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 (Concurrency)

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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

 

 

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

  WS3

worksheet3

lec3-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

 

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

    

		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

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

	Wed	Feb 21

Feb 23

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 Determinism

-Parallel Programming model. Loop-Level Parallelism, Loop Chunking

Module 1: Sections

2

3.

5

1, 3.2, 3.

6

3

Topic

2

3.

5 Lecture

1 Lecture, Topic 3.1 Demonstration , Topic 3.2 Lecture,  Topic 3.

5

2 Demonstration, Topic

2

3.

6

3 Lecture,

Topic 2

Topic 3.

6  

3 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 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstrationworksheet20

Barrier Synchronization with Phasers

Module 1: Sections 3.4

Topic 3.4 Lecture, Topic 3.4 Demonstration

worksheet20

lec20

l ec20

-slides

 

WS20-solution

 

	Wed

  

Feb 28

Lecture 21: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

 

Wed

Mar 02

Lecture 21: N-Body problem, applications and implementations

  

worksheet21

lec21-slides

    

 

		WS21-solution
	Fri	Mar 01	Lecture 22: Fuzzy Barriers with Phasers	Module 1: Section 4.1	Topic 4.1 Lecture, Topic 4.1 Demonstration	worksheet22	lec22-slides			WS22-solution
9	Mon

Fri

Mar 04

Lecture

22

23:  Fork/Join programming model. OS Threads. Scheduler Pattern

Module 2: Sections 2.7, 2.8

Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration

,  worksheet22

worksheet23

lec22

lec23-slides

Homework 4

Homework 3

  

(CP 1)	WS23-solution
	Wed	Mar 06	Lecture 24: Confinement & Monitor Pattern. Critical sections Global lock

9

Mon

Mar 07

Lecture 23:  Locks, Atomic variables

Module 2:

7.3

Sections 5.1, 5.2

Topic

7

5.

3 Lecture worksheet23 lec23-slides  

 

  

 

Wed

Mar 09

Lecture 24: Parallel Spanning Tree, other graph algorithms

  

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

  Lecture 25: Linearizability of Concurrent Objects

Mar 08

 

 

Fri

Mar 11

Lecture 25:  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

 

 

 

  

		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				lec37-slides
	Wed	Apr 17	Lecture 38: Course Review (Lectures 19-34)				lec38-slides		Homework 4 (All)
	Fri	Apr 19	Lecture 39: Course Review (Lectures 19-34)				lec39-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: Overview of other models and frameworks   lec38-slides     WedApr 20Lecture 39: Course Review (Lectures 19-38)   lec39-slides     FriApr 22Lecture 40: Course Review (Lectures 19-38)   lec40-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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