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COMP 322: Fundamentals of Parallel Programming (Spring

...

2023)

 

InstructorsInstructor:

Mackale Joyner, DH 2063

Zoran Budimlić, DH 1038

TAs:Adrienne Li, Austin Hushower, Claire Xu, Diep Hoang, Hunena Badat, Maki Yu, Mantej Singh, Rose Zhang, Victor Song, Yidi Wang 
Admin Assistant:Annepha Hurlock, annepha@rice.edu, DH 3122, 713-348-5186 

 

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/spring2022/comp322 (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Herzstein Amphitheater (online 1st 2 weeks)TBD

Lecture times:

MWF 1:00pm - 1:50pm

Lab locations:

Keck 100 (online 1st 2 weeks)TBD

Lab times:

Mon  3:00pm - 3:50pm ()

Wed Tue 4:30pm 00pm - 54:20pm 50pm ()

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 , MapReduce

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 instructor 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")   Feb 08 Map Reduce4 4    Quiz for Unit 24 15No class (weather) lec11lec15lec16lec19 lec30lec33Fri 23 34: Algorithms based on Parallel Prefix (Scan) operationsQuiz for Unit 814Mon 26 35 Algorithms based on (Scan) operations cont.

WeekWeek

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 1Functional 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 1WS6-solution 

 

3Mon

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

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

Module 1: Section 1.1, 4.5

 

Topic

2

1.

7

1 Lecture, Topic

2

1.

7

1 Demonstration, Topic

2

4.

8

5 Lecture, Topic

2

4.

8

5 Demonstration

worksheet9

lec9-slidesslides   WS9-solution 
 WedMon

 

Feb 01Lecture 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  
 FriFeb 19No class (weather)        
WS11-solution 
5

Mon

Feb 2206

Lecture 10: Loop-Level Parallelism, Parallel Matrix Multiplication12: Scheduling/executing computation graphs
Abstract performance metrics
Module 1: Sections 3.Section 1, 3.24Topic 31.1 4 Lecture , Topic 3. 1 Demonstration ,  Topic 3.2 Lecture,  Topic 3.2 .4 Demonstrationworksheet10worksheet12lec10lec12-slides   WS12-solution 

 

Wed

Feb 2408

Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization 13: Parallel Speedup, Critical Path, Amdahl's Law

Module 1: Sections 3.3, 3.4Section 1.5

Topic 31.3 5 Lecture , Topic 31.3 Demonstration, Topic 3.4 Lecture  ,   Topic 3.4 Demonstration

worksheet11

5 Demonstration

worksheet13lec13-slides   WS13-solution 

 

Fri

Feb 26 Lecture 12: Data-Driven Tasks10

No class: Spring Recess

 

 

Module 1: Sections 4.5

Topic 4.5 Lecture   Topic 4.5 Demonstration

worksheet12lec12-slides Quiz for Unit 2       
6

Mon

Mar 01

Spring "Sprinkle" Day (no class)

    

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

Mar
03Feb 15 

Lecture 1315: Parallelism in Java Streams, Parallel Prefix Sums 

Module 1: Sections 3.7Topic 3.7 Lecture , Topic 3.7 Demonstrationworksheet13lec13-slides

Homework 3 (includes one intermediate checkpoint)

 

Homework 2

Recursive Task Parallelism  

  worksheet15lec15-slides

 

 

 WS15-solution 
 FriMar 05Feb 17

Lecture 14: Iterative Averaging Revisited, SPMD pattern16: Data Races, Functional & Structural Determinism

Module 1: Sections 32.5, 32.6Topic 32.5 Lecture ,  Topic 32.5 Demonstration,  Topic 32.6 Lecture,  Topic 32.6 Demonstrationworksheet14 worksheet16 lec14lec16-slidesQuiz for Unit Homework 3  Homework 2WS16-solution 

7

MonMar

08Feb 20

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 Demonstrationworksheet15

17: Midterm Review

   lec17-slides    

 

Wed

Feb 22

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

  worksheet18lec18-slides   WS18-solution 

 

WedFriMar 10

Feb 24 

Lecture 16: Midterm Review

   

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

FriMon

Mar 12 

Feb 27

Lecture 17: 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 Demonstrationworksheet17lec17-slides    

8

Mon

Mar 15

Lecture 18: Abstract vs. Real Performance

  worksheet18lec18-slides   Quiz for Unit 4Quiz for Unit 3 

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 1701

Lecture 19: Critical Sections, Isolated construct (start of Module 2)21:  Atomic variables, Synchronized statements

Module 2: Sections 5.

