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COMP 322: Fundamentals of Parallel Programming (Spring

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2025)

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Instructor:

Mackale Joyner, DH 2063

Head
TAs:
 Admin Assistant:Annepha Hurlock, annepha@rice.edu, DH 3122, 713-348-5186Undergraduate TAs:

Piazza site:

https://piazza.com/class/khclqrtu2133zo (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Fully Online

Lecture times:

MWF 1:30pm - 2:25pm

Lab locations:

Fully Online

Lab times:

Tu 1:30pm - 2:25pm, Th 4:50pm - 5:45pm

Course Syllabus

Raahim Absar, TJ Li

Piazza site:

https://piazza.com/rice/spring2025/comp322 (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Herzstein Amp

Lecture times:

MWF 1:00pm - 1:50pm

Lab location:

Brockman 101

Lab time:

Mon  3:00pm - 3:50pm 

Course Syllabus

A summary PDF file containing the course syllabus for 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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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.

...

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  handout (Concurrency)

There

...

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:

 

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

Lecture Schedule

 

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Week

...

Day

...

Date (2021)

...

Lecture

...

Assigned Videos (see Canvas site for video links)

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In-class Worksheets

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Work Assigned

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Work Due

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1

...

Mon

...

Jan 25

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Lecture 1: Task Creation and Termination (Async, Finish)

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Lecture Schedule



Week

Day

Date (2025)

Lecture

Assigned Reading

Assigned Videos (see Canvas site for video links)

In-class Worksheets

Slides

Work Assigned

Work Due

Worksheet Solutions

1

Mon

Jan 13

Lecture 1: Introduction



worksheet1lec1-slides  



WS1-solution


Wed

Jan 15

Lecture 2:  Functional Programming



worksheet2lec02-slides



WS2-solution

FriJan 17Lecture 3: Higher order functions

worksheet3 lec3-slides   



WS3-solution

2

Mon

Jan 20

No class: MLK










Wed

Jan 22

Lecture 4: Lazy Computation



worksheet4lec4-slides

WS4-solution


Fri

Jan 24

Lecture 5: Java Streams



worksheet5lec5-slidesHomework 1
WS5-solution
3MonJan 27

Lecture 6: Map Reduce with Java Streams

Module 1: Section 2.4Topic 2.4 Lecture, Topic 2.4 Demonstration  worksheet6lec6-slides



WS6-solution


Wed

Jan 29

Lecture 7: Futures

Module 1: Section 2.1Topic 2.1 Lecture , Topic 2.1 Demonstrationworksheet7lec7-slides



WS7-solution


Fri

Jan 31

Lecture 8:  Async, Finish, Computation Graphs

Module 1: Sections 1.1, 1.2Topic 1.1 Lecture, Topic 1.1 Demonstration, Topic 1.2 Lecture, Topic 1.2 Demonstrationworksheet8lec8-slides

WS8-solution

4

Mon


Feb 03 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 

WS9-solution

WedFeb 05Lecture 10: Event-based programming model




worksheet10lec10-slides
Homework 1WS10-solution

FriFeb 07Lecture 11: GUI programming, Scheduling/executing computation graphs

Module 1: Section 1.4Topic 1.4 Lecture , Topic 1.4 Demonstrationworksheet11lec11-slidesHomework 2
WS11-solution
5

Mon

Feb 10

Lecture 12: Abstract performance metrics, Parallel Speedup, Amdahl's Law Module 1: Section 1.5Topic 1.5 Lecture , Topic 1.5 Demonstrationworksheet12lec12-slides

WS12-solution


Wed

Feb 12

Lecture 13: Accumulation and reduction. Finish accumulators

Module 1: Section 2.3

Topic 2.3 Lecture   Topic 2.3 Demonstration

worksheet13lec13-slides 
WS13-solution


Fri

Feb 14

No class: Spring Recess










6

Mon

Feb 17

Lecture 14: Data Races, Functional & Structural Determinism

Module 1: Sections 2.5, 2.6Topic 2.5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.6 Lecture,  Topic 2.6 Demonstrationworksheet14lec14-slides

WS14-solution


Wed

Feb 19

Lecture 15: Limitations of Functional parallelism.
Abstract vs. real performance. Cutoff Strategy



worksheet15lec15-slides



Homework 2WS15-solution

FriFeb 21

Lecture 16: Recursive Task Parallelism  



worksheet16 lec16-slidesHomework 3
WS16-solution

7

Mon

Feb 24

Lecture 17: Midterm Review




lec17-slides




Wed

Feb 26

Lecture 18: Midterm Review




lec18-slides




Fri

Feb 28 

Lecture 19:  Fork/Join programming model


Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstrationworksheet19lec19-slides

