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

 

 

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

    Jan 31

		WS8-solution
4	Mon

 

Jan 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	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

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

    

 

	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  worksheet21

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	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 7

Topic 4.

3 Lecture

1 Lecture, Topic 4.1 Demonstration

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

  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 13	No class: Spring Break
	Fri	Mar 15

 WedMar 16

No class: Spring Break

 

10

   

 

   

 

Fri

Mar 18

No class: Spring Break

     

 

  

10

Mon

Mar 21

Mon

Mar 18

Lecture 26: Java Threads and Locks

- Soundness and progress guarantees

Module 2: Sections 7.

5

1, 7.3

Topic 7.

5 Lecture

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 Module 2: 7.3, 7.5

Dining Philosophers Problem

Topic 7.

3 Lecture, Topic 7.5 Lecture,  

6 Lecture

worksheet28

lec28-slides

 

 

 

 

WS28-solution
11	Mon	Mar

28

25	Lecture 29:

Task Affinity and locality. Memory hierarchy

Linearizability of Concurrent Objects

Module 2: Sections 7.4

Topic 7.4 Lecture

   

worksheet29

lec29-slides

 

 

  

WS29-solution
	Wed	Mar

30

27	Lecture 30:

Reactor Pattern. Web servers   

Parallel Spanning Tree, other graph algorithms

worksheet30

lec30-slides

 

   

WS30-solution
	Fri

Apr 01

Mar 29

Lecture 31:

 Scan Pattern. Parallel Prefix Sum, uses and algorithms

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

Homework 5

Homework 4

  

		WS31-solution
12	Mon	Apr

04

01	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

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

06

03	Lecture 33:

Barrier Synchronization with phasersModule 1: Section 3.4

Topic 3.4 Lecture ,   Topic 3.4 Demonstration

Task Affinity and locality. Memory hierarchy

worksheet33

lec33-slides

 

   

 

		WS33-solution
	Fri	Apr

08

05	Lecture 34:

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

Eureka-style Speculative Task Parallelism

worksheet34

lec34-slides

 

WS34-solution

 

13

 

Mon

 

Apr 08	No class: Solar Eclipse
	Wed	Apr 10

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

 

 

  

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

 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    

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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