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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

AO)

Th 4

Tue   4:

50pm

00pm -

5

4:

45pm

50pm  (

XW, RW, TR, KP, YW, FW

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 . 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 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

 

 

  
  



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

 

   FriJan 29Lecture 3: Abstract Performance Metrics, Multiprocessor SchedulingModule 1: Section 1.4Topic 1.4 Lecture, Topic 1.4 Demonstration



WS2-solution

FriJan 12Lecture 3: Higher order functions

worksheet3 
worksheet3
lec3-slides
 
 
 
 



WS3-solution

2

Mon

Jan 15

No class: MLK










Wed

Jan 17

Feb 01

Lecture 4:
Parallel Speedup and Amdahl's LawModule 1: Section 1.5Topic 1.5 Lecture, Topic 1.5 Demonstration
Lazy Computation



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
11: GUI programming, Scheduling/executing computation graphs

Module 1:
Sections 2.7, 2.8
Section 1.4Topic
2
1.
7
4 Lecture , Topic
2
1.
8 Lecture
4 Demonstration
worksheet9
worksheet11
lec9
lec11-slides
Quiz for Unit
Homework 2
   

WS11-solution
5
4

Mon

Feb

15

05

Lecture
10: Loop-Level Parallelism, Parallel Matrix Multiplication
12: Abstract performance metrics, Parallel Speedup, Amdahl's Law Module 1:
Sections 3.
Section 1
, 3
.
2
5Topic
3
1.
1
5 Lecture , Topic
3.1 Demonstration ,  Topic 3.2 Lecture,  Topic 3.2 Demonstration
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
worksheet10lec10
-slides 
 

WS13-solution
 


Fri

 

Feb 09

No class: Spring Recess










6

Mon

Feb 12

Lecture 14: Data Races, Functional & Structural Determinism

 WedFeb 17Spring "Sprinkle" Day (no class)        

 

Fri

Feb 19

Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization

Module 1: Sections
3
2.
3
5,
3
2.
4
6Topic
3
2.
3
5 Lecture ,  Topic
3
2.
3
5 Demonstration,  Topic
3
2.
4
6 Lecture
 
,  Topic
3
2.
4
6 Demonstration
worksheet11
worksheet14
lec11
lec14-slides
 Quiz for Unit 2  

5

Mon

Feb 22

Lecture 12:  Parallelism in Java Streams, Parallel Prefix Sums

Module 1: Section 3.7Topic Topic 3.7 Java Streams, Topic 3.7 Java Streams Demonstrationworksheet12lec12-slides     

Wed

Feb 24

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 Demonstrationworksheet14 lec14-slides    6MonMar 01Spring "Sprinkle" Day (no class)        

 

Wed

Mar 03



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.

Lecture 15:  

Point-to-point Synchronization with Phasers

Module 1:

Section

Sections 4.2, 4.3

Topic 4.2 Lecture,
 
Topic 4.2 Demonstration, Topic 4.3 Lecture,
 Topic
Topic 4.3 Demonstration
worksheet15
worksheet22
lec15
lec22-slides
 


WS22-solution
   

9

Mon

 

Fri

Mar

05

04

Lecture

16: Pipeline Parallelism, Signal Statement,

23: Fuzzy Barriers with Phasers

Module 1:
Sections 4.4, 4
Section 4.1
Topic
 Topic 4.
4 Lecture ,   Topic 4.4 Demonstration, Topic 4.1 Lecture,  Topic
1 Lecture, Topic 4.1 Demonstration
worksheet16
worksheet23
lec16
lec23-slides
Quiz for Unit 4Quiz for Unit 3  

7

Mon

Mar 08

Lecture 17: Midterm Review

   lec17-slides    

 

Wed

Mar 10

Lecture 18: Abstract vs. Real Performance

  worksheet18 lec18-slides     

 

Fri

Mar 12

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    

8

Mon

Mar 15

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 

Homework 3, Checkpoint-1

  

 

Wed

Mar 17

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  

 

  

 

Fri

Mar 19

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

  

9

Mon

Mar 22

Lecture 23: Actors (contd)

Module 2: 6.6Topic 6.6 Lecture, Topic 6.6 Demonstration lec23-slidesQuiz for Unit 5

 

 

   

