COMP 322: Fundamentals of Parallel Programming (Spring
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2023)
Instructor: | Prof. Vivek SarkarMackale Joyner, DH 31312063 | Head TATAs: | Max Grossman |
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Admin Assistant: | Annepha Hurlock, annepha@rice.edu, DH 3080, 713-348-5186 | Graduate TAs: | Jonathan Sharman, Ryan Spring, Bing Xue, Lechen Yu |
Co-Instructor: | Dr. Mackale Joyner | Undergraduate TAs: | Marc Canby, Anna Chi, Peter Elmers, Joseph Hungate, Cary Jiang, Gloria Kim, Cecilia Liu, Kevin Mullin, Victoria Nazari, Ashok Sankaran, Sujay Tadwalkar, Vidhi Vakharia, Eugene WangMohamed 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/classrice/ixdqx0x3bjl6enspring2022/comp322 (Piazza is the preferred medium for all course communications, but you can also send email to comp322-staff at rice dot edu if needed) | Cross-listing: | ELEC 323 |
Lecture location: | Herzstein Hall 210TBD | Lecture times: | MWF 1:00pm - 1:50pm (followed by group office hours during 2pm - 3pm, usually in DH 3092) |
Lab locations: | DH 1042, DH 1064TBD | Lab times: | Wednesday, 07Mon 3:00pm - 083:30pm |
Course Syllabus
50pm () Tue 4:00pm - 4:50pm () |
Course Syllabus
A summary 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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The prerequisite course requirements are COMP 182 and COMP 215. COMP 322 should be accessible to anyone familiar with the foundations of sequential algorithms and data structures, and with basic Java programming. COMP 321 is also recommended as a co-requisite.
Textbooks and Other Resources
There are no required textbooks for the class. Instead, lecture handouts are provided for each module as follows. The links You are expected to the latest versions on Owlspace are included below:
- Module 1 handout (Parallelism)
- Module 2 handout (Concurrency)
- Module 3 handout (Distribution and Locality)
You are expected to read the relevant sections 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 are also a few optional textbooks that we will draw from quite heavilyduring 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
Past Offerings of COMP 322
- Spring 2016 (Rice University)
- Spring 2015 (Rice University)
- Spring 2014 (Rice University)
- Spring 2013 (Rice University)
- Fall 2012 (Harvey Mudd College CS 181E, half-semester class, co-instructor: Prof. Ran Libeskind-Hadas)
- Spring 2012 (Rice University)
- Spring 2011 (Rice University)
- Fall 2009 (Rice University)
Lecture Schedule
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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 09 | Lecture 1: Introduction |
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| Wed | Jan 11 | Lecture 2: Functional Programming | GList.java | worksheet2 | lec02-slides |
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Week | Day | Date (2016) | Topic | Assigned Reading | Assigned Videos (Quizzes due by Friday of each week) | In-class Worksheets | Slides | Work Assigned | Work Due | |||||||||||||
1 | Mon | Jan 09 | Lecture 1: Task Creation and Termination (Async, Finish) | Module 1: Section 1.1 | Topic 1.1 Lecture, Topic 1.1 Demonstrationworksheet1 | lec1-slides |
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| Wed | Jan 11 | Lecture 2: 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 | worksheet2 | lec2-slides | ||||||
Fri | Jan 13 | Lecture 3: Abstract Performance Metrics, Multiprocessor Scheduling | Module 1: Section 1.4 | Topic 1.4 Lecture, Topic 1.4 Demonstration | worksheet3 | lec3-slides | Homework 1 (2 weeks) | Lecture & demo quizzes for topics 1.1, 1.2, 1.3, 1.4 | Higher order functions | worksheet3 | lec3-slides |
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2 | Mon | Jan 16 | No class: MLK | 2 | Mon | Jan 16 | No lecture, School Holiday (Martin Luther King, Jr. Day) | |||||||||||||||
