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COMP 322: Fundamentals of Parallel Programming (Spring

...

2023)

...


Instructor:

Mackale Joyner, DH 2063

Head
TAs:
 Admin Assistant:Annepha Hurlock, annepha@rice.edu, DH 3122, 713-348-5186Undergraduate TAs:
Mohamed Abead, Chase Hartsell, Taha Hasan, Harrison Huang, Jerry Jiang, Jasmine Lee, Michelle Lee, Hung Nguyen, Quang Nguyen, Ryan Ramos, Oscar Reynozo, Delaney Schultz, Tina Wen, Raiyan Zannat, Kailin Zhang

Piazza site:

https://piazza.com/rice/

spring2021

spring2023/comp322 (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Fully Online

Herzstein Amphitheater

Lecture times:

MWF 1:

30pm

00pm -

2

1:

25pm

50pm

Lab locations:

Fully Online

Mon (Herzstein Amp), Tue (Keck 100)

Lab times:

Tu 1

Mon  3:

30pm

00pm -

2

3:

25pm (TV, MS, TG)Th 4:50pm - 5:45pm (XW, RW, TR

50pm (Raiyan, Oscar, Mohamed, Ryan, Michelle, Taha, Jasmine)

Tue 4:00pm - 4:50pm (Tina, Delaney, Chase, Hung, Jerry, Kailin)

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.

...

The desired learning outcomes fall into three major areas (course modules):

1) Parallelism: functional programming, Java streams, creation and coordination of parallelism (async, finish), abstract performance metrics (work, critical paths), Amdahl's Law, weak vs. strong scaling, data races and determinism, data race avoidance (immutability, futures, accumulators, dataflow), deadlock avoidance, abstract vs. real performance (granularity, scalability), collective & point-to-point synchronization (phasers, barriers), parallel algorithms, systolic algorithms.

...

3) Locality & Distribution: memory hierarchies, locality, cache affinity, data movement, message-passing (MPI), communication overheads (bandwidth, latency), MapReduce, accelerators, GPGPUs, CUDA, OpenCL.

To achieve these learning outcomes, each class period will include time for both instructor lectures and in-class exercises based on assigned reading and videos.  The lab exercises will be used to help students gain hands-on programming experience with the concepts introduced in the lectures.

To ensure that students gain a strong knowledge of parallel programming foundations, the classes and homeworks homework will place equal emphasis on both theory and practice. The programming component of the course will mostly use the  Habanero-Java Library (HJ-lib)  pedagogic extension to the Java language developed in the  Habanero Extreme Scale Software Research project  at Rice University.  The course will also introduce you to real-world parallel programming models including Java Concurrency, MapReduce, MPI, OpenCL and CUDA. . An important goal is that, at the end of COMP 322, you should feel comfortable programming in any parallel language for which you are familiar with the underlying sequential language (Java or C). Any parallel programming primitives that you encounter in the future should be easily recognizable based on the fundamentals studied in COMP 322.

...

  • Module 1 handout (Parallelism)
  • Module 2 handout (Concurrency)There is no lecture handout for Module 3 (Distribution and Locality).  The instructors will refer you to optional resources to supplement the lecture slides and videos.

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:

Lecture Schedule

 

Finally, here are some additional resources that may be helpful for you:

Lecture Schedule

 



Week

Day

Date (2023

Week

Day

Date (2021 

)

Lecture

Assigned Reading

Assigned Videos (see Canvas site for video links)

In-class Worksheets

Slides

Work Assigned

Work Due

 
Worksheet Solutions

1

Mon

Jan

25Topic 1.1 Lecture, Topic 1.1 Demonstration

09

Lecture 1:

Task Creation and Termination (Async, Finish)Module 1: Section 1.1

Introduction



worksheet1lec1-slides

 

 

  
  



WS1-solution
 


Wed

Jan

27

11

Lecture 2: 

Computation Graphs, Ideal ParallelismModule 1: Sections 1.2, 1.3Topic 1.2 Lecture, Topic 1.2 Demonstration, Topic 1.3 Lecture, Topic 1.3 Demonstration