WS19-solution

8

Mon

Mar 03 

Lecture 20: 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 Demonstrationworksheet20lec20-slides  

WS20-solution


Wed

Mar 05

Lecture 21: Barrier Synchronization with Phasers

Module 1: Sections 3.4 Topic 3.4 Lecture, Topic 3.4 Demonstrationworksheet21   lec21-slides

WS21-solution


Fri

Mar 07

Lecture 22: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 Demonstrationworksheet22lec22-slides

WS22-solution

9

Mon

Mar 10

Lecture 23: Fuzzy Barriers with Phasers

Module 1: Section 4.1 Topic 4.1 Lecture, Topic 4.1 Demonstrationworksheet23lec23-slides

Homework 3 (CP 1)

WS23-solution


Wed

Mar 12

Lecture 24: Confinement & Monitor Pattern. Critical sections
Global lock

Module 2: Sections 5.1, 5.2Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstrationworksheet24 lec24-slides


WS24-solution


Fri

Mar 14

 Lecture 25:  Atomic variables, Synchronized statementsModule 2: Sections 5.4, 7.2Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture worksheet25lec25-slides


WS25-solution

Mon

Mar 17

No class: Spring Break


 






WedMar 19No class: Spring Break








Fri

Mar 21

No class: Spring Break









10

Mon

Mar 24

Lecture 26: Java Threads and Locks

Module 2: Sections 7.1, 7.3Topic 7.1 Lecture, Topic 7.3 Lectureworksheet26lec26-slides

WS26-solution


Wed

Mar 26

Lecture 27: Read-Write Locks,  Soundness and progress guarantees

Module 2: Section 7.3Topic 7.3 Lecture, Topic 7.5 Lectureworksheet27lec27-slides


Homework 3 (CP 2)WS27-solution


Fri

Mar 28

Lecture 28: Dining Philosophers Problem


Topic 7.6 Lectureworksheet28lec28-slides




WS28-solution

11

Mon

Mar 31

Lecture 29:  Linearizability of Concurrent Objects

Module 2: Sections 7.4Topic 7.4 Lectureworksheet29lec29-slides



WS29-solution


Wed

Apr 02

Lecture 30:  Parallel Spanning Tree, other graph algorithms

 
worksheet30lec30-slides



WS30-solution


Fri

Apr 04

Lecture 31: Message-Passing programming model with Actors

Module 2: Sections 6.1, 6.2Topic 6.1 Lecture, Topic 6.1 Demonstration,   Topic 6.2 Lecture, Topic 6.2 Demonstrationworksheet31lec31-slides


WS31-solution

12

Mon

Apr 07

Lecture 32: Active Object Pattern. Combining Actors with task parallelismModule 2: Sections 6.3, 6.4Topic 6.3 Lecture, Topic 6.3 Demonstration,   Topic 6.4 Lecture, Topic 6.4 Demonstrationworksheet32lec32-slides



WS32-solution


Wed

Apr 09

Lecture 33: Task Affinity and locality. Memory hierarchy



worksheet33lec33-slides

Homework 4

Homework 3 (All)WS33-solution


Fri

Apr 11

Lecture 34: Eureka-style Speculative Task Parallelism

 
worksheet34lec34-slides


WS34-solution

13

Mon

Apr 14

No class: Solar Eclipse









WedApr 16Lecture 35: Scan Pattern. Parallel Prefix Sum


worksheet35lec35-slides
Homework 4 (CP 1)WS35-solution

FriApr 18Lecture 36: Parallel Prefix Sum applications

worksheet36lec36-slides

WS36-solution
14MonApr 21Lecture 37: Overview of other models and frameworks


lec37-slides




WedApr 23Lecture 38: Course Review (Lectures 19-34)
 
lec38-slides
Homework 4 (All)


FriApr 25Lecture 39: Course Review (Lectures 19-34)


lec39-slides




Lab Schedule

Lab #

Date (2025)

Topic

Handouts

Examples

1

Jan 13

Infrastructure setup

lab0-handout

lab1-handout


-Jan 20No lab this week (MLK)

2Jan 27Functional Programminglab2-handout

3

Feb 03

Futures

lab3-handout

4Feb 10Data-Driven Taskslab4-handout

-

Feb 17

No lab this week



-Feb 24No lab this week (Midterm Exam)

5

Mar 03

Loop Parallelism 

lab5-handoutimage kernels
6Mar 10Recursive Task Cutoff Strategylab6-handout
-Mar 17No lab this week (Spring Break)

7Mar 24Java Threadslab7-handout
-Mar 31No lab this week

8Apr 07Concurrent Listslab8-handout
9

Apr 14

Actors

lab9-handout

-

Apr 21

No lab this week

...

