Versions Compared

Key

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

...

Instructors:

Mackale Joyner, DH 2063

Zoran Budimlić, DH 10383003

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 

 

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)

Lecture times:

MWF 1:00pm - 1:50pm

Lab locations:

Keck 100 (online 1st 2 weeks)

Lab times:

Mon  3:00pm - 3:50pm (Austin, Claire)

Wed 4:30pm - 5:20pm (Hunena, Mantej, Yidi, Victor, Rose, Adrienne, Diep, Maki)

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

...

There are also 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

 

 

Homework 3, Checkpoint-1Fri 26Spring "Sprinkle" Day (no class) 29Quiz for Unit 5Wed 31  24: Java Threads, Java synchronized statement lec25Apr 05 26: Java LocksFriApr 09 28 Safety and Liveness Properties, Java Synchronizers, Dining Philosophers Problem

 

 lec33Fri 23 34: Algorithms based on Parallel Prefix (Scan) operationsQuiz for Unit 814Mon 26 35 Algorithms based on (Scan) operations cont.

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 2510

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

Module 1: Section 1.1

Introduction

 

 Topic 1.1 Lecture, Topic 1.1 Demonstration

worksheet1lec1-slidesslides  

 

 

 
WS1-solution 

 

Wed

Jan 2712

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 2914Lecture 3: Abstract Performance Metrics, Multiprocessor SchedulingModule 1: Section 1.4Topic 1.4 Lecture, Topic 1.4 Demonstrationworksheet3 Higher order functions  worksheet3 lec3-slides   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 Demonstrationworksheet4lec4-slides

Jan 17

No class: MLK

     Quiz for Unit 1   

 

WedFeb

03Jan 19

Lecture 5: Future Tasks, Functional Parallelism ("Back to the Future")Module 1: Section 2.1Topic 2.1 Lecture, Topic 2.1 Demonstrationworksheet54: Lazy Computation

LazyList.java

Lazy.java

 worksheet4lec4lec5-slides   WS4-solution 

 

FriFeb

05Jan 21

Lecture 65:   Finish Accumulators

Module 1: Section 2.3Topic 2.3 Lecture, Topic 2.3 Demonstrationworksheet6lec6-slides Quiz for Unit 1

Java Streams

  worksheet5lec5-slidesHomework 1 WS5-solution  
3MonFeb 08Jan 24

Lecture 76: Map Reduce with Java Streams

Module 1: Section 2.4Topic 2.4 Lecture, Topic 2.4 Demonstration  worksheet7worksheet6lec7lec6-slides

 

  WS6-solution 

 

WedFeb

10Jan 26

Lecture 8: Data Races, Functional & Structural Determinism7: Futures

Module 1: Section 2.5, 2.61Topic 2.5 1 Lecture , Topic 2.5 Demonstration, Topic 2.6 Lecture, Topic 2.6 Demonstration   worksheet81 Demonstrationworksheet7lec7lec8-slides

Homework 2 

Homework 1 WS7-solution  

 

FriFeb

12Jan 28

Lecture 9: Java’s Fork/Join Library

 Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstrationworksheet9lec9-slidesQuiz for Unit 2 

8:  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 Demonstrationworksheet8lec8-slides  WS8-solution  

4

Mon

 

Feb 15No class (weather)      Jan 31 Lecture 9: Async, Finish, Data-Driven Tasks 

Module 1: Section 1.1, 4.5

 

Topic 1.1 Lecture, Topic 1.1 Demonstration, Topic 4.5 Lecture, Topic 4.5 Demonstration

worksheet9

lec9-slides   WS9-solution  
 WedFeb 17Spring "Sprinkle" Day (no class)02Lecture 10: Event-based programming model

 

   worksheet10lec10-slides   WS10-solution 
 FriFeb 19No class (weather)04Lecture 11: GUI programming as an example of event-based,
futures/callbacks in GUI programming
   worksheet11   lec11-slidesHomework 2Homework 1WS11-solution  
5

Mon

Feb 2207

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 2409

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

worksheet13lec13lec11-slides   WS13-solution 

 

Fri

Feb 2611

No class: Spring Recess

 Lecture 12: Data-Driven Tasks 

 

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 14

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 16

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 18

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 21

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   

17: Midterm Review

   lec17-slides    

 

WedMar

10Feb 23

Lecture 16: Midterm Review18: Limitations of Functional parallelism.
Abstract vs. real performance. Cutoff Strategy

   worksheet18lec16lec18-slides   WS18-solution 

 

Fri

Mar
12 Feb 25 

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 Demonstrationworksheet17

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, worksheet19lec19lec17-slides   WS19-solution 

8

MonMar 15

Feb 28

Lecture 18: Abstract vs. Real Performance

  worksheet18lec18-slides   Quiz for Unit 4Quiz for Unit 3  

20: Confinement & Monitor Pattern. Critical sections
Global lock

 

Wed

Mar 17

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 Demonstrationworksheet19worksheet20lec19lec20-slides      WS20-solution 

 

WedFri

Mar 1902

Lecture 20: Parallel Spanning Tree algorithm, 21:  Atomic variables, Synchronized statements

Module 2: Sections

5.3,

5.4,

5

7.