Functional Programming



worksheet2
lec2
lec02-slides

Homework 1

 

  



WS2-solution

FriJan 13Lecture 3: Higher order functions

worksheet3 
 FriJan 29Lecture 3: Abstract Performance Metrics, Multiprocessor SchedulingModule 1: Section 1.4Topic 1.4 Lecture, Topic 1.4 Demonstrationworksheet3
lec3-slides
 
 
 
 



WS3-solution

2

Mon

Jan 16

No class: MLK










Wed

Jan 18

Feb 01

Lecture 4:
Parallel Speedup and Amdahl's LawModule 1: Section 1.5Topic 1.5 Lecture, Topic 1.5 Demonstration
Lazy Computation



worksheet4lec4-slides
Quiz for Unit 1   


WS4-solution


Fri

Jan 20

Lecture 5: Java Streams



worksheet5lec5-slidesHomework 1
WS5-solution
3MonJan 23

Lecture 6: Map Reduce with Java Streams

 

Wed

Feb 03

Lecture 5: Future Tasks, Functional Parallelism ("Back to the Future")

Module 1: Section 2.
1
4Topic 2.
1
4 Lecture, Topic 2.
1
4 Demonstration  
worksheet5
worksheet6
lec5
lec6-slides
 



WS6-solution
   


Wed

Jan 25

Lecture 7: Futures

 

Fri

Feb 05

Lecture 6:   Finish Accumulators

Module 1: Section 2.
3
1Topic 2.
3
1 Lecture , Topic 2.
3
1 Demonstration
worksheet6
worksheet7
lec6
lec7-slides
 Quiz for Unit 1  



WS7-solution


Fri

Jan 27

Lecture 8:  Async, Finish, Computation Graphs

3MonFeb 08Lecture 7: Map Reduce

Module 1:
Section 2.4
Sections 1.1, 1.2Topic
2
1.
4
1 Lecture, Topic
2
1.
4 Demonstration  
1 Demonstration, Topic 1.2 Lecture, Topic 1.2 Demonstrationworksheet8lec8
worksheet7lec7
-slides
 


WS8-solution
 

4

 
Mon

 Lecture 8: Data Races, Functional & Structural Determinism


Jan 30 

Wed

Feb 10

Lecture 9: Ideal Parallelism, Data-Driven Tasks 

Module 1: Section

2

1.

5

3,

2

4.

6

5


Topic

2

1.

5

3 Lecture, Topic

2

1.

5

3 Demonstration, Topic

2

4.

6

5 Lecture, Topic

2

4.

6 Demonstration   

5 Demonstration

worksheet9

lec9-slides 

WS9-solution

WedFeb 01Lecture 10: Event-based programming model




worksheet10lec10-slides
Homework 1WS10-solution
worksheet8lec8-slides

Homework 2

Homework 1   


FriFeb
12
03Lecture
9: Java’s Fork/Join Library
11: GUI programming, Scheduling/executing computation graphs

Module 1:
Sections 2.7, 2.8
Section 1.4Topic
2
1.
7
4 Lecture , Topic
2
1.
8 Lecture
4 Demonstration
worksheet9
worksheet11
lec9
lec11-slides
Quiz for Unit
Homework 2
   

WS11-solution
5
4

Mon

Feb

15

06

Lecture
10: Loop-Level Parallelism, Parallel Matrix Multiplication
12: Abstract performance metrics, Parallel Speedup, Amdahl's Law Module 1:
Sections 3.
Section 1
, 3
.
2
5Topic
3
1.
1
5 Lecture , Topic
3.1 Demonstration ,  Topic 3.2 Lecture,  Topic 3.2 Demonstration
1.5 Demonstrationworksheet12lec12-slides

WS12-solution


Wed

Feb 08

Lecture 13: Accumulation and reduction. Finish accumulators

Module 1: Section 2.3

Topic 2.3 Lecture   Topic 2.3 Demonstration

worksheet13lec13
worksheet10lec10
-slides 
 

WS13-solution
 


Fri

  WedFeb 17Spring "Sprinkle" Day (no class)        

