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COMP 322: Fundamentals of Parallel Programming (Spring

...

2022)

 

Head

InstructorInstructors:

Mackale Joyner, DH 2063

Zoran Budimlić, DH 3003

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, 713-348-5186Undergraduate TAs: 

 

Piazza site:

https://piazza.com/rice/spring2021spring2022/comp322 (Piazza is the preferred medium for all course communications)

Cross-listing:

ELEC 323

Lecture location:

Fully OnlineHerzstein Amphitheater (online 1st 2 weeks)

Lecture times:

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

Lab locations:

Fully OnlineKeck 100 (online 1st 2 weeks)

Lab times:

Tu 1Mon  3:30pm 00pm - 23:25pm, Th 50pm (Austin, Claire)

Wed 4:50pm 30pm - 5:45pm20pm (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  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

 

 

lec5lec8lec9 19 Iteration Grouping (Chunking), Barrier Synchronization Topic 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.4 Lecture  ,   Topic 3.4 Demonstration Quiz for Unit 22  Parallelism in Java Streams, Parallel Prefix Sums Topic 3.7 Java Streams 37 Java Streams   24 Iterative Averaging Revisited, SPMD pattern 3 3 , Topic 3.6 Lecture,   Topic 3.6 DemonstrationHomework 2lec14-slidesMar 05 Pipeline Parallelism, Signal Statement, Fuzzy Barriers44 44 41  Topic 4.1 Quiz for Unit 24 Java Threads, Java synchronized statement Wedlec29-handout     Fri 24Algorithms 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 2510

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

Module 1: Section 1.1

Topic 1.1 Lecture, Topic 1.1 Demonstration Introduction

 

 

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 Demonstrationworksheet3lec3-slides Higher 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 Demonstrationworksheet4lec4-slidesQuiz for Unit 1

Jan 17

No class: MLK

        

 

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

 worksheet4lec4-slides   WS4-solution 

 

FriFeb

05Jan 21

Lecture 65: Java Streams

  Finish AccumulatorsModule 1: Section 2.3Topic 2.3 Lecture, Topic 2.3 Demonstrationworksheet6lec6-slides Quiz for Unit  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 Demonstrationworksheet7lec7-slides

Homework 2 

Homework 1 WS7-solution 

 

FriFeb

12Jan 28

Lecture 9: Java’s Fork/Join Library8:  Computation Graphs, Ideal Parallelism

Module 1: Sections 1.2.7, 21.83Topic 1.2 .7 Lecture, Topic 1.2 Demonstration, Topic 1.8 Lectureworksheet93 Lecture, Topic 1.3 Demonstrationworksheet8lec8-slidesQuiz for Unit 2  WS8-solution 

4

Mon

Feb 15

Lecture 10: Loop-Level Parallelism, Parallel Matrix Multiplication

 

Jan 31 Lecture 9: Async, Finish, Data-Driven Tasks 

Module 1:

Sections 3

Section 1.1,

3

4.

2

5

 

Topic

3

1.1 Lecture, Topic

3

1.1 Demonstration,

 

Topic

3

4.

2

5 Lecture,

 

Topic

3

4.

2

5 Demonstration

worksheet10

worksheet9

lec10lec9-slidesslides    WS9-solution 
 WedFeb 17Spring "Sprinkle" Day (no class)02Lecture 10: Event-based programming model

 

   worksheet10 lec10-slides  WS10-solution 
 FriFeb 04Lecture 11: Module 1: Sections 3.3, 3.4 GUI programming as an example of event-based,
futures/callbacks in GUI programming
  worksheet11lec11-slides Homework 2 Homework 1WS11-solution 
5

Mon

Feb

07

Lecture 12: Scheduling/executing computation graphs
Abstract performance metrics
Module 1: Section 31.74Topic 1.4 Lecture , Topic 1.4 Demonstrationworksheet12lec12-slides  WS12-solution 

 

Wed

Feb

09

Lecture 13:

Parallel Speedup, Critical Path, Amdahl's Law

Module 1: Sections 3Section 1.5, 3.6

Topic

1.5 Lecture , Topic

1.5 Demonstration

worksheet13lec13-slides

Homework 3 (includes one intermediate checkpoint)

Quiz for Unit 3

  WS13-solution 

 

 

Fri

Feb 2611

Lecture 14: Data-Driven Tasks 

Module 1: Sections 4.5Topic 4.5 Lecture   Topic 4.5 Demonstrationworksheet14 No class: Spring Recess

 

        
6

Mon

Mar 01Spring "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 

 

WedMar 03

Feb 16

Lecture 15: Recursive Task Parallelism   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 Demonstration

  worksheet15lec15-slides

 

 

 WS15-solution 
 FriFeb 18

Lecture 16:

Data Races, Functional & Structural Determinism

Module 1: Sections 42.45, 42.16Topic 2.5 Lecture ,  Topic 2.5 Demonstration,  Topic 2.6 Lecture,  Topic 2.6 Demonstrationworksheet16 lec16-slidesQuiz for Unit 4Homework 3 Homework 2WS16-solution 

7

MonMar

08Feb 21

Lecture 17: Midterm  Midterm Review

   lec17-slides    

 

WedMar 10

Feb 23

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

  worksheet18lec18lec18-slides    WS18-solution 

 

FriMar 12

Feb 25 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 Homework 3, Checkpoint-1 WS19-solution 
 

8

MonMar

15Feb 28

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 5.3 1 Lecture, Topic 5.1 Demonstration, Topic 5.4 2 Lecture, Topic 5.4 2 Demonstration, Topic 5.5 6 Lecture, Topic 5.5 6 Demonstrationworksheet20lec20-slides        WS20-solution 

