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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• 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

 

 

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: 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-

slides 

slides

   

		WS9-solution
	Wed	Jan 31

 WedFeb 02

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:

Lightweight task parallelism

Accumulation and reduction. Finish

/async

accumulators

Module 1: Section

1

2.

1

3

Topic

1

2.

1

3 Lecture

,

Topic

1

2.

1

 

3 Demonstration

worksheet13

lec13-slides

   

	WS13-solution

Fri

Feb

11

09	No class: Spring Recess

 

        

6	Mon	Feb

14

12	Lecture 14:

Parallel Speedup, Critical Path, Amdah's Law

Data Races, Functional & Structural Determinism

Module 1:

Section 1

Sections 2.5, 2.6

Topic

1

2.5 Lecture ,  Topic

1

2.5 Demonstration

,  Topic 2.6 Lecture,  Topic 2.6 Demonstration

worksheet14

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-solution
	Fri	Feb

18

16	Lecture 16:

Accumulation and reduction. Finish accumulatorsModule 1: Section 2.3Topic 2.3 Lecture , Topic 2.3 Demonstration 

Recursive Task Parallelism

worksheet16

lec16-slides

Homework 3

Homework 2 

WS16-solution
7	Mon	Feb

21

19	Lecture 17: Midterm Review

   

lec17-slides

    

 

	Wed	Feb

23

21	Lecture 18:

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

Midterm Review

lec18-slides

   lec18-slides     

	Fri	Feb

25 

23	Lecture 19:

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

Fork/Join programming model. OS Threads. Scheduler Pattern

Topic 2.

5

7 Lecture, Topic 2.

5

7 Demonstration, Topic 2.

6

8 Lecture, Topic 2.

6  

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

l ec20

lec20-slides

        

		WS20-solution
	Wed	Feb 28

 

Wed

Mar 02

Lecture 21:

N-Body problem, applications and implementations

Barrier Synchronization with Phasers

Module 1: Sections 3.4

Topic 3.4 Lecture, Topic 3.4 Demonstration

worksheet21

lec21-slides

WS21-solution

  worksheet21lec21-slides     

	Fri	Mar

04

01	Lecture 22:

Fork/Join programming model. OS Threads. Scheduler Pattern

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

Module 2: Sections 2.7, 2.8Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration,   

worksheet22

lec22-slides

Homework 4

Homework 3

 

WS22-solution
9	Mon	Mar

07

04	Lecture 23:

 Locks, Atomic variables

Fuzzy Barriers with Phasers

Module

2

1:

7

Section 4.

3

1	Topic 4.1 Lecture, Topic 4.1 Demonstration

Topic 7.3 Lecture

 

worksheet23

lec23-slides

 

 

  

	Homework 3 (CP 1)	WS23-solution

Wed

Mar

09

06	Lecture 24:

Parallel Spanning Tree, other graph algorithms

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 08	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 11	No class: Spring Break

  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

     

 

  

	Wed	Mar

16

13	No class: Spring Break

 

 

Fri

Mar 18

	Fri

   

 

   

Mar 15

No class: Spring Break

     

 

  

10	Mon	Mar

21

18	Lecture 26: Java Threads and Locks

- Soundness and progress guarantees

Module 2: Sections 7.

5

1, 7.3

Topic 7.

5  

1 Lecture, Topic 7.3 Lecture

worksheet26

lec26-slides

    

WS26-solution
	Wed	Mar

23

20	Lecture 27:

Dining Philosophers Problem

Read-Write Locks,  Soundness and progress guarantees

Module 2: Section 7.

6

3

Topic 7.

4

3 Lecture, Topic 7.

6

5 Lecture

worksheet27

lec27-slides

 

   

 

	Homework 3 (CP 2)	WS27-solution
	Fri	Mar

25

22	Lecture 28:

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

Dining Philosophers Problem		Topic 7.6 Lecture	worksheet28	lec28-slides			WS28-solution
11	Mon	Mar 25	Lecture 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

 

  

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 

Mar 27	Lecture 30:  Parallel Spanning Tree, other graph algorithms			worksheet30	lec30-slides			WS30-solution
	Fri	Mar 29	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 01	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
	Wed	Apr 03	Lecture 33: Task Affinity and locality. Memory hierarchy			worksheet33	lec33-slides			WS33-solution
	Fri	Apr 05	Lecture 34: Eureka-style Speculative Task Parallelism			worksheet34	lec34-slides			WS34-solution
13	Mon	Apr 08	No class: Solar Eclipse
	Wed	Apr 10	Lecture 35: Scan Pattern. Parallel Prefix Sum			worksheet35	lec35-slides		Homework 4 (CP 1)	WS35-solution
	Fri	Apr 12	Lecture 36: Parallel Prefix Sum applications			worksheet36	lec36-slides			WS36-solution
14	Mon	Apr 15	Lecture 37: Overview of other models and frameworks

   lec38-slides    

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-

38

34)

   lec40

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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