 

Fri

Feb 19

Feb 10

No class: Spring Recess










6

Mon

Feb 13

Lecture 14: Recursive Task Parallelism  



worksheet14lec14-slides

WS14-solution


Wed

Feb 15

Lecture 15: Data Races, Functional & Structural Determinism

Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization

Module 1: Sections
3
2.
3
5,
3
2.
4
6Topic
3
2.
3
5 Lecture ,  Topic
3
2.
3
5 Demonstration,  Topic
3
2.
4
6 Lecture
 
,  Topic
3
2.
4
6 Demonstration
worksheet11
worksheet15
lec11Quiz for Unit
lec15-slides
 



Homework 2
  
WS15-solution

Fri

5

Mon
Feb
22
17

Lecture

12:  Parallelism in Java Streams, Parallel Prefix Sums Module 1: Section 3.7Topic Topic 3.7 Java Streams, Topic 3.7 Java Streams Demonstrationworksheet12lec12-slides     

Wed

Feb 24

Lecture 13: Iterative Averaging Revisited, SPMD pattern

Module 1: Sections 3.5, 3.6Topic 3.5 Lecture , Topic 3.5 Demonstration , Topic 3.6 Lecture,   Topic 3.6 Demonstrationworksheet13lec13-slides

Homework 3 (includes one intermediate checkpoint)

Quiz for Unit 3

Homework 2  

 

Fri

Feb 26

Lecture 14: Data-Driven Tasks 

Module 1: Sections 4.5Topic 4.5 Lecture   Topic 4.5 Demonstrationworksheet14 lec14-slides    6MonMar 01Spring "Sprinkle" Day (no class)        

 

Wed

Mar 03

Lecture 15:  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 Demonstrationworksheet15lec15-slides    

 

Fri

Mar 05

Lecture 16: Pipeline Parallelism, Signal Statement, Fuzzy Barriers

Module 1: Sections 4.4, 4.1Topic 4.4 Lecture ,   Topic 4.4 Demonstration, Topic 4.1 Lecture,  Topic 4.1 Demonstrationworksheet16lec16-slidesQuiz for Unit 4Quiz for Unit 3  

7

Mon

Mar 08

Lecture 17: Midterm Review

   lec17-slides    

 

Wed

Mar 10

Lecture 18: Abstract vs. Real Performance

  worksheet18 lec18-slides     

 

Fri

Mar 12

Lecture 19: Critical Sections, Isolated construct (start of Module 2)

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 Demonstrationworksheet19lec19-slides    

8

Mon

Mar 15

Lecture 20: Parallel Spanning Tree algorithm, Atomic variables

Module 2: Sections 5.3, 5.4, 5.5Topic 5.3 Demonstration, Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 5.5 Lecture, Topic 5.5 Demonstrationworksheet20lec20-slides 

Homework 3, Checkpoint-1

  

 

Wed

Mar 17

Lecture 21: Actors

Module 2: 6.1, 6.2

Topic 6.1 Lecture ,   Topic 6.1 Demonstration ,   Topic 6.2 Lecture, Topic 6.2 Demonstration

worksheet21 lec21-slides  

 

  

 

Fri

Mar 19

Lecture 22: Actors (contd)

Module 2: 6.3, 6.4, 6.5Topic 6.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture , Topic 6.4 Demonstration,   Topic 6.5 Lecture, Topic 6.5 Demonstration worksheet22 lec22-slides 

Quiz for Unit 4

  

9

Mon

Mar 22

Lecture 23: Actors (contd)

Module 2: 6.6Topic 6.6 Lecture, Topic 6.6 Demonstration lec23-slidesQuiz for Unit 5

 

 

   

Wed

Mar 24

Lecture 24: Java Threads, Java synchronized statement

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lecture lec24-slides

 

 

    FriMar 26Spring "Sprinkle" Day (no class)        

10

Mon

Mar 29

Lecture 25: Java Threads, Java synchronized statement (contd), wait/notify

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lecture lec25-slides  

 

