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COMP 322: Fundamentals of Parallel Programming (Spring
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2024)
Instructor: | Mackale Joyner, DH 2063 |
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Zoran Budimlić, DH 1038
TAs: |
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Haotian Dang, Andrew Ondara, Stefan Boskovic, Huzaifa Ali, Raahim Absar | |
Piazza site: |
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Piazza site:
/comp322 (Piazza is the preferred medium for all course communications) | Cross-listing: | ELEC 323 |
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Lecture location: | Herzstein |
Amp | Lecture times: | MWF 1:00pm - 1:50pm |
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Lab locations: |
Mon (Brockman 101) Tue (Herzstein Amp) | Lab times: | Mon 3:00pm - 3:50pm (SB, HA, AO) |
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Tue 4: |
00pm - |
4: |
50pm (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.
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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.
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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.
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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 (Concurrency)
There
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There are also a few optional textbooks that we will draw 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:
- Fork-Join Parallelism with a Data-Structures Focus (FJP) by Dan Grossman (Chapter 7 in Topics in Parallel and Distributed Computing)
- Java Concurrency in Practice by Brian Goetz with Tim Peierls, Joshua Bloch, Joseph Bowbeer, David Holmes and Doug Lea
- Principles of Parallel Programming by Calvin Lin and Lawrence Snyder
- The Art of Multiprocessor Programming by Maurice Herlihy and Nir Shavit
Finally, here are some additional resources that may be helpful for you:
- Slides titled "MPI-based Approaches for Java" by Bryan Carpenter
Lecture Schedule
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Week
Week |
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Day | Date ( |
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2024) | Lecture | Assigned Reading | Assigned Videos (see Canvas site for video links) | In-class Worksheets | Slides | Work Assigned | Work Due |
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Worksheet Solutions |
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1 | Mon | Jan |
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08 | Lecture 1: |
Introduction |
worksheet1 | lec1-slides |
WS1-solution |
Wed | Jan |
10 | Lecture 2: |
Homework 1
Functional Programming | worksheet2 | lec02-slides | WS2-solution |
Fri | Jan |
12 | Lecture 3: |
Higher order functions | worksheet3 | lec3-slides |
WS3-solution | |||||||||||
2 | Mon | Jan 15 | No class: MLK | ||||||||
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Wed | Jan 17 | Lecture 4: |
Lazy Computation | worksheet4 | lec4-slides | WS4-solution | ||||||||
Fri | Jan 19 | Lecture 5: Java Streams | worksheet5 | lec5-slides | Homework 1 | WS5-solution | |||||
3 | Mon | Jan 22 | Lecture 6: Map Reduce with Java Streams |
Wed
Jan 19
Module 1: Section 2. |
4 | Topic 2. |
4 Lecture, Topic 2. |
4 Demonstration |
worksheet6 |
lec6-slides |
WS6-solution | |||
Wed | Jan 24 | Lecture 7: Futures |
Fri
Jan 21
Module 1: Section 2. |
1 | Topic 2. |
1 Lecture , Topic 2. |
1 Demonstration |
worksheet7 |
lec7-slides |
WS7-solution | |||||||||||
Fri | Jan 26 | Lecture 8: Async, Finish, Computation Graphs | Module 1: Sections 1.1, 1.2 | Topic 1.1 Lecture, Topic 1.1 Demonstration, Topic 1.2 Lecture, Topic 1.2 Demonstration | worksheet8 | lec8-slides | WS8-solution | ||||
4 | Mon | Jan 29 | Lecture 9: Ideal Parallelism, Data-Driven Tasks | Module 1: Section 1.3, 4.5 | Topic 1.3 Lecture, Topic 1.3 Demonstration, Topic 4.5 Lecture, Topic 4.5 Demonstration | lec9-slides | WS9-solution | ||||