| Wed | Jan 18 | Lecture 4: Parallel Speedup and Amdahl's Law | Module 1: Section 1.5 | Lazy Computation | LazyList.java Lazy.java | Topic 1.5 Lecture, Topic 1.5 Demonstration | worksheet4 | lec4-slides | WS4-solution | ||||||||||||
| Fri | Jan 20 | Lecture 5: | Future Tasks, Functional ParallelismModule 1: Section 2.1 | Topic 2.1 Lecture , Topic 2.1 DemonstrationJava Streams | worksheet5 | lec5-slides | Homework 1 | Lecture & demo quizzes for topics 1.5, 2.1 (topic 1.6 is optional) | WS5-solution | ||||||||||||
3 | Mon | Jan 23 | Lecture 6: Memoization Map Reduce with Java Streams | Module 1: Section 2.24 | Topic 2.2 4 Lecture , Topic 2.2 4 Demonstration | worksheet6 | lec6-slides |
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| Wed | Jan 25 | Lecture 7: | Finish AccumulatorsFutures | Module 1: Section 2.31 | Topic 2. | 31 Lecture | , | Topic 2. | 31 Demonstration | worksheet7 | lec7-slides |
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| Fri | Jan 27 | Lecture 8: Data Races, Functional & Structural Determinism Computation Graphs, Ideal Parallelism | Module 1: Sections 1.2.5, 21.63 | Topic 1.2 .5 Lecture , Topic 1.2 .5 Demonstration, Topic 21.6 3 Lecture , Topic 21.6 3 Demonstration | worksheet8 | lec8-slides | (2 weeks) | WS8-solution | Homework 1, Lecture & demo quizzes for topics 2.2, 2.3, 2.5, 2.6 | ||||||||||||
4 | Mon
| Jan 30 | Lecture 9: Map ReduceAsync, Finish, Data-Driven Tasks | Module 1: Section 21.1, 4.5
| Topic 2.4 Lecture , Topic 2.4 Demonstration1.1 Lecture, Topic 1.1 Demonstration, Topic 4.5 Lecture, Topic 4.5 Demonstration | worksheet9 | lec9-slidesslides | WS9-solution | ||||||||||||||
Wed | Feb 01 | Lecture 10: | Java’s Fork/Join Library Event-based programming model FJP chapter: Sections 7.3 & 7.5 | worksheet10 | lec10-slides | Homework 1 | WS10-solution | ArraySumFourWay.java|||||||||||||||
Fri | Feb 03 | Lecture 11: | Loop-Level Parallelism, Parallel Matrix Multiplication, Iteration Grouping (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 | worksheet11 | lec11-slides | Lecture & demo quizzes for topics 2.4, 3.1, 3.2, 3.3 | |||||||||||||||
5 | Mon | Feb 06 | Lecture 12: Barrier Synchronization | Module 1: Section 3.4 | Topic 3.4 Lecture , Topic 3.4 Demonstration | worksheet12 | lec12-slides | |||||||||||||||
| Wed | Feb 08 | Lecture 13: Iterative Averaging Revisited, SPMD pattern | Module 1: Sections 3.5, 3.6 | Topic 3.5 Lecture , Topic 3.5 Demonstration , Topic 3.6 Lecture, Topic 3.6 Demonstration | worksheet13 | lec13-slides | Worksheet12.java | ||||||||||||||
- | Fri | Feb 10 | Spring Recess | |||||||||||||||||||
6 | Mon | Feb 13 | Lecture 14: Data-Driven Tasks and Data-Driven Futures | Module 1: Section 4.5 | Topic 4.5 Lecture , Topic 4.5 Demonstration | worksheet14 | lec14-slides | (5 weeks, with two intermediate checkpoints) | Homework 2, Lecture & demo quizzes for topics | |||||||||||||
| Wed | Feb 15 | Lecture 15: Phasers, Point-to-point Synchronization | Module 1: Sections 4.2, 4.3 | Topic 4.2 Lecture , Topic 4.2 Demonstration, Topic 4.3 Lecture, Topic 4.3 Demonstration | worksheet15 | lec15-slides | |||||||||||||||
| Fri | Feb 17 | Lecture 16: Pipeline Parallelism, Signal Statement, Fuzzy Barriers | Module 1: Sections 4.4, 4.1 | Topic 4.4 Lecture , Topic 4.4 Demonstration, Topic 4.1 Lecture, Topic 4.1 Demonstration, | worksheet16 | lec16-slides | Lecture & demo quizzes for topics 4.1, 4.2, 4.3, 4.4 | ||||||||||||||
7 | Mon | Feb 20 | Lecture 17: Midterm Summary | lec18-slides | ||||||||||||||||||
| Wed | Feb 22 | Midterm Review (interactive Q&A only, no lecture) | Exam 1 held during lab time (7:00pm - 10:00pm), scope of exam limited to lectures 1-17 | ||||||||||||||||||
