edX site | Autograder Guide |
COMP 322: Fundamentals of Parallel Programming (Spring
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2024)
Instructor: | Mackale Joyner, DH 2063 |
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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:
There
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There are also a few optional 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
Week | 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 |
08 | Lecture 1: Introduction |
worksheet1 | lec1-slides |
WS1-solution |
Wed | Jan |
10 | Lecture 2: Functional Programming |
worksheet2 |
lec02-slides |
Homework 1
WS2-solution | |||
Fri | Jan |
12 | Lecture 3: Higher order functions | worksheet3 |
lec3-slides |
WS3-solution | ||
2 | Mon | Jan |
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15 | No class: MLK |
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 | Module 1: Section 2.4 | Topic 2.4 Lecture, Topic 2.4 Demonstration | worksheet6 | lec6-slides |
WS6-solution | ||
Wed | Jan |
24 | Lecture 7: Futures | Module 1: Section 2.1 | Topic 2.1 Lecture , Topic 2.1 Demonstration | worksheet7 | lec7-slides |
Homework 2
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 |
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4
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 |
Mon
Feb 07
, |
futures/callbacks in GUI programming
Scheduling/executing computation graphs |
Abstract performance metrics
Module 1: Section 1.4 | Topic 1.4 Lecture , Topic 1.4 Demonstration |
worksheet11 |
lec11-slides |
Wed
Feb 09
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 |
Fri
Feb 11
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 3 (includes one intermediate checkpoint)
Homework 2 |
WS15-solution | ||
Fri | Feb |
16 | Lecture 16: |
Recursive Task Parallelism | worksheet16 | lec16-slides |
Homework 3 |
WS16-solution | ||
7 | Mon | Feb |
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19 | Lecture 17: Midterm Review |
lec17-slides |
Wed | Feb |
21 | Lecture 18: |
Abstract vs. real performance. Cutoff Strategy
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 |
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26 | Lecture 20: |
Global lock
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 |
Wed
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 |
Quiz for Unit 4
WS22-solution | ||
9 | Mon | Mar |
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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 | 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 |
Homework 3, Checkpoint-1
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 7.2 Lecture | worksheet25 |
lec25-slides |
Quiz for Unit 5
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 |
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18 | Lecture 26: Java Threads and Locks |
Module 2: Sections 7. |
1, 7.3 | Topic 7. |
1 Lecture, Topic 7.3 Lecture | worksheet26 | lec26-slides |
WS26-solution | ||
Wed | Mar |
20 | Lecture 27: |
Read-Write Locks, Soundness and progress guarantees | Module 2: Section 7. |
3 | Topic 7. |
3 Lecture, Topic 7. |
5 Lecture | worksheet27 | lec27-slides |
Homework 3 (CP 2) | WS27-solution | ||
Fri | Mar |
22 | Lecture 28: |
Dining Philosophers Problem | Topic 7. |
6 Lecture | worksheet28 | lec28-slides |
Quiz for Unit 7
WS28-solution | |||
11 | Mon | Mar |
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25 | Lecture 29: |
Linearizability of Concurrent Objects | Module 2: Sections 7.4 | Topic 7.4 Lecture |
worksheet29 | lec29-slides |
Quiz for Unit 6
WS29-solution | ||
Wed | Mar |
27 | Lecture 30: |
Parallel Spanning Tree, other graph algorithms | worksheet30 | lec30-slides |
Fri
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 |
Quiz for Unit 7
12
Mon
WS31-solution | |||
12 | Mon | Apr 01 |
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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 3 (All) | WS32-solution |
Wed | Apr |
03 | Lecture 33: |
Topic 3.4 Lecture , Topic 3.4 Demonstration
Task Affinity and locality. Memory hierarchy | worksheet33 | lec33-slides |
WS33-solution | |||
Fri | Apr |
05 | Lecture 34: |
Eureka-style Speculative Task Parallelism | worksheet34 | lec34-slides |
Quiz for Unit 8
WS34-solution | |||
13 |
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Mon | Apr |
08 |
Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration
No class: Solar Eclipse | ||||||||
Wed | Apr |
10 | Lecture |
35: |
Scan Pattern. Parallel Prefix Sum | worksheet35 | lec35-slides |
Topic 6.3 Lecture , Topic 6.3 Demonstration , Topic 6.4 Lecture, Topic 6.4 Demonstration
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 ( |
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2023) | Topic | Handouts | Examples |
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1 |
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Jan 08 | Infrastructure |
setup |
1
Jan 10
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15 | No lab this week (MLK) |
2 | Jan |
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22 |
Functional Programming | lab2-handout |
3 | Jan |
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3
Feb 07
29 | Futures | lab3-handout |
4 | Feb |
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05 | Data-Driven Tasks | lab4- |
handout | |
- | Feb |
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12 | No lab this week |
- | Feb |
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19 | No lab this week (Midterm Exam) |
5 |
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Feb 26 | Loop |
Parallelism | lab5-handout |
image kernels | |
6 | Mar |
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04 | Recursive Task Cutoff Strategy | lab6-handout |
- | Mar |
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11 | No lab this week (Spring Break) |
7 | Mar |
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18 | Java Threads |
lab7-handout |
8 |
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Apr 04
Mar 25 | Concurrent Lists |
lab8-handout |
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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
9 | Apr 01 | Actors | lab9-handout | |
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- | Apr 08 | No lab this week (Solar Eclipse) | ||
- | Apr 15 | No lab this week |
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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