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COMP 322: Fundamentals of Parallel Programming (Spring

...

2024)

...


Instructor:

Mackale Joyner, DH 2063

TAs:
Elian Ahmar, Timothy Goh, Kelly Park, Tucker Reinhardt, Mantej Singh, Minh Vu, Thanh Vu, Robert Walsh, Frederick Wang, Xincheng Wang, Yidi Wang  
Haotian Dang, Andrew Ondara, Stefan Boskovic, Huzaifa Ali, Raahim Absar

Piazza site:

https://piazza.com/rice/spring2024

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

 

Piazza site:

https://piazza.com/rice/spring2021

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

Cross-listing:

ELEC 323

Lecture location:

Fully Online

Herzstein Amp

Lecture times:

MWF 1:

30pm

00pm -

2

1:

25pm

50pm

Lab locations:

Fully Online

Mon (Brockman 101)

Tue (Herzstein Amp)

Lab times:

Tu 1

Mon  3:

30pm

00pm -

2

3:

25pm

50pm (

TV

SB,

MS

HA,

TG, RW

AO)

Th 4

Tue   4:

50pm

00pm -

5

4:

45pm

50pm  (

XW, TR, KP, YW, FW, EA

RA, HD)

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 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

 



Week

Day

Date (2024

Week

Day

Date (2021 

)

Lecture

Assigned Reading

Assigned Videos (see Canvas site for video links)

In-class Worksheets

Slides

Work Assigned

Work Due

 
Worksheet Solutions

1

Mon

Jan

25Topic 1.1 Lecture, Topic 1.1 Demonstration

08

Lecture 1:

Task Creation and Termination (Async, Finish)Module 1: Section 1.1

Introduction



worksheet1lec1-
slides

 

 

  
slides  



WS1-solution
 


Wed

Jan

27

10

Lecture 2: 

Computation Graphs, Ideal ParallelismModule 1: Sections 1.2, 1.3Topic 1.2 Lecture, Topic 1.2 Demonstration, Topic 1.3 Lecture, Topic 1.3 Demonstration

Functional Programming



worksheet2
lec2
lec02-slides

Homework 1

 

   Fri



WS2-solution

FriJan 12
Jan 29
Lecture 3:
Abstract Performance Metrics, Multiprocessor SchedulingModule 1: Section 1.4Topic 1.4 Lecture, Topic 1.4 Demonstration
Higher order functions

worksheet3 
worksheet3
lec3-
slides 
slides   
  



WS3-solution

2

Mon

Feb 01

Lecture 4: Parallel Speedup and Amdahl's Law

Module 1: Section 1.5

Jan 15

No class: MLK










Wed

Jan 17

Lecture 4: Lazy Computation
Topic 1.5 Lecture, Topic 1.5 Demonstration



worksheet4lec4-slides
Quiz for Unit 1   


WS4-solution


Fri

Jan 19

Lecture 5: Java Streams



worksheet5lec5-slidesHomework 1
WS5-solution
3MonJan 22

Lecture 6: Map Reduce with Java Streams

 

Wed

Feb 03

Lecture 5: Future Tasks, Functional Parallelism ("Back to the Future")

Module 1: Section 2.
1
4Topic 2.
1
4 Lecture, Topic 2.
1
4 Demonstration  
worksheet5
worksheet6
lec5
lec6-slides
 



WS6-solution
   


Wed

Jan 24

Lecture 7: Futures

 

Fri

Feb 05

Lecture 6:   Finish Accumulators

Module 1: Section 2.
3
1Topic 2.
3
1 Lecture , Topic 2.
3
1 Demonstration
worksheet6
worksheet7
lec6
lec7-slides
 Quiz for Unit 1  



WS7-solution


Fri

Jan 26

Lecture 8:  Async, Finish, Computation Graphs

3MonFeb 08Lecture 7: Map Reduce

Module 1:
Section 2.4
Sections 1.1, 1.2Topic
2
1.
4
1 Lecture, Topic
2
1.
4 Demonstration  
1 Demonstration, Topic 1.2 Lecture, Topic 1.2 Demonstrationworksheet8lec8
worksheet7lec7
-slides
 


WS8-solution
 

4

 
Mon

 Lecture 8: Data Races, Functional & Structural Determinism


Jan 29 

Wed

Feb 10

Lecture 9: Ideal Parallelism, Data-Driven Tasks 

Module 1: Section

2

1.

