COMP 322: Fundamentals of Parallel Programming (Spring
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2023)
InstructorsInstructor: | Mackale Joyner, DH 2063 Zoran Budimlić, DH 3003 | TAs: | Adrienne Li, Austin Hushower, Claire Xu, Diep Hoang, Hunena Badat, Maki Yu, Mantej Singh, Rose Zhang, Victor Song, Yidi Wang |
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| Admin Assistant: | Annepha Hurlock, annepha@rice.edu, DH 3122, 713-348-5186 |
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| Mohamed Abead, Chase Hartsell, Taha Hasan, Harrison Huang, Jerry Jiang, Jasmine Lee, Michelle Lee, Hung Nguyen, Quang Nguyen, Ryan Ramos, Oscar Reynozo, Delaney Schultz, Tina Wen, Raiyan Zannat, Kailin Zhang | |||
Piazza site: | https://piazza.com/rice/spring2022/comp322 (Piazza is the preferred medium for all course communications) | Cross-listing: | ELEC 323 |
Lecture location: | Herzstein Amphitheater (online 1st 2 weeks)TBD | Lecture times: | MWF 1:00pm - 1:50pm |
Lab locations: | Keck 100 (online 1st 2 weeks)TBD | Lab times: | Mon 3:00pm - 3:50pm () Wed Tue 4:30pm 00pm - 54:20pm (Claire, Hunena, Mantej, Yidi50pm () |
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 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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- Module 1 handout (Parallelism)
- Module 2 handout (Concurrency)
There
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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:
- 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 Lecture Schedule
Week | Day | Date (2022) | Lecture | Assigned Reading | Assigned Videos (see Canvas site for video links) | In-class Worksheets | Slides | Work Assigned | Work Due | Worksheet Solutions | |||||||||||||
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1 | Mon | Jan 1009 | Lecture 1: Introduction |
| worksheet1 | lec1-slidesslides |
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| Wed | Jan 1211 | Lecture 2: Functional Programming | GList.java | worksheet2 | lec2lec02-slides |
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| Fri | Jan 1413 | Lecture 3: Higher order functions | worksheet3worksheet3 | lec3-slidesslides |
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2 | Mon | Jan 1716 | No class: MLK | ||||||||||||||||||||
| Wed | Jan 1918 | Lecture 4: Lazy Computation | LazyList.java Lazy.java | worksheet4 | lec4-slides | WS4-solution | ||||||||||||||||
| Fri | Jan 2120 | Lecture 5: Java Streams | worksheet5 | lec5-slides | Homework 1 | WS5-solution | ||||||||||||||||
| 3 | Mon | Jan 2423 | Lecture 6: Map Reduce with Java Streams | Module 1: Section 2.4 | Topic 2.4 Lecture, Topic 2.4 Demonstration | worksheet6 | lec6-slides |
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| Wed | Jan 2625 | Lecture 7: Futures | Module 1: Section 2.1 | Topic 2.1 Lecture , Topic 2.1 Demonstration | worksheet7 | lec7-slides |
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| Fri | Jan 2827 | Lecture 8: Computation Graphs, Ideal Parallelism | Module 1: Sections 1.2, 1.3 | Topic 1.2 Lecture, Topic 1.2 Demonstration, Topic 1.3 Lecture, Topic 1.3 Demonstration | worksheet8 | lec8-slides | WS8-solution | |||||||||||||||
4 | Mon
| Jan 3130 | Lecture 9: Async, Finish, Data-Driven Tasks | Module 1: Section 1.1, 4.5
| Topic 1.1 Lecture, Topic 1.1 Demonstration, Topic 4.5 Lecture , Topic 4.5 Demonstration | worksheet9 | lec9-slides | WS9-solution | |||||||||||||||
| Wed | Feb 0201 | Lecture 10: Event-based programming model
| worksheet10 | lec10-slides | Homework 1 | WS10-solution | |||||||||||||||||
| Fri | Feb 0403 | Lecture 11: GUI programming as an example of event-based, futures/callbacks in GUI programming | worksheet11 | lec11-slides | Homework 2 | WS11-solution | |||||||||||||||||
| 5 | Mon | Feb 0706 | Lecture 12: Scheduling/executing computation graphs Abstract performance metrics | Module 1: Section 1.4 | Topic 1.4 Lecture , Topic 1.4 Demonstration | worksheet12 | lec12-slides | WS12-solution | |||||||||||||||