  

 

Wed

Mar 31

Lecture 26: Java Threads (exercise)

   lec26-handout  Homework 3 (all)  

 

Fri

Apr 02

Lecture 27: Java Locks

Module 2: 7.3Topic 7.3 Lecture  lec27-slides

Quiz for Unit 6

Quiz for Unit 5  

11

Mon

Apr 05

Lecture 28: Linearizability of Concurrent Objects

Module 2: 7.4Topic 7.4 Lecture lec28-slides

Homework 4 (includes one intermediate checkpoint)

 

 

  

 

Wed

Apr 07

Lecture 29:  Java Locks (exercise)

   lec29-handout  

 

  

 

Fri

Apr 09

Lecture 30: Safety and Liveness Properties, Java Synchronizers, Dining Philosophers Problem

Module 2: 7.5, 7.6Topic 7.5 Lecture, Topic 7.6 Lecture lec30-slides

Quiz for Unit 7

Quiz for Unit 6

  

12

Mon

Apr 12

Lecture 31: Message Passing Interface (MPI), (start of Module 3)

 Topic 8.1 Lecture, Topic 8.2 Lecture, Topic 8.3 Lecture lec31-slides

 

   

 

Wed

Apr 14

Lecture 32: Message Passing Interface (MPI, contd)

 Topic 8.4 Lecture  lec32-slides 

 

  

 

Fri

Apr 16

Lecture 33: Message Passing Interface (MPI, contd)

 Topic 8.5 Lecture, Topic 8 Demonstration Video lec33-slides

 

Homework 4 Checkpoint-1

  

13

Mon

Apr 19

Lecture 34: Task Affinity with Places

   

lec34-slides

  Quiz for Unit 8

Quiz for Unit 7  

 

Wed

Apr 21

Lecture 35: Eureka-style Speculative Task Parallelism

   lec35-slides 

 

  

 

Fri

Apr 24

Lecture 36: Algorithms based on Parallel Prefix (Scan) operations   lec36-slides

 

 

  

14

Mon

Apr 26

TBD

     

 

   WedApr 28Lecture 38: Course Review (Lectures 19-34)   lec38-slides Homework 4 (all)   FriApr 30TBD     Quiz for Unit 8  

Lab Schedule

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



worksheet16 lec16-slidesHomework 3
WS16-solution

7

Mon

Feb 20

Lecture 17: Midterm Review




lec17-slides




Wed

Feb 22

Lecture 18: Midterm Review




lec18-slides

WS18-solution


Fri

Feb 24 

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, worksheet19lec19-slides

WS19-solution

8

Mon

Feb 27

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 Demonstrationworksheet20lec20-slides      

WS20-solution


Wed

Mar 01

Lecture 21:  Atomic variables, Synchronized statements

Module 2: Sections 5.4, 7.2

Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lectureworksheet21lec21-slides
Homework 3WS21-solution


Fri

Mar 03

Lecture 22: Parallel Spanning Tree, other graph algorithms 


 worksheet22lec22-slidesHomework 4


WS22-solution

9

Mon

Mar 06

Lecture 23: Java Threads and Locks

Module 2: Sections 7.1, 7.3

Topic 7.1 Lecture, Topic 7.3 Lecture

worksheet23 lec23-slides


WS23-solution


Wed

Mar 08

Lecture 24: Java Locks - Soundness and progress guarantees  

Module 2: 7.5Topic 7.5 Lecture worksheet24 lec24-slides


WS24-solution


Fri

Mar 10

 Lecture 25: Dining Philosophers Problem  Module 2: 7.6Topic 7.6 Lectureworksheet25lec25-slides


WS25-solution

Mon

Mar 13

No class: Spring Break

 