 

Wed

Mar 1702

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 1904

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

Parallel Spanning Tree, other graph algorithms 

  worksheet22lec22-slides Quiz for Unit Homework 4 

Homework 3

WS22-solution 

9

Mon

Mar 2207

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

 worksheet23lec23-slides Quiz for Unit 5 

 

 
WS23-solution 

 

Wed

Mar

09

Lecture 24:

Java Locks - Soundness and progress guarantees  

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lecture lec245Topic 7.5 Lecture worksheet24 lec24-slides 

 

WS24-solution 

 

Fri

Mar 11

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

 

WS25-solution 
 

Mon

Mar 14

No class: Spring Break

  FriMar 26Spring "Sprinkle" Day (no class)   

 

  
 WedMar 16No class: Spring Break    

 

   

10 

MonFri

Mar 2918

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

No class: Spring Break

     

 

  Wed

10

Mon

Mar 3121

Lecture 26: Java Threads (exercise) N-Body problem, applications and implementations 

  worksheet26lec26-handout slides Homework 3 (all) WS26-solution 

 

FriWed

Apr 02Mar 23

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

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

Quiz for Unit 6

Quiz for Unit 5

 

 WS27-solution 

 

11Fri

MonMar 25

Apr 05

Lecture 28: Linearizability of Concurrent Objects Message-Passing programming model with Actors

Module 2: 7.46.1, 6.2Topic 76.4 Lecture 1 Lecture, Topic 6.1 Demonstration,   Topic 6.2 Lecture, Topic 6.2 Demonstrationworksheet28lec28-slides

Homework 4 (includes one intermediate checkpoint)

 

 

 

 
WS28-solution 

11

Apr 07Mon

Mar 28

Lecture 29:   Java Locks (exercise)

   

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 

 

FriWed

Apr 09Mar 30

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

Module 2: 7.5, 7.6Topic 7.5 Lecture, Topic 7.6 Lecture 

Task Affinity and locality. Memory hierarchy 

  worksheet30lec30-slides

Quiz for Unit 7

Quiz for Unit 6

 

 WS30-solution 

 12

Fri

Mon

Apr 1201

Topic 8

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

 

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

Module 1: Sections 3.1, 3.2, 3.3Topic 3.1 Lecture, Topic 8.3.1 Demonstration , Topic 3.2 Lecture, Topic 8 Topic 3.2 Demonstration, Topic 3.3 Lecture,  Topic 3.3 Demonstrationworksheet31lec31-slides Homework 5  

Homework 4

WS31-solution 

 12

WedMon

Apr 1404

Lecture 32:  Message Passing Interface (MPI, contd) Topic 8.4 Lecture Barrier Synchronization with PhasersModule 1: Section 3.4Topic 3.4 Lecture,  Topic 3.4 Demonstrationworksheet32lec32-slides

 

Homework 4 Checkpoint-1 

WS32-solution 

  

Wed

Fri

Apr 1606

Lecture 33: Message Passing Interface (MPI, contd)

 Topic 8.5 Lecture, Topic 8 Demonstration Video

  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 1908

Lecture 34: Task Affinity with Places

  

 Fuzzy Barriers with Phasers

Module 1: Section 4.1Topic 4.1 Lecture, Topic 4.1 Demonstrationworksheet34lec34-slides  Quiz for Unit 8Quiz for Unit 7

 

 
WS34-solution Wed

13

Mon

Apr 2111

Lecture 35: Eureka-style Speculative Task Parallelism 

 

 worksheet35lec35-slides

 

 

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

 

 
worksheet36lec36-slides  WS36-solution 
 FriApr 15Lecture 37: Parallel Prefix Sum applications  worksheet37lec37-slides    
14MonApr 18Lecture 38: Overview of other models and frameworks    lec38-slides    
 WedApr 2820Lecture 3839: Course Review (Lectures 19-3438)   lec38lec39-slides Homework 4 (all)   
 FriApr 30TBD22Lecture 40: Course Review (Lectures 19-38)    lec40-slides Quiz for Unit 8Homework 5  

Lab Schedule

0  Setup1 26lab1- 2Feb 09lab25Mar 16 "Sprinkle" DayApache Spark

Lab #

Date (20212022)

Topic

Handouts

Examples

1

Jan 10

Infrastructure

setup

lab0-handout

lab1-handout

 
2Jan

Async-Finish Parallel Programming with abstract metrics

17Functional Programminglab2-handout 

3

Feb 02No lab this week

Jan 24

Java Streams

lab3-handout
 
4Jan 31Futureslab4-handout 

35

Feb 16

Cutoff Strategy and Real World Performance

lab3

07

Data-Driven Tasks

lab5-handout 
46

Feb 2314

DDFsAsync / Finish

lab4lab6-handout handout 
-Mar 02

Feb 21

No lab this week (Midterm)

  
7

Mar 09

Loop-level Parallelism

lab5-handout lab5-intro

-

Feb 28Recursive Task Cutoff Strategylab7-handout 
8Mar 07Java Threadslab8-handout 

-

Mar 14

No lab this week (Spring

Break)

  
-9

 

Isolated Statement and Atomic Variables

 Mar 21Concurrent Listslab9-handout 
-10 Mar 28Actors  lab10-handout 

Java Threads, Java Locks

  

-

 

Message Passing Interface (MPI)

  

-

 

11

Apr 04

Loop Parallelism

lab11-handout 

-

Apr 11

No lab this week

  

-

 

Eureka-style Speculative Task ParallelismApr 18

No lab this week

  
- 

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.

...