5

3,

2

4.

6

5


Topic

2

1.

5

3 Lecture, Topic

2

1.

5

3 Demonstration, Topic

2

4.

6

5 Lecture, Topic

2

4.

6 Demonstration   

5 Demonstration

worksheet9

lec9-slides 

WS9-solution

WedJan 31Lecture 10: Event-based programming model




worksheet10lec10-slides
Homework 1WS10-solution
worksheet8lec8-slides

Homework 2

Homework 1   


FriFeb
12
02Lecture
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   
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 05

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 07

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 09

No class: Spring Recess










6

Mon

Feb 12

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 14

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



worksheet15lec15-slides



Homework 2WS15-solution

FriFeb 16

Lecture 16: Recursive Task Parallelism  



worksheet16 lec16-slidesHomework 3
WS16-solution

7

Mon

Feb 19

Lecture 17: Midterm Review




lec17-slides




Wed

Feb 21

Lecture 18: Midterm Review




lec18-slides




Fri

Feb 23 

Lecture 19:  Fork/Join programming model. OS Threads. Scheduler Pattern


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

WS19-solution

8

Mon

Feb 26 

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

Feb 28

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 01

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 04

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 06

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 08

 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 11

No class: Spring Break


 






WedMar 13No class: Spring Break








Fri

Mar 15

No class: Spring Break









10

Mon

Mar 18

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 20

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 22

Lecture 28: Dining Philosophers Problem


Topic 7.6 Lectureworksheet28lec28-slides




WS28-solution

11

Mon

Mar 25

Lecture 29:  Linearizability of Concurrent Objects

Module 2: Sections 7.4Topic 7.4 Lectureworksheet29lec29-slides



WS29-solution


Wed

Mar 27

Lecture 30:  Parallel Spanning Tree, other graph algorithms

 
worksheet30lec30-slides



WS30-solution


Fri

Mar 29

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 01

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

Homework 4

Homework 3 (All)

WS32-solution


Wed

Apr 03

Lecture 33: Task Affinity and locality. Memory hierarchy



worksheet33lec33-slides



WS33-solution


Fri

Apr 05

Lecture 34

comp322-s21-lab6.pdf4

Mon

 

Feb 15No class (weather)         WedFeb 17Spring "Sprinkle" Day (no class)         FriFeb 19No class (weather)        5

Mon

Feb 22

Lecture 10: Loop-Level Parallelism, Parallel Matrix MultiplicationModule 1: Sections 3.1, 3.2Topic 3.1 Lecture , Topic 3.1 Demonstration ,  Topic 3.2 Lecture,  Topic 3.2 Demonstrationworksheet10lec10-slides    

 

Wed

Feb 24

Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization

Module 1: Sections 3.3, 3.4

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

worksheet11lec11-slides    

 

Fri

Feb 26

 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)

        

 

Wed

Mar 03

Lecture 13: 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   FriMar 05

Lecture 14: 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 Demonstrationworksheet14 lec14-slidesQuiz for Unit 3   

7

Mon

Mar 08

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    

 

Wed

Mar 10

Lecture 16: Midterm Review

   lec16-slides    

 

Fri

Mar 12 

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  

 

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 Demonstrationworksheet19lec19-slides    

 

Fri

Mar 19

Lecture 20: 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

  

9

Mon

Mar 22

Lecture 21: Actors

Module 2: 6.1, 6.2

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

worksheet21 lec21-slides Quiz for Unit 5

 

  

 

Wed

Mar 24

Lecture 22: Actors (contd)

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

Homework 3, Checkpoint-1

  

 

