Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

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/spring2021spring2022/comp322 (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Fully OnlineTBD

Lecture times:

MWF 1:30pm 00pm - 21:25pm50pm

Lab locations:

Fully OnlineTBD

Lab times:

Tu 1Mon  3:30pm 00pm - 23:25pm 50pm (TV, MS, TG)

Th Tue 4:50pm 00pm - 54:45pm 50pm (XW, RW, TR)

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.

...

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)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

 

Topic 1.1 Lecture, Topic 1.1 Demonstration lec1-slidesWedFeb 03Topic 2.1 Lecture, Topic 2.1 Demonstration Future Tasks, Functional Parallelism ("Back to the Future")   MonFeb 08 Map Reduce4 4    Quiz for Unit 2Mon 15 Loop-Level Parallelism, Parallel Matrix Multiplication  Fri 19 11: Iteration Grouping (Chunking), Barrier Synchronization 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.   3Quiz for Unit 2Wed 246Spring "Sprinkle" Day (no class) WedMar 03 15:  Point-to-point Synchronization with Phasers42 42 43  Topic 4.3   Mar 10 24 Java Threads, Java synchronized statement1 Lecture, Topic 7.2 Lecture   26Spring "Sprinkle" Day (no class)10Mon 29lec25-slides Apr 02Apr 05 28 WedApr 07 29:  Java Locks (exercise) lec33lec34Quiz for Unit 7 21 35: Eureka-style Speculative Task Parallelism  24 36Algorithms based on (Scan) operations 26TBD

Week

Day

Date (20212022)

Lecture

Assigned Reading

Assigned Videos (see Canvas site for video links)

In-class Worksheets

Slides

Work Assigned

Work Due

 Worksheet Solutions 

1

Mon

Jan 2509

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

Module 1: Section 1.1worksheet1

Introduction

 

 

worksheet1lec1-slides  

 

 

 
WS1-solution 

 

Wed

Jan 2711

Lecture 2:  Computation Graphs, Ideal Parallelism

Module 1: Sections 1.2, 1.3Topic 1.2 Lecture, Topic 1.2 Demonstration, Topic 1.3 Lecture, Topic 1.3 Demonstrationworksheet2lec2-slides

Homework 1

 

 

Functional Programming

GList.java worksheet2lec02-slides

 

 

WS2-solution 
 FriJan 2913Lecture 3: Abstract Performance Metrics, Multiprocessor SchedulingModule 1: Section 1.4Topic 1.4 Lecture, Topic 1.4 Demonstrationworksheet3lec3-slidesHigher order functions  worksheet3 lec3-slides   

 

  WS3-solution 

2

Mon

Feb 01

Lecture 4: Parallel Speedup and Amdahl's Law

Module 1: Section 1.5Topic 1.5 Lecture, Topic 1.5 Demonstration

Jan 16

No class: MLK

        

 

Wed

Jan 18

Lecture 4: Lazy Computation

LazyList.java

Lazy.java

 worksheet4lec4-slidesQuiz for Unit 1   WS4-solution 

 

Fri

Jan 20

Module 1: Section 2.1

Lecture 5:

Java Streams

  worksheet5lec5-slidesHomework 1 WS5-solution 
3FriMonFeb 05Jan 23

Lecture 6:   Finish Accumulators Map Reduce with Java Streams

Module 1: Section 2.34Topic 2.3 4 Lecture, Topic 2.3 4 Demonstration  worksheet6lec6-slides

 

Quiz for Unit 1

 WS6-solution 3

 

Wed

Jan 25

Lecture 7:

Futures

Module 1: Section 2.41Topic 2.1 Lecture , Topic 2.1 Demonstrationworksheet7lec7-slides

 

 WS7-solution 

 

WedFri

Feb 10Jan 27

Lecture 8: Data Races, Functional & Structural Determinism  Computation Graphs, Ideal Parallelism

Module 1: Section Sections 1.2.5, 21.63Topic 1.2 .5 Lecture, Topic 1.2 .5 Demonstration, Topic 21.6 3 Lecture, Topic 21.6 3 Demonstration   worksheet8lec8-slides 

Homework 2

Homework 1 WS8-solution  

4

Mon

 

Fri

Feb 12

Jan 30 Lecture 9: Java’s Fork/Join LibraryAsync, Finish, Data-Driven Tasks 

Module 1:

Sections 2

Section 1.