5

2

Topic 5.3 Demonstration, Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 57.5 Lecture, Topic 5.5 Demonstrationworksheet20lec20-slides 2 Lectureworksheet21lec21-slides  WS21-solutionQuiz for Unit 4 

 

9

MonFri

Mar 04

Lecture 22: Parallel Spanning Tree, other graph algorithms 

  worksheet22lec22-slidesHomework 4

Homework 3

WS22-solution 

9

Mon

Mar 07

Lecture 23: Java Threads and LocksLecture 21: Actors

Module 2: 6Sections 7.1, 67.23

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

worksheet21 lec21-slides Quiz for Unit 5

 

7.1 Lecture, Topic 7.3 Lecture

worksheet23 lec23-slides  

 

WS23-solution 

 

Wed

Mar 09

Lecture 24: Java Locks - Soundness and progress guarantees  

Module 2: 7.5Topic 7.5 Lecture worksheet24 lec24-slides 

 

WS24-solution  

 

WedFri

Mar 2411Lecture 22: Actors (contd)

 Lecture 25: Dining Philosophers Problem  Module 2: 6.3, 6.4Topic 6.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture , Topic 6.4 Demonstrationworksheet22 lec22-slides 7.6Topic 7.6 Lectureworksheet25lec25-slides 

 

WS25-solution 
 

Mon

Mar 14

No class: Spring Break

     

 

  
 WedMar 16No class: Spring Break    

 

   

 

 

Fri

10

Mon

Mar

18

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 

No class: Spring Break

     

 

  

10

Mon

Mar

21

Lecture

26: N-Body problem, applications and implementations 

  worksheet26lec26-slides   WS26-solutionModule 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lectureworksheet24lec24-slides

Quiz for Unit 6

  

 

FriWed

Apr 02Mar 23

Lecture 25: Java Threads, Java synchronized statement (contd), wait/notify27: Read-Write Locks, Linearizability of Concurrent Objects

Module 2: 7.13, 7.24Topic 7.1 3 Lecture, Topic 7.2 4 Lectureworksheet25worksheet27lec27-slides

 

 WS27-solution 

 

11

Mon

Fri

Mar 25

Lecture

28: Message-Passing programming model with Actors

Module 2: 7.3Topic 7.3 Lecture worksheet26lec26-slides Homework 4 (includes one intermediate checkpoint)Homework 3 (all)  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 28

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

 

Wed

Apr 07

Lecture 27: Linearizability of Concurrent Objects 

Module 2: 7.4Topic 7.4 Lecture worksheet27lec27-slides

 

 

 
WS29-solution 

 

Wed

Mar 30

Lecture

30:

Task Affinity and locality. Memory hierarchy 

  worksheet30lec30-slides

 

 WS30-solution Topic 7.5 Lecture, Topic 7.6 Lectureworksheet28lec28-slides

Quiz for Unit 7

 

 

12

MonFri

Apr 1201

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

 

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

Module 1: Sections 3.1, 3.2, 3.3Topic 3Topic 8.1 Lecture, Topic 83.1 Demonstration , Topic 3.2 Lecture, Topic 8 Topic 3.2 Demonstration, Topic 3.3 Lectureworksheet29,  Topic 3.3 Demonstrationworksheet31lec31lec29-slides

 

Quiz for Unit 6

Homework 5

Homework 4

WS31-solution  

 12

WedMon

Apr 1404

Lecture 30: Message Passing Interface (MPI, contd) Topic 8.4 Lectureworksheet3032: Barrier Synchronization with PhasersModule 1: Section 3.4Topic 3.4 Lecture,  Topic 3.4 Demonstrationworksheet32lec32lec30-slides

 

 

 
WS32-solution 

 

FriWed

Apr 1606

Lecture 31: Message Passing Interface (MPI, contd)

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

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-solutionQuiz for Unit 7 

 13

Fri

Mon

Apr 1908

Lecture 32: Task Affinity with Places

  worksheet32lec32-slides

 

Homework 4 Checkpoint-1

  

34: Fuzzy Barriers with Phasers

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

 

WS34-solution 

13

Mon

Apr 11

Lecture 35

 

Wed

Apr 21

Lecture 33: Eureka-style Speculative Task Parallelism 

 

worksheet33worksheet35lec35-slides

 

 

 
WS35-solution 
 WedApr 13Lecture 36: Scan Pattern. Parallel Prefix Sum 

 

worksheet34worksheet36lec34lec36-slides  WS36-solution 
 FriApr 15Lecture 37: Parallel Prefix Sum applications  worksheet35worksheet37lec35lec37-slides     
14WedMonApr 2818Lecture 36: Course Review (Lectures 19-33)38: Overview of other models and frameworks   lec36lec38-slides Homework 4 (all)   
 FriWedApr 3020Lecture 3739: Course Review (Lectures 19-3338)   lec37lec39-slides    

Lab Schedule

 FriApr 22Lecture 40: Course Review (Lectures 19-38)   lec40-slides Homework 5  

Lab Schedule

Isolated Statement and Atomic Variables-Apache Spark  Java'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

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

lab6-handout 
-Apr 06

Feb 21

No lab this week (

Spring "Sprinkle" Day

Midterm)

  
7Apr 13Feb 28Recursive Task Cutoff StrategyJava Threads, Java Lockslab7-handout 
8

Apr 20

Mar 07Java ThreadsActorslab8-handout 

-

Mar 14

No lab this week (Spring Break)

  
9Mar 21Concurrent Listslab9-handout 
10Mar 28Actorslab10-handout

Message Passing Interface (MPI)

   
11

Apr 04

Loop Parallelism

lab11-handout 

-

Apr 11

No lab this weekEureka-style Speculative Task Parallelism

  

-

 

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.

...