Fri

Mar 26

Spring "Sprinkle" Day (no class)

 

     

 

 

  10

Mon

Mar 29

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 5

   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 6

   

 

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  

 

  

11

Mon

Apr 05

Lecture 26: Java Locks

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

 

Wed

Apr 07

Lecture 27: Linearizability of Concurrent Objects 

Module 2: 7.4Topic 7.4 Lecture worksheet27lec27-slides

 

   

 

Fri

Apr 09

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

Module 2: 7.5, 7.6Topic 7.5 Lecture, Topic 7.6 Lectureworksheet28lec28-slides

Quiz for Unit 7

 

 

  

12

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 Lectureworksheet30lec30-slides

 

   

 

Fri

Apr 16

Lecture 31: Message Passing Interface (MPI, contd)

  Topic 8.5 Lecture, Topic 8 Demonstration Videoworksheet31lec31-slides 

Quiz for Unit 7

  

13

Mon

Apr 19

Lecture 32: TBD

   lec32-slides

Quiz for Unit 8

Homework 4 Checkpoint-1

  

 

Wed

Apr 21

Lecture 34: Task Affinity with Places

   

lec34-slides

 

   

 

Fri

Apr 23

Lecture 35

: Eureka-style Speculative Task Parallelism

 
 

worksheet34
 
lec34-slides
lec35-slides 

 

  

14

Mon



WS34-solution

13

Mon

Apr 08

No class: Solar Eclipse









WedApr 10Lecture 35: Scan Pattern. Parallel Prefix Sum


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

FriApr 12
Apr 26
Lecture 36:
Algorithms based on
Parallel Prefix
(Scan) operations
Sum applications

worksheet36
   
lec36-slides

WS36-solution

 

Quiz for Unit 8

  

14MonApr 15Lecture 37: Overview of other models and frameworks


lec37-slides
 





WedApr
28
17Lecture
37lec37
38: Course Review (Lectures 19-34)
 
  

lec38-slides
 

Homework 4 (
all)   
All)


FriApr
30TBD       
19Lecture 39: Course Review (Lectures 19-34)


lec39-slides
 





Lab Schedule

Lab #

Date (

2021

2023)

Topic

Handouts

Examples

0 Infrastructure Setuplab0-handout

Handouts

Examples

 

1

Jan

26Async-Finish Parallel Programming with abstract metrics

08

Infrastructure setup

lab0-handout

lab1-handout


 


-
Feb 02
Jan 15No lab this week
  
(MLK)

2

Feb 09

Jan 22Functional Programming
Futures
lab2-handout

 -Feb 16No lab this week (classes cancelled)  

3

Feb 23

Cutoff Strategy and Real World Performance

Jan 29

Futures

lab3-handout
 


4

Mar 02

DDFs
Feb 05Data-Driven Taskslab4-handout
  

-

Mar 09

Feb 12

No lab this week

(Midterm exam)  



-
Mar 16
Feb 19No lab this week (
Spring "Sprinkle" Day)  
Midterm Exam)

5
Mar 23

Feb 26

Loop

-level Parallelism

Parallelism 

lab5-handout
lab5-intro
image kernels
6Mar
30Isolated Statement and Atomic Variables
04Recursive Task Cutoff Strategylab6-handout
 

-
Apr 06
Mar 11No lab this week (Spring
"Sprinkle" Day)  
Break)

7
Apr 13
Mar 18Java Threads
, Java Locks
lab7-handout
 

8
-
Mar 25

 

Actors

  

-

 

Message Passing Interface (MPI)

  

-

 

Apache Spark

  

-

 

Eureka-style Speculative Task Parallelism

  - 

Java's ForkJoin Framework

 
Concurrent Listslab8-handout
9Apr 01Actorslab9-handout
-

Apr 08

No lab this week (Solar Eclipse)



-

Apr 15

No lab this week

 



Grading, Honor Code Policy, Processes and Procedures

...

Labs must be submitted by the following Monday at 11:59pm3pm.  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.

...