| Fri | Feb 24 | Lecture 18: Abstract vs. Real Performance | worksheet17 | lec17-slides | Homework 3 Checkpoint-1, Lecture & demo quizzes for topic 4.6 | ||||||||||||||||
8 | Mon | Feb 27 | Lecture 19: Task Scheduling Policies | Topic 4.6 Lecture , Topic 4.6 Demonstration | worksheet19 | lec19-slides | Lec19HelpFirstWorkStealing.java |
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| Wed | Mar 01 | Lecture 20: Critical sections, Isolated construct, Parallel Spanning Tree algorithm (start of Module 2) | Module 2: Sections 5.1, 5.2, 5.3, 5.6 | Topic 5.1 Lecture, Topic 5.1 Demonstration, Topic 5.2 Lecture, Topic 5.2 Demonstration, Topic 5.3 Lecture, Topic 5.3 Demonstration | worksheet20 | lec20-slides |
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| Fri | Mar 03 | Lecture 21: Atomic variables, Read-Write Isolation | Module 2: Sections 5.4, 5.5 | Topic 5.4 Lecture, Topic 5.4 Demonstration, Topic 5.5 Lecture, Topic 5.5 Demonstration, Topic 5.6 Lecture, Topic 5.6 Demonstration | worksheet21 | lec21-slides | Homework 3 Checkpoint-2, Lecture & demo quizzes for topics 5.1 to 5.6 | ||||||||||||||
GUI programming as an example of event-based, futures/callbacks in GUI programming | worksheet11 | lec11-slides | Homework 2 | WS11-solution | ||||||||||||||||||
5 | Mon | Feb 06 | 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 08 | Lecture 13: Parallel Speedup, Critical Path, Amdahl's Law | Module 1: Section 1.5 | Topic 1.5 Lecture , Topic 1.5 Demonstration | worksheet13 | lec13-slides | WS13-solution | ||||||||||||||
| Fri | Feb 10 | No class: Spring Recess
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6 | Mon | Feb 13 | Lecture 14: Accumulation and reduction. Finish accumulators | Module 1: Section 2.3 | Topic 2.3 Lecture Topic 2.3 Demonstration | worksheet14 | lec14-slides | WS14-solution | ||||||||||||||
| Wed | Feb 15 | Lecture 15: Recursive Task Parallelism | worksheet15 | lec15-slides |
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Fri | Feb 17 | Lecture 16: 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 | worksheet16 | lec16-slides | Homework 3 | Homework 2 | WS16-solution | |||||||||||||
7 | Mon | Feb 20 | Lecture 17: Midterm Review | lec17-slides | ||||||||||||||||||
| Wed | Feb 22 | Lecture 18: Limitations of Functional parallelism. | worksheet18 | lec18-slides | WS18-solution | ||||||||||||||||
| Fri | Feb 24 | 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 27 | 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 | lec20-slides | WS20-solution | ||||||||||||||
| Wed | Mar 01 | Lecture 21: 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 03 | Lecture 22: Parallel Spanning Tree, other graph algorithms | worksheet22 | lec22-slides | Homework 4 | Homework 3 | WS22-solution | ||||||||||||||
9 | Mon | Mar 06 | Lecture 23: 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 08 | Lecture 24: Java Locks - Soundness and progress guarantees | Module 2: 7.5 | Topic 7.5 Lecture | worksheet24 | lec24-slides |
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| Fri | Mar 10 | Lecture 25: Dining Philosophers Problem | Module 2: 7.6 | Topic 7.6 Lecture | worksheet25 | lec25-slides |
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Mon | Mar 13 | No class: Spring Break |
| 9 | Mon | Mar 06 | Lecture 22: Parallelism in Java Streams, Parallel Prefix Sums
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Wed | Mar | 0815 | Lecture 23: Java Threads, Java synchronized statement | Topic 7.1 Lecture, Topic 7.2 Lecture | worksheet23 | No class: Spring Break |
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| Fri | Mar 1017 | Lecture 24: Java synchronized statement (contd), wait/notify | Topic 7.3 Lecture | worksheet24 | lec24-slides |
| Homework 3, Lecture quizzes for topics 7.1 - 7.4 | No class: Spring Break | - | M-F | Mar 13 - Mar 17 | Spring Break |