 

...

 

...

 

...

Wed

...

Jan 27

...

Lecture 2:  Computation Graphs, Ideal Parallelism

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Homework 1

...

 

...

 

...

2

...

Mon

...

Feb 01

...

Lecture 4: Parallel Speedup and Amdahl's Law

...

 

...

Wed

...

Feb 03

...

 

...

Fri

...

Feb 05

...

Lecture 6:   Finish Accumulators

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Lecture 7: Map Reduce

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Homework 2

...

 

...

Wed

...

Feb 10

...

Lecture 8: Data Races, Functional & Structural Determinism

...

 

...

 

...

Fri

...

Feb 12

...

Lecture 9: Java’s Fork/Join Library

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4

...

Mon

...

Feb 15

...

 

...

Fri

...

Feb 19

...

Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization

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Topic 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.4 Lecture  ,   Topic 3.4 Demonstration

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5

...

Mon

...

Feb 22

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Lecture 12:  Parallelism in Java Streams, Parallel Prefix Sums

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Wed

...

Feb 24

...

Lecture 13: Iterative Averaging Revisited, SPMD pattern

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Homework 3 (includes one intermediate checkpoint)

Quiz for Unit 3

...

 

...

Fri

...

Feb 26

...

Lecture 14: Data-Driven Tasks 

...

 

...

Wed

...

Mar 03

...

Lecture 15:  Point-to-point Synchronization with Phasers

...

 

...

Fri

...

Mar 05

...

Lecture 16: Pipeline Parallelism, Signal Statement, Fuzzy Barriers

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7

...

Mon

...

Mar 08

...

Lecture 17: Midterm Review

...

 

...

Wed

...

Mar 10

...

Lecture 18: Abstract vs. Real Performance

...

 

...

Fri

...

Mar 12

...

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

...

8

...

Mon

...

Mar 15

...

Lecture 20: Parallel Spanning Tree algorithm, Atomic variables

...

 

...

 

...

Wed

...

Mar 17

...

Lecture 21: Actors

...

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

...

 

...

 

...

Fri

...

Mar 19

...

Lecture 22: Actors (contd)

...

Quiz for Unit 4

...

9

...

Mon

...

Mar 22

...

Lecture 23: Actors (contd)

...

 

 

...

Wed

...

Mar 24

...

Lecture 24: Java Threads, Java synchronized statement

...

 

 

...

10

...

Mon

...

Mar 29

...

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

...

 

...

 

...

Wed

...

Mar 31

...

Lecture 26: Java Threads (exercise)

...

 

...

Fri

...

Apr 02

...

Lecture 27: Java Locks

...

Quiz for Unit 6

...

11

...

Mon

...

Apr 05

...

Lecture 28: Linearizability of Concurrent Objects

...

Homework 4 (includes one intermediate checkpoint)

...

 

 

...

 

...

Wed

...

Apr 07

...

Lecture 29:  Java Locks (exercise)

...

 

...

 

...

Fri

...

Apr 09

...

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

...

Quiz for Unit 7

...

Quiz for Unit 6

...

12

...

Mon

...

Apr 12

...

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

...

 

...

 

...

Wed

...

Apr 14

...

Lecture 32: Message Passing Interface (MPI, contd)

...

Homework 4 Checkpoint-1

...

 

...

Fri

...

Apr 16

...

Lecture 33: Message Passing Interface (MPI, contd)

...

 

...

 

...

13

...

Mon

...

Apr 19

...

Lecture 34: Task Affinity with Places

...

lec34-slides

...

  Quiz for Unit 8

...

 

...

Wed

...

Apr 21

...

Lecture 35: Eureka-style Speculative Task Parallelism

...

 

...

 

...

Fri

...

Apr 24

...

 

...

 

...

14

...

Mon

...

Apr 26

...

TBD

...

 

...

Lab Schedule

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

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Labs must be submitted by the following Monday at 11:59pmFriday at 4pm.  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.

...