7

1,

2

4.

8

5

 

Topic

2

1.

7 Lecture

1 Lecture, Topic 1.1 Demonstration, Topic

2

4.

8 Lecture

5 Lecture, Topic 4.5 Demonstration

worksheet9

lec9-slidesslides   WS9-solution 
 

4

WedFeb 01Module 1: Sections 3.1, 3.2Topic 3.1 Lecture , Topic 3.1 Demonstration ,  Topic 3.2 Lecture,  Topic 3.2 Demonstration Lecture 10: Event-based programming model

 

  worksheet10lec10-slides  Homework 1WS10-solution 
 WedFriFeb 17Spring "Sprinkle" Day (no class)03Lecture 11: GUI programming as an example of event-based,
futures/callbacks in GUI programming
   worksheet11  lec11-slidesHomework 2  WS11-solution 
5

Mon

Feb

06

Lecture 12: Scheduling/executing computation graphs
Abstract performance metrics
Module 1: Sections 3.3, 3Section 1.4Topic 1.4 Lecture , Topic 1.4 Demonstrationworksheet11worksheet12lec11lec12-slides  WS12-solution 

 

5

MonWed

Feb 2208

Lecture 12:  Parallelism in Java Streams, Parallel Prefix Sums 13: Parallel Speedup, Critical Path, Amdahl's Law

Module 1: Section 31.75

Topic

Topic 3.7 Java Streams

1.5 Lecture , Topic

3

1.

7 Java Streams

5 Demonstration

worksheet12worksheet13lec12lec13-slides   WS13-solution 

 

Fri

Feb

10

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 No class: Spring Recess

 

        
6

Mon

Feb 13

Lecture 14: Accumulation and reduction. Finish accumulators

Module 1: Section 2.3Topic 2.3 Lecture   Topic 2.3 Demonstrationworksheet14lec14-slides  WS14-solution 

 

Wed

MonMar 01Feb 15

Lecture 15: Recursive Task Parallelism  

   worksheet15 lec15-slides

 

 

 WS15-solution 
 FriFeb 17

Lecture

16: Data Races, Functional & Structural Determinism

Module 1: Section 4Sections 2.5, 2, 4.36Topic 2.5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.6 Lecture,  Topic 2.6 Demonstrationworksheet15worksheet16 lec15lec16-slidesHomework 3 Homework 2WS16-solution 

 7

FriMon

Mar 05Feb 20

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

17: Midterm Review

   lec17-slides    

7

Mon

Mar 08

Lecture 17: Midterm Review

   lec17-slides    

 

Wed

 

Wed

Feb 22

Lecture 18: Limitations of Functional parallelism.
Abstract vs.
Real Performancereal performance. Cutoff Strategy

  worksheet18lec18lec18-slides    WS18-solution 

 

FriMar 12

Feb 24 Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration

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

Module 2: Sections 5.1, 5.2, 5.6,

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

MonMar

15Feb 27

Lecture 20: Parallel Spanning Tree algorithm, Atomic variables Confinement & Monitor Pattern. Critical sections
Global lock

Module 2: Sections 5.31, 5.42, 5.56 Topic 5.1 Lecture, Topic 5.3 1 Demonstration, Topic 5.4 2 Lecture, Topic 5.4 2 Demonstration, Topic 5.5 6 Lecture, Topic 5.5 6 Demonstrationworksheet20lec20-slides        

Homework 3, Checkpoint-1

 WS20-solution 

 

Wed

Mar 1701

Lecture 21: Actors  Atomic variables, Synchronized statements

Module 2:

6

Sections 5.

1

4,

6

7.2

Topic 65.1 4 Lecture,   Topic 65.1 4 Demonstration,   Topic 67.2 Lecture, Topic 6.2 Demonstrationworksheet21lec21-slides   WS21-solution 

 

Fri

Mar 1903

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

  

Parallel Spanning Tree, other graph algorithms 

  worksheet22lec22-slidesHomework 4

Homework 3

WS22-solution 

9

Mon

Mar 2206

Lecture 23: Actors (contd)Java Threads and Locks

Module 2: 6.6Sections 7.1, 7.3

Topic

6

7.