WedMar 15No class: Spring Break








Fri

Mar 17

No class: Spring Break









10

Mon

Mar 20

Lecture 26: N-Body problem, applications and implementations 



worksheet26lec26-slides

WS26-solution


Wed

Mar 22

Lecture 27: Read-Write Locks, Linearizability of Concurrent Objects

Module 2: 7.3, 7.4Topic 7.3 Lecture, Topic 7.4 Lectureworksheet27lec27-slides



WS27-solution


Fri

Mar 24

Lecture 28: Message-Passing programming model with Actors

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 27

Lecture 29: Active Object Pattern. Combining Actors with task parallelism 

Module 2: 6.3, 6.4Topic 6.3 Lecture, Topic 6.3 Demonstration,   Topic 6.4 Lecture, Topic 6.4 Demonstrationworksheet29lec29-slides



WS29-solution


Wed

Mar 29

Lecture 30: Task Affinity and locality. Memory hierarchy 



worksheet30lec30-slides


Homework 4WS30-solution


Fri

Mar 31

Lecture 31: Data-Parallel Programming model. Loop-Level Parallelism, Loop Chunking

Module 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 Demonstrationworksheet31lec31-slidesHomework 5


WS31-solution

12

Mon

Apr 03

Lecture 32: Barrier Synchronization with PhasersModule 1: Section 3.4Topic 3.4 Lecture,  Topic 3.4 Demonstrationworksheet32lec32-slides



WS32-solution


Wed

Apr 05

Lecture 33:  Stencil computation. Point-to-point Synchronization with Phasers

Module 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


Fri

Apr 07

Lecture 34: Fuzzy Barriers with Phasers

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


WS34-solution

13

Mon

Apr 10

Lecture 35: Eureka-style Speculative Task Parallelism


worksheet35lec35-slides



WS35-solution

WedApr 12Lecture 36: Scan Pattern. Parallel Prefix Sum


worksheet36lec36-slides

WS36-solution

FriApr 14Lecture 37: Parallel Prefix Sum applications

worksheet37lec37-slides



14MonApr 17Lecture 38: Overview of other models and frameworks


lec38-slides




WedApr 19Lecture 39: Course Review (Lectures 19-38)


lec39-slides
Homework 5


FriApr 21Lecture 40: Course Review (Lectures 19-38)


lec40-slides



Lab Schedule

Lab #

Date (2023)

Topic

Handouts

Examples

1

Jan 09

Infrastructure setup

lab0-handout

lab1-handout


-Jan 16No lab this week (MLK)

2Jan 23Functional Programminglab2-handout

3

Jan 30

Futures

lab3-handout

4Feb 06Data-Driven Taskslab4-handout

5

Feb 13

Async / Finish

lab5-handout
-Feb 20No lab this week (Midterm Exam)

6

Feb 27

Recursive Task Cutoff Strategy

lab6-handout
7Mar 06Java Threadslab7-handout
-Mar 13No lab this week (Spring Break)

8Mar 20Concurrent Listslab8-handout
9Mar 27Actorslab9-handout
-Apr 03TBD

10

Apr 10

Loop Parallelism

lab10-handout

-

Apr 17

No lab this week

Lab #

Date (2021)

Topic

Handouts

Examples

0 Infrastructure Setuplab0-handout 

1

Jan 26

Async-Finish Parallel Programming with abstract metrics

lab1-handout
 -Feb 02No lab this week  

2

Feb 09

Futures

lab2-handout
 

3

Feb 16

Cutoff Strategy and Real World Performance

lab3-handout  4

Feb 23

DDFs

lab4-handout  -Mar 02No lab this week  

5

Mar 09

Loop-level Parallelism

lab5-handout lab5-intro

-

Mar 16

No lab this week (Spring "Sprinkle" Day)

  

-

 

Isolated Statement and Atomic Variables

  - Actors  -

 

Java Threads, Java Locks

  

-

 

Message Passing Interface (MPI)

  

-

 

Apache Spark

  

-

 

Eureka-style Speculative Task Parallelism

  - 

Java's ForkJoin Framework

  



Grading, Honor Code Policy, Processes and Procedures

...

Labs must be submitted by the following Monday Wednesday at 114:59pm30pm.  Labs must be checked off by a TA.

Worksheets should be completed by the deadline listed in Canvas before the start of the following class (for full credit) so that solutions to the worksheets can be discussed in the next class.

...