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10 | Mon | Mar 20 | Lecture 25: Concurrent Objects, Linearizability of Concurrent Objects26: N-Body problem, applications and implementations | Topic 7.4 Lecture | worksheet25 | worksheet26 | lec26lec25-slides | WS26-solution(3 weeks, with one intermediate checkpoint) | ||||||||||||||
| Wed | Mar 22 | Lecture 2627: Linearizability (contd), Java locks Read-Write Locks, Linearizability of Concurrent Objects | Module 2: 7.3, 7.4 | Topic 7.3 Lecture (recap), Topic 7.4 Lecture (recap) | worksheet26 worksheet27 | lec26lec27-slides |
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| Fri | Mar 24 | WS27-solution | Lecture 27: Parallel Design Patterns, Safety and Liveness Properties | |||||||||
| Topic 7.5 Lecture | worksheet27 | lec27-slides | Lecture & demo quizzes for topics 7.5 | 11 | Mon | Mar 27Fri | Mar 24 | Lecture 28: Message-Passing programming model with Actors | Module 2: 6.1, 6.2 | Topic 6.1 Lecture, | Topic 6.1 Demonstration, Topic 6.2 Lecture, Topic 6.2 Demonstration | , Topic 6.3 Lecture, Topic 6.3 Demonstrationworksheet28 | lec28-slides |
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11 | Mon | Wed | Mar 2927 | Lecture 29: Actors (contd) | Active Object Pattern. Combining Actors with task parallelism | Module 2: 6.3, 6.4 | Topic 6.3 Topic 6.4 Lecture , Topic 6.4 Demonstration , Topic 6.5 Lecture, Topic 6.5 3 Demonstration, Topic 6.6 4 Lecture, Topic 6.6 4 Demonstration | worksheet29 | lec29-slides |
| Lec29Slide2ThreadRing.java |
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| FriWed | Mar | 3129 | Lecture 30: | Java Synchronizers, Dining Philosophers ProblemTask Affinity and locality. Memory hierarchy | Topic 7.6 Lecture | worksheet30 | lec30-slides |
| Lecture quiz for topic 7.6 | WS30-solution | |||||||||||
| Fri | Mar 31 | 12 | Mon | Apr 03 | Lecture 31: Eureka-style Speculative Task Parallelism | 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 | worksheet31 | lec31-slides | Homework 5 | Homework 4 Checkpoint | WS31-1solution | ||||||||
12 | MonWed | Apr 0503 | Lecture 32: Task Affinity with Places (start of Module 3) | Barrier Synchronization with Phasers | Module 1: Section 3.4 | Topic 3.4 Lecture, Topic 3.4 Demonstration | worksheet32 | lec32-slides |
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| WedFri | Apr 0705 | Lecture 33: Message Passing Interface (MPI) | 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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| FriMon | Apr 0907 | Lecture 34: Message Passing Interface (MPI, contd) | Fuzzy Barriers with Phasers | Module 1: Section 4.1 | Topic 4.1 Lecture, Topic 4.1 Demonstration | worksheet34 | lec34-slides | Homework 4 | WS34-solution | ||||||||||||
13 | WedMon | Apr 1210 | Lecture 35: GPU Computing Eureka-style Speculative Task Parallelism |
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Fri | Wed | Apr | 1412 | Lecture 36: | Partitioned Global Address Space (PGAS) programming modelsScan Pattern. Parallel Prefix Sum |
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Mon | Fri | Apr | 1714 | Lecture 37: | Apache Spark frameworkParallel Prefix Sum applications | worksheet37 | lec37-slides | |||||||||||||||
14 | Mon | WedApr | 1917 | Lecture 38: | Topic TBDOverview of other models and frameworks | lec38-slides | ||||||||||||||||
Fri | Wed | Apr | 2119 | Lecture 39: Course Review ( | lectures 20Lectures 19- | 3738) | , Last day of classeslec38lec39-slides | Homework 5 (automatic extension till May 1st after which slip days may be used) | ||||||||||||||
Fri | Apr 21 | Lecture 40: Course Review (Lectures 19-38 | - | Mon | Apr 24 | Review session / Office Hours, 1pm - 3pm, Herzstein 212 (different room from usual) | lec40-slides | Homework 5 | - |
Lab Schedule
