This course teaches learners (industry professionals and students) the fundamental concepts of concurrent programming in the context of Java 8. Concurrent programming enables developers to efficiently and correctly mediate the use of shared resources in parallel programs. By the end of this course, you will learn how to use basic concurrency constructs in Java such as threads, locks, critical sections, atomic variables, isolation, actors, optimistic concurrency and concurrent collections, as well as their theoretical foundations (e.g., progress guarantees, deadlock, livelock, starvation, linearizability).
This course is part of the Parallel, Concurrent, and Distributed Programming in Java Specialization
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About this Course
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Learner Career Outcomes
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Intermediate Level
Approx. 19 hours to complete
English
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
Skills you will gain
Concurrency (Computer Science)Actor ModelOptimistic Concurrency ControlJava Concurrency
Learner Career Outcomes
11%
started a new career after completing these courses
14%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 3 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 19 hours to complete
English
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
Offered by
Rice University
Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy.
Syllabus - What you will learn from this course
1 hour to complete
Welcome to the Course!
Welcome to Concurrent Programming in Java! This course is designed as a three-part series and covers a theme or body of knowledge through various video lectures, demonstrations, and coding projects.
1 hour to complete
1 video (Total 1 min), 5 readings, 1 quiz
1 video
5 readings
General Course Info5m
Course Icon Legend2m
Discussion Forum Guidelines2m
Pre-Course Survey10m
Mini Project 0: Setup10m
5 hours to complete
Threads and Locks
In this module, we will learn about threads and locks, which have served as primitive building blocks for concurrent programming for over five decades. All computing platforms today include some form of support for threads and locks, and make them available for use by developers in a wide range of programming languages. We will learn how threads can be created, joined, and synchronized using structured (e.g., synchronized statements/methods) and unstructured (e.g., java.util.concurrent libraries) locks in Java. We will also learn about new classes of bugs that can arise when concurrent programs need to access shared resources. These bugs are referred to as violations of liveness/progress guarantees, and include deadlock, livelock, and starvation. We will conclude this module by studying different solutions to the classical "Dining Philosophers" problem, and use these solutions to illustrate instances of deadlock, livelock and starvation.
5 hours to complete
6 videos (Total 41 min), 6 readings, 2 quizzes
6 videos
1.2 Structured Locks7m
1.3 Unstructured Locks7m
1.4 Liveness7m
1.5 Dining Philosophers8m
Demonstration: Locking and Synchronization4m
6 readings
1.1 Lecture Summary5m
1.2 Lecture Summary5m
1.3 Lecture Summary5m
1.4 Lecture Summary5m
1.5 Lecture Summary5m
Mini Project 1: Locking and Synchronization10m
1 practice exercise
Module 1 Quiz30m
4 hours to complete
Critical Sections and Isolation
In this module, we will learn different approaches to coordinating accesses to shared resources without encountering the deadlock or livelock bugs studied earlier. Critical/isolated sections are higher-level concurrent programming constructs (relative to locks) that simplify the implementation of mutual exclusion by guaranteeing the absence of deadlocks and livelocks. Object-based isolation relaxes the constraints imposed by critical sections by allowing mutual exclusion to be specified on a per-object basis, as illustrated in the Spanning Tree example. Java's atomic variables represent an important, but restricted, case of object-based isolation that is implemented efficiently on all hardware platforms. Finally, we will learn how object-based isolation can be further relaxed with read/write access modes.
4 hours to complete
6 videos (Total 36 min), 6 readings, 2 quizzes
6 videos
2.2 Object Based Isolation (Monitors)7m
2.3 Concurrent Spanning Tree Algorithm6m
2.4 Atomic Variables6m
2.5 Read, Write Isolation5m
Demonstration: Global and Object-Based Isolation3m
6 readings
2.1 Lecture Summary10m
2.2 Lecture Summary10m
2.3 Lecture Summary10m
2.4 Lecture Summary10m
2.5 Lecture Summary10m
Mini Project 2: Global and Object-Based Isolation10m
1 practice exercise
Module 2 Quiz33m
20 minutes to complete
Talking to Two Sigma: Using it in the Field
Join Professor Vivek Sarkar as he talks with Software Engineer, Dr. Shams Imam, at their downtown Houston, Texas office about threads, locks, deadlocks, high-level and low-level constructs, and the importance of concurrent programming.