| Wed | Feb 0908 | Lecture 13: Lightweight task parallelism. Finish/async Parallel Speedup, Critical Path, Amdahl's Law | Module 1: Section 1.15 | Topic 1.1 5 Lecture , Topic 1.1 5 Demonstration | worksheet13 | lec13-slides | WS13-solution | |||||||||||||||
| Fri | Feb 1110 | No class: Spring Recess
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| 6 | Mon | Feb 1413 | Lecture 14: Parallel Speedup, Critical Path, Amdah's Law Accumulation and reduction. Finish accumulators | Module 1: Section 12.53 | Topic 12.5 3 Lecture Topic 12.5 3 Demonstration | worksheet14 | lec14-slides | WS14-solution | |||||||||||||||
| Wed | Feb 1615 | Lecture 15: Recursive Task Parallelism | worksheet15 | lec15-slides |
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| Fri | Feb 1817 | Lecture 16: Accumulation and reduction. Finish accumulatorsData Races, Functional & Structural Determinism | Module 1: Section Sections 2.5, 2.36 | Topic 2.3 5 Lecture , Topic 2.3 Demonstration | worksheet16 | 5 Demonstration, Topic 2.6 Lecture, Topic 2.6 Demonstration | worksheet16 | lec16-slides | Homework 3 | Homework 2 | WS16-solution | ||||||||||||
7 | Mon | Feb 2120 | Lecture 17: Midterm Review | lec17-slides | |||||||||||||||||||
| Wed | Feb 2322 | Lecture 18: Limitations of Functional parallelism. | worksheet18 | lec18-slides | WS18-solution | |||||||||||||||||
| Fri | Feb 25 24 | Lecture 19: Data Races, Functional & Structural Determinism Fork/Join programming model. OS Threads. Scheduler Pattern | Module 1: Sections 2.5, 2.6 | Topic 2.5 7 Lecture, Topic 2.5 7 Demonstration, Topic 2.6 8 Lecture, Topic 2.6 8 Demonstration, | worksheet19 | lec19-slides | WS19-solution | |||||||||||||||
8 | Mon | Feb 2827 | Lecture 20: Confinement & Monitor Pattern. Critical sections | 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 Demonstration | worksheet20 | lec20lec20-slides | WS20-solution | |||||||||||||||
| Wed | Mar 0201 | Lecture 21: N-Body problem, applications and implementations | Atomic variables, Synchronized statements | Module 2: Sections 5.4, 7.2 | Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 7.2 Lecture | worksheet21 | lec21-slides | WS21-solution | ||||||||||||||
| Fri | Mar 0403 | Lecture 22: Fork/Join programming model. OS Threads. Scheduler Pattern | Module 2: Sections 2.7, 2.8 | Parallel Spanning Tree, other graph algorithms | Topic 2.7 Lecture, Topic 2.7 Demonstration, Topic 2.8 Lecture, Topic 2.8 Demonstration, | worksheet22 | lec22-slides | Homework 4 |
| Homework 3 | WS22-solution | |||||||||||
9 | Mon | Mar 0706 | Lecture 23: Locks, Atomic variables Java Threads and Locks | Module 2: Sections 7.1, 7.3 | Topic 7.1 Lecture, Topic 7.3 Lecture | worksheet23 | lec23-slides |
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| Wed | Mar 0908 | Lecture 24: Parallel Spanning Tree, other graph algorithms | Java Locks - Soundness and progress guarantees | Module 2: 7.5 | Topic 7.5 Lecture | worksheet24 | lec24-slides |
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| Fri | Mar 1110 | Lecture 25: Linearizability of Concurrent Objects Dining Philosophers Problem | Module 2: 7.46 | Topic 7.4 6 Lecture | worksheet25 | lec25-slides |
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Mon | Mar 1413 | No class: Spring Break |
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| Wed | Mar 1615 | No class: Spring Break |
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| Fri | Mar 1817 | No class: Spring Break |
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10 | Mon | Mar 2120 | Lecture 26: Java Locks - Soundness and progress guarantees | Module 2: 7.5 | N-Body problem, applications and implementations | Topic 7.5 Lecture | worksheet26 | lec26-slides | WS26-solution | ||||||||||||||
| Wed | Mar 2322 | Lecture 27: Dining Philosophers Problem Read-Write Locks, Linearizability of Concurrent Objects | Module 2: 7.63, 7.4 | Topic 7.4 3 Lecture, Topic 7.6 4 Lecture | worksheet27 | lec27-slides |
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| Fri | Mar 2524 | Lecture 28: Read-Write Pattern. Read-Write Locks. Fairness & starvation Message-Passing programming model with Actors | Module 2: 76.31, 76.52 | Topic 76.3 Lecture, Topic 7.5 Lecture, 1 Lecture, Topic 6.1 Demonstration, Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet28 | lec28-slides |