Lab # | Date (2023) | Topic | Handouts | Examples | ||||||||||||||
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1 | Jan 09 | Infrastructure setup | lab0-handout lab1-handout | |||||||||||||||
- | Jan 16 | No lab this week (MLK) | Wed | Apr 26 | Review session / Office Hours, 1pm - 3pm, Herzstein 212 (different room from usual) | - | Thu | Apr 28 | Review session / Office Hours, 1pm - 3pm, Herzstein 212 (different room from usual) | |||||||||
2 | Jan 23 | Functional Programming | lab2-handout | Tue|||||||||||||||
3 | Jan 30 | Java Streams | Scheduled final exam (Exam 2 – scope of exam limited to lectures 18-37), location and time TBD by registrarlab3-handout | |||||||||||||||
4 | Feb 06 | Futures | lab4-handout |
Lab Schedule
Lab # | Date (2015) | Topic | Handouts | Code Examples |
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0 | Infrastructure Setup | lab0-handout | - | |
1 | Jan 13 | Async-Finish Parallel Programming | lab1-handout, lab1-slides | lab_1.zip |
2 | Jan 20 | Abstract performance metrics with async & finish | lab2-handout, lab2-slides | lab_2.zip |
3 | Jan 27 | DIY HJ-lib Programming, Futures, HJ-Viz | lab3-handout, lab3-slides | lab_3.zip |
4 | Feb 03 | Finish Accumulators and Loop-Level Parallelism | lab4-handout and lab4-slides | lab_4.zip |
5 | Feb 10 | Loop Chunking and Barrier Synchronization | lab5-handout and lab5-slides | lab_5.zip |
6 | Feb 17 | Data-Driven Futures and Phasers | lab6-handout | lab_6.zip |
- | Feb 24 | No lab this week — Exam 1 | - | - |
- | Mar 02 | No lab this week — Spring Break | - | - |
7 | Mar 09 | Isolated Statement and Atomic Variables | lab7-handout | |
8 | Mar 16 | Java Threads | lab8-handout | |
9 | Mar 23 | Java Locks | lab9-handout | |
10 | Mar 30 | Actors and Selectors | lab10-handout | |
11 | Apr 06 | Eureka-style Speculative Task Parallelism | lab11-handout | |
12 | Apr 13 | Message Passing Interface (MPI) | lab12-handout | |
13 | Apr 20 | Apache Spark | lab13-handout |
Grading, Honor Code Policy, Processes and Procedures
Grading will be based on your performance on five homeworks (weighted 40% in all), two exams (weighted 40% in all), weekly lab exercises (weighted 10% in all), and class participation including worksheets, in-class Q&A, Piazza participation, and online quizzes (weighted 10% in all).
The purpose of the homeworks is to train you to solve problems and to help deepen your understanding of concepts introduced in class. Homeworks are due on the dates and times specified in the course schedule. Please turn in all your homeworks using the subversion system set up for the class. Homework is worth full credit when turned in on time. No late submissions (other than those using slip days mentioned below) will be accepted.
As in COMP 321, all students will be given 3 slip days to use throughout the semester. When you use a slip day, you will receive up to 24 additional hours to complete the assignment. You may use these slip days in any way you see fit (3 days on one assignment, 1 day each on 3 assignments, etc.). If you use slip days, you must submit a SLIPDAY.txt file in your SVN homework folder before the actual submission deadline indicating the number of slip days that you plan to use. Other than slip days, no extensions will be given unless there are exceptional circumstances (such as severe sickness, not because you have too much other work). Such extensions must be requested and approved by the instructor (via e-mail, phone, or in person) before the due date for the assignment. Last minute requests are likely to be denied. If you do receive an extension from the instructor, please indicate this by placing an EXTENSION.txt file in your SVN homework folder before the actual submission deadline indicating the date that the extension was granted by the instructor as well as the length of the extension.