Wed

Mar 24

Lecture 24: Java Threads, Java synchronized statement

Module 2: 7.1, 7.2Topic 7.1 Lecture, Topic 7.2 Lecture lec24-slides

 

 

    FriMar 26Spring "Sprinkle" Day (no class)        

10

Mon

Mar 29

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

Module 2: 7.1, 7.2

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.
2
3 Lecture
 
worksheet26
lec25-slides  

 

  

 

Wed

Mar 31

Lecture 26: Java Threads (exercise)

   lec26-handout  Homework 3 (all)  

 

Fri

lec26-slides

WS26-solution


Wed

Mar 20

Apr 02

Lecture 27:

Java Locks

Read-Write Locks,  Soundness and progress guarantees

Module 2: Section 7.3Topic 7.3 Lecture, Topic 7.5 Lecture
 
worksheet27lec27-slides

Quiz for Unit 6

Quiz for Unit 5 


Homework 3 (CP 2)WS27-solution


Fri

Mar 22

Lecture 28: Dining Philosophers Problem


Topic 7.6 Lectureworksheet28lec28-slides




WS28-solution
 

11

Mon

Apr 05

Mar 25

Lecture

28

29:

Linearizability

 Linearizability of Concurrent Objects

Module 2: Sections 7.4Topic 7.4 Lecture
 
worksheet29
lec28
lec29-slides

Homework 4 (includes one intermediate checkpoint)

 

 

  

 

Wed

Apr 07

Lecture 29:  Java Locks (exercise)

   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

 



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

12

01

Lecture
31: Message Passing Interface (MPI), (start of Module 3)
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 Demonstrationworksheet32
 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

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: Eureka-style Speculative Task Parallelism

 
worksheet34lec34-slides


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 12Lecture 36: Parallel Prefix Sum applications

worksheet36lec36-slides

WS36-solution
14MonApr 15Lecture 37: Overview of other models and frameworks


lec37-slides




WedApr 17

 

Fri

Apr 16

Lecture 33: Message Passing Interface (MPI, contd)

 Topic 8.5 Lecture, Topic 8 Demonstration Video lec33-slides

 

Homework 4 Checkpoint-1

  

13

Mon

Apr 19

Lecture 34: Task Affinity with Places

   

lec34-slides

  Quiz for Unit 8

Quiz for Unit 7  

 

Wed

Apr 21

Lecture 35: Eureka-style Speculative Task Parallelism

   lec35-slides 

 

  

 

Fri

Apr 24

Lecture 36: Algorithms based on Parallel Prefix (Scan) operations   lec36-slides

 

 

  

14

Mon

Apr 26

TBD

     

 

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

 
lec38-slides
 

Homework 4 (
all)   
All)


FriApr
30TBD     Quiz for Unit 8 
19Lecture 39: Course Review (Lectures 19-34)


lec39-slides
 





Lab Schedule

Lab #

Date (

2021

2023)

Topic

Handouts

Examples

0

1

 

Jan 08

Infrastructure

Setup

setup

lab0-handout

 

1

Jan 26

Async-Finish Parallel Programming with abstract metrics

lab1-handout


 


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

2

Feb 09

Jan 22Functional Programming
Futures
lab2-handout

 

3

Feb 16

Cutoff Strategy and Real World Performance

Jan 29

Futures

lab3-handout
 


4Feb
23DDFs
05Data-Driven Taskslab4-
handout  
handout

-

Mar 02

Feb 12

No lab this week

  

5

Mar 09

Loop-level Parallelism

lab5


-
handout 
Feb 19
lab5-intro

-

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

5

Feb 26

Loop Parallelism 

lab5-handoutimage kernels
6Mar 04Recursive Task Cutoff Strategylab6-handout
-Mar 11No lab this week (Spring Break)

7Mar 18Java Threadslab7-handout
8Mar 25Concurrent Listslab8-handout
9Apr 01Actorslab9-handout
-

Apr 08

No lab this week (Solar Eclipse)



-

Apr 15

No lab this week

  

-

 

Isolated Statement and Atomic Variables

  - Actors  -

 

Java Threads, Java Locks

  

-

 

Message Passing Interface (MPI)

  

-

 

Apache Spark

  

-

 

Eureka-style Speculative Task Parallelism

  - 

Java's ForkJoin Framework

  



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.

...