6

1 Lecture, Topic

6

7.

6 Demonstration

3 Lecture

 worksheet23 lec23-slides Quiz for Unit 5 

 

 
WS23-solution 

 

Wed

Mar

08

Lecture 24:

Java Locks - Soundness and progress guarantees  

Module 2: 7.1, 7.25Topic 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 15

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

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lecture No class: Spring Break    

 

   

 

WedFri

Mar 3117

Lecture 26: Java Threads (exercise)No class: Spring Break

   lec26-handout   Homework 3 (all)

 

  

Fri

10

Mon

Mar 20

Quiz for Unit 5

Lecture 27: Java Locks

Module 2: 7.3Topic 7.3 Lecture  lec27-slides

Quiz for Unit 6

26: N-Body problem, applications and implementations 

  worksheet26lec26-slides   WS26-solution 

 

11

Mon

Wed

Mar 22

Lecture

27: Read-Write Locks, Linearizability of Concurrent Objects

Module 2: 7.3, 7.4Topic 7.3 Lecture, Topic 7.4 Lecture worksheet27lec28lec27-slides

Homework 4 (includes one intermediate checkpoint)

 

 WS27-solution 

 

Fri

Mar 24

Lecture

   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 

Homework 4 Checkpoint-1

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

 

 WS30-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

Homework 4

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 1607

Lecture 33: Message Passing Interface (MPI, contd)

 Topic 8.5 Lecture, Topic 8 Demonstration Video 

34: Fuzzy Barriers with Phasers

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

 

 
WS34-solution 

13

Mon

Apr 1910

Lecture 34: Task Affinity with Places35: Eureka-style Speculative Task Parallelism 

 

 worksheet35lec35-slides

  Quiz for Unit 8

 

 

WS35-solution 
 WedApr 12Lecture 36: Scan Pattern. Parallel Prefix Sum 

 

 
worksheet36lec35lec36-slides  WS36-solution 
 FriApr 14Lecture 37: Parallel Prefix Sum applications   worksheet37lec36lec37-slides    
14MonApr 17Lecture 38: Overview of other models and frameworks    lec38-slides    
 WedApr 2819Lecture 3839: Course Review (Lectures 19-3438)   lec38lec39-slides Homework 4 (all)   
 FriApr 30TBD21Lecture 40: Course Review (Lectures 19-38)    lec40-slides Quiz for Unit 8Homework 5  

Lab Schedule

0  Setup Futures 23DDFshandout Mar 16Spring "Sprinkle" Day ---Apache Spark   Java's ForkJoin Framework

Lab #

Date (20212023)

Topic

Handouts

Examples

1

Jan 09

Infrastructure

setup

lab0-handout

1

Jan 26

Async-Finish Parallel Programming with abstract metrics

lab1-handout

 
-Feb 02Jan 16No lab this week (MLK)  
2

Feb 09

Jan 23Functional Programminglab2-handout 

3

Feb 16

Cutoff Strategy and Real World Performance

Jan 30

Java Streams

lab3-handout
 
4Feb 06Futureslab4- -Mar 02No lab this weekhandout  

5

Mar 09Feb 13Loop

Data-

level Parallelism

Driven Tasks

lab5-handout handoutlab5-intro 
-Feb 20No lab this week (Midterm)  
6

Feb 27

Async / Finish

lab6-handout 

Isolated Statement and Atomic Variables

7Mar 06Recursive Task Cutoff Strategylab7-handout 
- ActorsMar 13No lab this week (Spring Break)  
8 Mar 20Java Threads, Java Locks  lab8-handout 

Message Passing Interface (MPI)

  
9Mar 27Concurrent Listslab9-handout 
10Apr 03Actorslab10-handout 

Eureka-style Speculative Task Parallelism

11

Apr 10

Loop Parallelism

lab11-handout 

-

 

Apr 17

No lab this week

  

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.

...