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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• 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

lec5-slides

Homework 1

 3

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.

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

	Wed	Feb 07

Feb 09

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

       6

Mon

Feb 14

Lecture 14: Parallel Speedup, Critical Path, Amdah's Law

Feb 12

Lecture 14: 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

lec14-slides

    

		WS14-solution
	Wed	Feb 14

 

Wed

Feb 16

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 Demonstrationworksheet16 lec16-slidesHomework 3Homework 2  

Recursive Task Parallelism			worksheet16	lec16-slides	Homework 3		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

Mar 02  worksheet21

Feb 28

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

   

 

Fri

	Fri	Mar 01

Mar 04

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

	Fri	Mar 08

Mar 11

Lecture 25:

Linearizability of Concurrent Objects

Atomic variables, Synchronized statements

Module 2: Sections 5.4, 7.

4

2

Topic

7

5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture

worksheet25

lec25-slides

 

WS25-solution

 

	Mon

 

Mar 11

No class: Spring Break

 Mon

	Wed	Mar

14

13	No class: Spring Break

     

 

  

	Fri	Mar 15

 WedMar 16

No class: Spring Break

 

10

 

Mon

  

 

   

 

Fri

Mar 18

No class: Spring Break

     

 

  

10

Mon

Mar 21

Lecture 26

Mar 18	Lecture 26: Parallel Spanning Tree, other graph algorithms			worksheet26	lec26-slides			WS26-solution
	Wed	Mar 20	Lecture 27: Java Threads and Locks	Module 2: Sections 7.1, 7.3	Topic 7.1 Lecture, Topic 7.3 Lecture	worksheet27	lec27-slides		Homework 3 (CP 2)	WS27-solution
	Fri	Mar 22	Lecture 28: Java Locks - Soundness and progress guarantees	Module 2: Section 7.5	Topic 7.5 Lecture

worksheet26

worksheet28

lec26

lec28-slides

 

WS28-solution

   

11	Mon

 

Wed

Mar

23

25

Lecture

27

29:

Dining

Dining Philosophers Problem

Module 2: Section 7.6

Topic 7.4 Lecture

Topic 7.6 Lecture

worksheet27

worksheet29

lec27

lec29-slides

 

   

 

Fri

Mar 25

Lecture 28

		WS29-solution
	Wed	Mar 27	Lecture 30: Read-Write

Pattern. Read-Write Locks. Fairness & starvation

Locks, Linearizability of Concurrent Objects

Module 2: Sections 7.3, 7.

5

4	Topic 7.3 Lecture, Topic 7.

5

4 Lecture

, worksheet28

worksheet30

lec28

lec30-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 

		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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