Labs must be checked off by a TA prior to the start of the lab the following week.
Worksheets are due by the beginning of the class after they are distributed, so that solutions to the worksheets can be discussed.
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5 | Feb 13 | Data-Driven Tasks | lab5-handout | |
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- | Feb 20 | No lab this week (Midterm) | ||
6 | Feb 27 | Async / Finish | lab6-handout | |
7 | Mar 06 | Recursive Task Cutoff Strategy | lab7-handout | |
- | Mar 13 | No lab this week (Spring Break) | ||
8 | Mar 20 | Java Threads | lab8-handout | |
9 | Mar 27 | Concurrent Lists | lab9-handout | |
10 | Apr 03 | Actors | lab10-handout | |
11 | Apr 10 | Loop Parallelism | lab11-handout | |
- | Apr 17 | No lab this week |
Grading, Honor Code Policy, Processes and Procedures
Grading will be based on your performance on four homework assignments (weighted 40% in all), two exams (weighted 40% in all), lab exercises (weighted 10% in all), online quizzes (weighted 5% in all), and in-class worksheets (weighted 5% in all).
The purpose of the homework is to give you practice in solving problems that deepen your understanding of concepts introduced in class. Homework is due on the dates and times specified in the course schedule. No late submissions (other than those using slip days mentioned below) will be accepted.
The slip day policy for COMP 322 is similar to that of COMP 321. All students will be given 3 slip days to use throughout the semester. When you use a slip day, you will receive up to 24 additional hours to complete the assignment. You may use these slip days in any way you see fit (3 days on one assignment, 1 day each on 3 assignments, etc.). Slip days will be tracked using the README.md file. Other than slip days, no extensions will be given unless there are exceptional circumstances (such as severe sickness, not because you have too much other work). Such extensions must be requested and approved by the instructor (via e-mail, phone, or in person) before the due date for the assignment. Last minute requests are likely to be denied.
Labs must be submitted by the following Wednesday at 4:30pm. Labs must be checked off by a TA.
Worksheets should be completed by the deadline listed in Canvas so that solutions to the worksheets can be discussed in the next class.
You will be expected to follow the Honor Code in all homework and exams. The following policies will apply to different work products in the course:
- In-class worksheets: You are free to discuss all aspects of in-class worksheets with your other classmates, the teaching assistants and the professor during the class. You can work in a group and write down the solution that you obtained as a group. If you work on the worksheet outside of class (e.g., due to an absence), then it must be entirely your individual effort, without discussion with any other students. If you use any material from external sources, you must provide proper attribution.
- Weekly lab assignments: You are free to discuss all aspects of lab assignments with your other classmates, the teaching assistants and the professor during the lab. However, all code and reports that you submit are expected to be the result of your individual effort. If you work on the lab outside of class (e.g., due to an absence), then it must be entirely your individual effort, without discussion with any other students. If you use any material from external sources, you must provide proper attribution (as shown here).
- Homework: All submitted homework is expected to be the result of your individual effort. You are free to discuss course material and approaches to
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- problems with your other classmates, the teaching assistants and the professor, but you should never misrepresent someone else’s work as your own. If you use any material from external sources, you must provide proper attribution.
- Quizzes: Each online quiz will be an open-notes individual test. The student may consult their course materials and notes when taking the quizzes, but may not consult any other external sources.
- Exams: Each exam will be a open-book, open-notes, and open-computer individual test, which must be completed within a specified time limit. No external materials may be consulted when taking the exams.
For grade disputes, please send an email to the course instructors within 7 days of receiving your grade. The email subject should include COMP 322 and the assignment. Please provide enough information in the email so that the instructor does not need to perform a checkout of your code (as shown here). Exams 1 and 2 test your individual understanding and knowledge of the material. Exams are closed-book, and collaboration on exams is strictly forbidden. Finally, it is also your responsibility to protect your homeworks and exams from unauthorized access. Graded homeworks will be returned to you via email, and exams as marked-up hardcopies. If you believe we have made an error in grading your homework or exam, please bring the matter to our attention within one week.
Accommodations for Students with Special Needs
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