1

4,

5

7.2

, 5.6,

Topic 5.1 4 Lecture, Topic 5.1 4 Demonstration, Topic 57.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstrationworksheet19worksheet21lec21-slides   WS21-solution 

 

Fri

Mar 1903

 

Lecture 2022: 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 

Quiz for Unit 4

, other graph algorithms 

  worksheet22lec22-slidesHomework 4

Homework 3

WS22-solution 

9

Mon

Mar 2206

Lecture 21: Actors23: Java Threads and Locks

Module 2: 6Sections 7.1, 67.23 

Topic 67.1 Lecture,   Topic 6.1 Demonstration ,   Topic 6.2 Lecture, Topic 6.2 Demonstration

worksheet21 lec21-slides Quiz for Unit 5

 

7.3 Lecture

worksheet23 lec23-slides  

 

WS23-solution 

 

Wed

Mar 2408

Lecture 22: Actors (contd)24: Java Locks - Soundness and progress guarantees  

Module 2: 6.3, 6.47.5Topic 67.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture , Topic 6.4 Demonstrationworksheet22 lec22-slides 

Homework 3, Checkpoint-1

 5 Lecture worksheet24 lec24-slides 

 

WS24-solution 

 

Fri

Mar 26

Spring "Sprinkle" Day (no class)

 

   

10

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

  

WS25-solution 
 10

Mon

Mar 2913

Lecture 23: Actors (contd)

Module 2: 6.5, 6.6Topic 6.5 Lecture, Topic 6.5 Demonstration, Topic 6.6 Lecture, Topic 6.6 Demonstrationworksheet23lec23-slides 

Quiz for Unit 5No class: Spring Break

     

 

  
 WedMar 31 Lecture 24: Java Threads, Java synchronized statementModule 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lectureworksheet24lec24-slides Quiz for Unit 615No class: Spring Break    

 

   

 

Fri

Apr 02

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

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lectureworksheet25lec25-slides

Mar 17

No class: Spring Break

     

 

  

1110

MonApr

05Mar 20

Lecture 26: Java Locks

Module 2: 7.3Topic 7.3 Lecture worksheet26

N-Body problem, applications and implementations 

  worksheet26lec26-slides Homework 4 (includes one intermediate checkpoint)Homework 3 (all)   WS26-solution 

 

WedApr 07

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 

 

FriApr

09Mar 24

Topic 7.5 Lecture, Topic 7.6 Lecture

Lecture 28: Safety and Liveness Properties, Java Synchronizers, Dining Philosophers Problem

 

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

Quiz for Unit 7 

 

 

 
WS28-solution 

1211

Mon

Apr 12

Lecture 29: Message Passing Interface (MPI), (start of Module 3)

 Topic 8.1 Lecture, Topic 8.2 Lecture, Topic 8.3 Lectureworksheet29lec29-slides

 

Quiz for Unit 6

  

 

Wed

Apr 14

Lecture 30: Message Passing Interface (MPI, contd)

 Topic 8.4 Lectureworksheet30

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 

 

FriWed

Apr 1605

Lecture 31: Message Passing Interface (MPI, contd)

  Topic 8.5 Lecture, Topic 8 Demonstration Videoworksheet31lec31-slidesQuiz for Unit 8

Quiz for Unit 733:  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 

 13

Fri

Mon

Apr 1907

Lecture 32: Task Affinity with Places

  worksheet32lec32-slides

 

Homework 4 Checkpoint-1

  

 

Wed

Apr 21

Lecture 3334: 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 

 

worksheet33worksheet35lec35-slides

 

 

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

 

worksheet34worksheet36lec34lec36-slides  WS36-solution 
 FriApr 14Lecture 37: Parallel Prefix Sum applications  worksheet35worksheet37lec35lec37-slides     
14WedMonApr 2817Lecture 36: Course Review (Lectures 19-33)38: Overview of other models and frameworks   lec36lec38-slides Homework 4 (all)   
 FriWedApr 3019Lecture 3739: Course Review (Lectures 19-3338)   lec37lec39-slides    

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
 
-Feb 16No lab this week (classes cancelled)  

3

Feb 23

Cutoff Strategy and Real World Performance

lab3-handout  
4

Mar 02

DDFs

lab4-handout  
-

Mar 09

No lab this week (Midterm exam)

  
-Mar 16No lab this week (Spring "Sprinkle" Day)  
5Mar 23Loop-level Parallelismlab5-handoutlab5-intro

6

Mar 30

Isolated Statement and Atomic Variables FriApr 21Lecture 40: Course Review (Lectures 19-38)   lec40-slides Homework 5  

Lab Schedule

-Apache Spark  Eureka-style Speculative Task ParallelismJava's ForkJoin Framework

Lab #

Date (2022)

Topic

Handouts

Examples

1

Jan 10

Infrastructure setup

lab0-handout

lab1-handout

 
2Jan 17Functional Programminglab2-handout 

3

Jan 24

Java Streams

lab3-handout
 
4Jan 31Futureslab4-handout 

5

Feb 07

Data-Driven Tasks

lab5-handout 
6

Feb 14

Async / Finish

lab6-handout 
-Apr 06

Feb 21

No lab this week (

Spring "Sprinkle" Day

Midterm)

  
7Apr 13Java Threads, Java LocksFeb 28Recursive Task Cutoff Strategylab7-handout 
8

Apr 20

ActorsMar 07Java Threadslab8-handout 

-

Mar 14

No lab this week (Spring Break)

  
9Mar 21Concurrent Listslab9-handout 

Message Passing Interface (MPI)

  10Mar 28Actorslab10-handout 
11

Apr 04

Loop Parallelism

lab11-handout 

-

Apr 11

No lab this week

  

-

 

Apr 18

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.

...