20 minutes to complete
2 videos (Total 10 min), 1 reading
2 videos
Industry Professional on Concurrency - Dr. Shams Imam, Software Engineer3m
1 reading
About these Talks10m
4 hours to complete
Actors
In this module, we will learn another high-level approach to concurrent programming called the "Actor" model. A major difference between the Actor model and the Isolated Sections model is that there are no data races possible in the Actor model because it does not allow for any form of shared variables. However, as in all concurrent programming models, higher-level forms of nondeterminism are still possible in the Actor model due to an inherent asynchrony in the order in which messages may be delivered. We will study multiple examples of concurrency using the Actor model, including the classical Sieve of Eratosthenes algorithm to generate prime numbers, as well as producer-consumer patterns with both unbounded and bounded buffers.
4 hours to complete
6 videos (Total 29 min), 6 readings, 2 quizzes
6 videos
3.2 Actor Examples6m
3.3 Sieve of Eratosthenes Algorithm5m
3.4 Producer-Consumer Problem4m
3.5 Bounded Buffer Problem3m
Demonstration: Sieve of Eratosthenes Using Actor Parallelism3m
6 readings
3.1 Lecture Summary10m
3.2 Lecture Summary10m
3.3 Lecture Summary10m
3.4 Lecture Summary10m
3.5 Lecture Summary10m
Mini Project 3: Sieve of Eratosthenes Using Actor Parallelism10m
1 practice exercise
Module 3 Quiz30m
4 hours to complete
Concurrent Data Structures
In this module, we will study Concurrent Data Structures, which form an essential software layer in all multithreaded programming systems. First, we will learn about Optimistic Concurrency, an important multithreaded pattern in which two threads can "optimistically" make progress on their assigned work without worrying about mutual conflicts, and only checking for conflicts before "committing" the results of their work. We will then study the widely-used Concurrent Queue data structure. Even though the APIs for using concurrent queues are very simple, their implementations using the Optimistic Concurrency model can be complex and error-prone. To that end, we will also learn the formal notion of Linearizability to better understand correctness requirements for concurrent data structures. We will then study Concurrent Hash Maps, another widely-used concurrent data structure. Finally, we discuss a concurrent algorithm for finding a Minimum Spanning Tree of an undirected graph, an algorithm that relies on the use of Concurrent Data Structures under the covers.
4 hours to complete
6 videos (Total 38 min), 7 readings, 2 quizzes
6 videos
4.2 Concurrent Queue5m
4.3 Linearizability6m
4.4 Concurrent Hash Map5m
4.5 Concurrent Minimum Spanning Tree Algorithm7m
Demonstration: Parallelization of Boruvka's Minimum Spanning Tree Algorithm7m
7 readings
4.1 Lecture Summary10m
4.2 Lecture Summary10m
4.3 Lecture Summary10m
4.4 Lecture Summary10m
4.5 Lecture Summary10m
Mini Project 4: Parallelization of Boruvka's Minimum Spanning Tree Algorithm10m
Exit Survey10m
1 practice exercise
Module 4 Quiz30m
15 minutes to complete
Continue Your Journey with the Specialization "Parallel, Concurrent, and Distributed Programming in Java"
The next two videos will showcase the importance of learning about Parallel Programming and Distributed Programming in Java. Professor Vivek Sarkar will speak with industry professionals at Two Sigma about how the topics of our other two courses are utilized in the field.
15 minutes to complete
2 videos (Total 13 min), 1 reading
2 videos
Industry Professional on Distribution - Dr. Eric Allen, Senior Vice President, Two Sigma6m
1 reading
Our Other Course Offerings2m
Reviews
TOP REVIEWS FROM CONCURRENT PROGRAMMING IN JAVA
by PSSep 1, 2017
Great course. With minimal effort you can learn about important concepts and see immediate results regarding the actual speedup you can achieve using concurrent programming.
by FCFeb 8, 2020
Excellent way to refresh what I learned some years ago in Operator System. Also I won a small hands-on experience using locks, isolation and high level concurrency in Java.
by PBNov 23, 2020
Amazing course. Especially for those who want to really understand the foundations behind multithreading and concurrency in Java. As always, Professor Sarkar is brilliant!
by SMNov 11, 2017
This was a good course and covered all the topics relevant to the course. I liked the Optimistic Concurrency in week 4 - that was an area I was not exposed to before
About the Parallel, Concurrent, and Distributed Programming in Java Specialization
Parallel, concurrent, and distributed programming underlies software in multiple domains, ranging from biomedical research to financial services. This specialization is intended for anyone with a basic knowledge of sequential programming in Java, who is motivated to learn how to write parallel, concurrent and distributed programs. Through a collection of three courses (which may be taken in any order or separately), you will learn foundational topics in Parallelism, Concurrency, and Distribution. These courses will prepare you for multithreaded and distributed programming for a wide range of computer platforms, from mobile devices to cloud computing servers.
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