures

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Labs must be submitted by the following Wednesday Monday at 4:30pm3pm.  Labs must be checked off by a TA.

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