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11 | Mon | Mar 2827 | Lecture 29: Task Affinity and locality. Memory hierarchy | Active Object Pattern. Combining Actors with task parallelism | Module 2: 6.3, 6.4 | Topic 6.3 Lecture, Topic 6.3 Demonstration, Topic 6.4 Lecture, Topic 6.4 Demonstration | worksheet29 | lec29-slides |
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| Wed | Mar 3029 | Lecture 30: Reactor Pattern. Web servers | worksheet30 | lec30-slides |
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| Fri | Apr 01 | Lecture 31: Scan Pattern. Parallel Prefix Sum, uses and algorithmsTask Affinity and locality. Memory hierarchy | worksheet31worksheet30 | lec31lec30-slides | Homework 5
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| 12 | Mon | Fri | Mar 31Apr 04 | Lecture 3231: 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 | worksheet32worksheet31 | lec32lec31-slides | Homework 5 |
| Homework 4 | WS31-solution | ||||||||||
12 | WedMon | Apr 0603 | Lecture 3332: Barrier Synchronization with phasersPhasers | Module 1: Section 3.4 | Topic 3.4 Lecture Lecture, Topic Topic 3.4 Demonstration | worksheet33worksheet32 | lec33lec32-slides |
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| Wed | Fri | Apr 0805 | Lecture 3433: Stencil computation. Point-to-point Synchronization with Phasers | Module 1: Section 4.2, 4.3 | Topic 4.2 Lecture, Topic 4.2 Demonstration, Topic 4.3 Lecture, Topic 4.3 Demonstration | worksheet33 | lec33-slides |
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| Fri | Apr 07 | Lecture 34: Fuzzy Barriers with Phasers | Module 1: Section 4.1 | Topic 4.1 Lecture, Topic 4.1 Demonstration | worksheet34 | lec34-slides |
| WS34-solution | ||||||||||||||
13 | Mon | Apr 1110 | Lecture 35: Message-Passing programming model with Actors | Module 2: 6.1, 6.2 | Eureka-style Speculative Task Parallelism | Topic 6.1 Lecture , Topic 6.1 Demonstration , Topic 6.2 Lecture, Topic 6.2 Demonstration | worksheet35 | lec35-slides |
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| Wed | Apr 1312 | Lecture 36: Active Object Pattern. Combining Actors with task parallelism | Module 2: 6.3, 6.4 | 36: Scan Pattern. Parallel Prefix Sum | Topic 6.3 Lecture , Topic 6.3 Demonstration , Topic 6.4 Lecture, Topic 6.4 Demonstration | worksheet36 | lec36-slides | WS36-solution | |||||||||||||||
| Fri | Apr 1514 | Lecture 37: Eureka-style Speculative Task Parallelism Parallel Prefix Sum applications | worksheet37 | lec37-slides | |||||||||||||||||||
| 14 | Mon | Apr 1817 | Lecture 38: Overview of other models and frameworks | lec38-slides | |||||||||||||||||||
| Wed | Apr 2019 | Lecture 39: Course Review (Lectures 19-38) | lec39-slides | ||||||||||||||||||||
| Fri | Apr 2221 | Lecture 40: Course Review (Lectures 19-38) | lec40-slides | Homework 5 |
Lab Schedule
Lab # | Date (2022) | Topic | Handouts | Examples | |
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1 | Jan 10 | Infrastructure setup | lab0-handout lab1-handout | ||
| -2 | Jan 17 | Functional Programming | lab2-handout | ||
-3 | Jan 24 | Java Streams | lab3-handout | ||
| -4 | Jan 31 | Futures | lab4-handout | ||
-5 | Feb 07 |
| Data-Driven Tasks | lab5-handout | |
| -6 | Feb 14 |
| Async / Finish | lab6-handout | |
| - | Feb 21 | No lab this week (Midterm) | |||
| -7 | Feb 28 | Recursive Task Cutoff Strategy | lab7-handout | ||
| -8 | Mar 07 | Java Threads | lab8-handout | ||
- | Mar 14 | No lab this week (Spring Break) | |||
| -9 | Mar 21 | Concurrent Lists | lab9-handout | ||
| -10 | Mar 28 | Actors | lab10-handout | ||
| -11 | Apr 04 |
| Loop Parallelism | lab11-handout | |
- | Apr 11 | No lab this week | |||
- | Apr 18 | No lab this week |
Grading, Honor Code Policy, Processes and Procedures
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Labs must be submitted by the following Monday Wednesday at 114:59pm30pm. 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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