Wed | Jan 31 | Lecture 10: Event-based programming model | worksheet10 | lec10-slides | Homework 1 | WS10-solution | |||||
Fri | Feb 02 | Lecture 11: GUI programming, Scheduling/executing computation graphs | Module 1: Section 1.4 | Topic 1.4 Lecture , Topic 1.4 Demonstration | worksheet11 | lec11-slides | Homework 2 | WS11-solution | |||
5 | Mon | Feb 05 | Lecture 12: Abstract performance metrics, Parallel Speedup, Amdahl's Law | Module 1: Section 1.5 | Topic 1.5 Lecture , Topic 1.5 Demonstration | worksheet12 | lec12-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 | worksheet13 | lec13-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, 2.6 | Topic 2.5 Lecture , Topic 2.5 Demonstration, Topic 2.6 Lecture, Topic 2.6 Demonstration | worksheet14 | lec14-slides | WS14-solution | |||
Wed | Feb 14 | Lecture 15: Limitations of Functional parallelism. | worksheet15 | lec15-slides | Homework 2 | WS15-solution | |||||
Fri | Feb 16 | Lecture 16: Recursive Task Parallelism | worksheet16 | lec16-slides | Homework 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 Demonstration | worksheet19 | lec19-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, 3.3 | Topic 3.1 Lecture, Topic 3.1 Demonstration , Topic 3.2 Lecture, Topic 3.2 Demonstration, Topic 3.3 Lecture, Topic 3.3 Demonstration | worksheet20 | lec20-slides | WS20-solution | |||
Wed | Feb 28 | Lecture 21: Barrier Synchronization with Phasers | Module 1: Sections 3.4 | Topic 3.4 Lecture, Topic 3.4 Demonstration | worksheet21 | 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 Demonstration | worksheet22 | lec22-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 Demonstration | worksheet23 | lec23-slides | Homework 3 (CP 1) | WS23-solution | ||
Wed | Mar 06 | Lecture 24: Confinement & Monitor Pattern. Critical sections |
Lecture 7: Map Reduce
Wed
Jan 26
Lecture 8: Data Races, Functional & Structural Determinism
Homework 2
Fri
Jan 28
Lecture 9: Java’s Fork/Join Library
4
Mon
Feb 07
Wed
Feb 09
Lecture 11: Iteration Grouping (Chunking), Barrier Synchronization
Topic 3.3 Lecture , Topic 3.3 Demonstration, Topic 3.4 Lecture , Topic 3.4 Demonstration
Fri
Feb 11
Lecture 12: Data-Driven Tasks
Module 1: Sections 4.5
Topic 4.5 Lecture Topic 4.5 Demonstration
Mon
Feb 14
Wed
Lecture 13: Parallelism in Java Streams, Parallel Prefix Sums
Homework 3 (includes one intermediate checkpoint)
Lecture 14: Iterative Averaging Revisited, SPMD pattern
7
Mon
Feb 21
Lecture 15: Point-to-point Synchronization with Phasers
Wed
Feb 23
Lecture 16: Midterm Review
Fri
Lecture 17: Pipeline Parallelism, Signal Statement, Fuzzy Barriers
8
Mon
Feb 28
Lecture 18: Abstract vs. Real Performance
Wed
Mar 02
Module 2: Sections 5.1, 5.2 |
Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration |
worksheet24 |
lec24-slides |
WS24-solution | |||
Fri | Mar |
08 |
Lecture 25: Atomic variables, Synchronized statements | Module 2: Sections |
5.4, |
7. |
2 | Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic |
Quiz for Unit 4
9
Mon
Mar 07
Lecture 21: Actors
Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration
Wed
Mar 09
Lecture 22: Actors (contd)
Homework 3, Checkpoint-1
Fri
Mar 11
Mon
Lecture 23: Actors (contd)
Quiz for Unit 5
Quiz for Unit 6
Fri
Mar 18
Lecture 25: Java Threads, Java synchronized statement (contd), wait/notify
10
Mon
Mar 21
Lecture 26: Java Locks
Wed
Mar 23
Lecture 27: Linearizability of Concurrent Objects
Fri
Mar 25
Lecture 28: Safety and Liveness Properties, Java Synchronizers, Dining Philosophers Problem
Quiz for Unit 7
11
Mon
Mar 28
Lecture 29: Task Affinity and locality. Memory hierarchy
Quiz for Unit 6
Wed
Mar 30
Lecture 30: Reactor Pattern. Web servers
Fri
Apr 01
Lecture 31: Scan Pattern. Parallel Prefix Sum, uses and algorithms
Quiz for Unit 7
12
Mon
Apr 04
Homework 4 Checkpoint-1
Wed
Apr 06
Lecture 33: Barrier Synchronization with phasers
Topic 3.4 Lecture , Topic 3.4 Demonstration
Fri
Apr 08
Lecture 34: Stencil computation. Point-to-point Synchronization with Phasers
Quiz for Unit 8
13
Mon
Apr 11
Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration
Topic 6.3 Lecture , Topic 6.3 Demonstration , Topic 6.4 Lecture, Topic 6.4 Demonstration
Lab Schedule
7.2 Lecture | worksheet25 | lec25-slides | WS25-solution | ||||||||
Mon | Mar 11 | No class: Spring Break | |||||||||
Wed | Mar 13 | No class: Spring Break | |||||||||
Fri | Mar 15 | No class: Spring Break | |||||||||
10 | Mon | Mar 18 | Lecture 26: Parallel Spanning Tree, other graph algorithms | worksheet26 | lec26-slides | WS26-solution | |||||
Wed | Mar 20 | Lecture 27: Java Threads and Locks | Module 2: Sections 7.1, 7.3 | Topic 7.1 Lecture, Topic 7.3 Lecture | worksheet27 | lec27-slides | Homework 3 (CP 2) | WS27-solution | |||
Fri | Mar 22 | Lecture 28: Java Locks - Soundness and progress guarantees | Module 2: Section 7.5 | Topic 7.5 Lecture | worksheet28 | lec28-slides | WS28-solution | ||||
11 | Mon | Mar 25 | Lecture 29: Dining Philosophers Problem | Module 2: Section 7.6 | Topic 7.6 Lecture | worksheet29 | lec29-slides | WS29-solution | |||
Wed | Mar 27 | Lecture 30: Read-Write Locks, Linearizability of Concurrent Objects | Module 2: Sections 7.3, 7.4 | Topic 7.3 Lecture, Topic 7.4 Lecture | worksheet30 | lec30-slides | WS30-solution | ||||
Fri | Mar 29 | Lecture 31: Message-Passing programming model with Actors | Module 2: Sections 6.1, 6.2 | Topic 6.1 Lecture, Topic 6.1 Demonstration, Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet31 | lec31-slides | WS31-solution | ||||
12 | Mon | Apr 01 | Lecture 32: Active Object Pattern. Combining Actors with task parallelism | Module 2: Sections 6.3, 6.4 | Topic 6.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture, Topic 6.4 Demonstration | worksheet32 | lec32-slides | Homework 4 | Homework 3 (All) | WS32-solution | |
Wed | Apr 03 | Lecture 33: Task Affinity and locality. Memory hierarchy | worksheet33 | lec33-slides | WS33-solution | ||||||
Fri | Apr 05 | Lecture 34: Eureka-style Speculative Task Parallelism | worksheet34 | lec34-slides | WS34-solution | ||||||
13 | Mon | Apr 08 | No class: Solar Eclipse | ||||||||
Wed | Apr 10 | Lecture 35: Scan Pattern. Parallel Prefix Sum | worksheet35 | lec35-slides | Homework 4 (CP 1) | WS35-solution | |||||
Fri | Apr 12 | Lecture 36: Parallel Prefix Sum applications | worksheet36 | lec36-slides | WS36-solution | ||||||
14 | Mon | Apr 15 | Lecture 37: Overview of other models and frameworks | lec37-slides | |||||||
Wed | Apr 17 | Lecture 38: Course Review (Lectures 19-34) | lec38-slides | Homework 4 (All) | |||||||
Fri | Apr 19 | Lecture 39: Course Review (Lectures 19-34) | lec39-slides |
Lab Schedule
Lab # | Date (2023) | Topic | Handouts | Examples |
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1 | Jan 08 | Infrastructure setup | ||
- | Jan 15 | No lab this week (MLK) | ||
2 | Jan 22 | Functional Programming | lab2-handout | |
3 | Jan 29 | Futures | lab3-handout | |
4 | Feb 05 | Data-Driven Tasks | lab4-handout | |
- | Feb 12 | No lab this week | ||
- | Feb 19 | No lab this week (Midterm Exam) | ||
5 | Feb 26 | Loop Parallelism | lab5-handout | image kernels |
6 | Mar 04 | Recursive Task Cutoff Strategy | lab6-handout | |
- | Mar 11 | No lab this week (Spring Break) | ||
7 | Mar 18 | Java Threads | lab7-handout | |
8 | Mar 25 | Concurrent Lists | lab8-handout | |
9 | Apr 01 | Actors | lab9-handout | |
- | Apr 08 | No lab this week (Solar Eclipse) | ||
- | Apr 15 | No lab this week |
Lab #
Date (2021)
Topic
Handouts
Examples
1
Jan 10
Async-Finish Parallel Programming with abstract metrics
2
Jan 24
Futures
3
Feb 07
Cutoff Strategy and Real World Performance
Feb 14
DDFs
Feb 21
No lab this week (Midterm exam)
6
Mar 14
Isolated Statement and Atomic Variables
Apr 04
Actors
-
Apr 11
Message Passing Interface (MPI)
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Apr 18
Apache Spark
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Eureka-style Speculative Task Parallelism
Java's ForkJoin Framework
Grading, Honor Code Policy, Processes and Procedures
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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.
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