edX site | Autograder Guide |
COMP 322: Fundamentals of Parallel Programming (Spring
...
2024)
Instructor: | Mackale Joyner, DH 2063 |
---|
TAs: |
---|
Haotian Dang, Andrew Ondara, Stefan Boskovic, Huzaifa Ali, Raahim Absar | |
Piazza site: |
---|
Piazza site:
/comp322 (Piazza is the preferred medium for all course communications) | Cross-listing: | ELEC 323 |
---|---|---|
Lecture location: | Herzstein |
Amp | Lecture times: | MWF 1:00pm - 1:50pm |
---|---|---|
Lab locations: |
Mon (Brockman 101) Tue (Herzstein Amp) | Lab times: | Mon 3:00pm - 3:50pm ( |
---|
SB, HA, AO) |
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.
...
The desired learning outcomes fall into three major areas:
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.
...
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. 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 (Concurrency)
...
- 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
Lecture Schedule
...
Week | Day | Date ( |
---|
2024) | Lecture | Assigned Reading | Assigned Videos (see Canvas site for video links) | In-class Worksheets | Slides | Work Assigned | Work Due |
---|
Worksheet Solutions |
---|
1 | Mon | Jan |
---|
08 | Lecture 1: Introduction |
worksheet1 | lec1- |
Wed
slides | WS1-solution | |||
Wed | Jan 10 |
Lecture 2: 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 |
Wed |
Jan 17 | Lecture 4: Lazy Computation | worksheet4 | lec4-slides | WS4-solution |
Wed
Jan 19
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 |
Wed
Lecture 7: Futures | 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 |
futures/callbacks in GUI programming
Mon
Feb 07
, Scheduling/executing computation graphs |
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 |
Fri
Feb 11
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 |
Wed
Feb 23
Lecture 18: Limitations of Functional parallelism.
Abstract vs. real performance. Cutoff Strategy
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: |
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 | 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 |
Homework 3
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 | 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 7.2 Lecture |
Fri
Mar 11
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 |
Fri
Mar 18
No class: Spring Break
10
Mon
Mar 21
Lecture 26: Java Locks - Soundness and progress guarantees
Wed
Mar 23
Lecture 27: Dining Philosophers Problem
Fri
Mar 25
Lecture 28: Read-Write Pattern. Read-Write Locks. Fairness & starvation
11
Mon
Mar 28
Lecture 29: Task Affinity and locality. Memory hierarchy
Wed
Mar 30
Lecture 30: Reactor Pattern. Web servers
Fri
Apr 01
Lecture 31: Scan Pattern. Parallel Prefix Sum, uses and algorithms
Homework 4
12
Mon
Apr 04
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
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
Lab # | Date ( |
---|
2023) | Topic | Handouts | Examples |
---|---|---|---|
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 |
-
Jan 24
-
Feb 07
Feb 14
Feb 21
-
No lab this week (Spring Break) |
7 | Mar |
---|
18 |
Apr 04
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 |
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.
...