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). Why take this course? • It is important for you to be aware of the theoretical foundations of concurrency to avoid common but subtle programming errors. • Java 8 has modernized many of the concurrency constructs since the early days of threads and locks. • During the course, you will have online access to the instructor and mentors to get individualized answers to your questions posted on the forums. • Each of the four modules in the course includes an assigned mini-project that will provide you with the necessary hands-on experience to use the concepts learned in the course on your own, after the course ends. The desired learning outcomes of this course are as follows: • Concurrency theory: progress guarantees, deadlock, livelock, starvation, linearizability • Use of threads and structured/unstructured locks in Java • Atomic variables and isolation • Optimistic concurrency and concurrent collections in Java (e.g., concurrent queues, concurrent hashmaps) • Actor model in Java Mastery of these concepts will enable you to immediately apply them in the context of concurrent Java programs, and will also help you master other concurrent programming system that you may encounter in the future (e.g., POSIX threads, .NET threads).
This course is part of the Parallel, Concurrent, and Distributed Programming in Java Specialization
Concurrent Programming in Java
Offered By
- Software Engineers
- Machine Learning Engineers
- Data Engineers
- Data Scientists
- Scientists
Skills you will gain
Syllabus - What you will learn from this course
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.
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.
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.
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.
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.
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.
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.
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Top reviews from Concurrent Programming in Java
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.
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
Instructor
Vivek Sarkar
ProfessorAbout Rice University
About the Parallel, Concurrent, and Distributed Programming in Java Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
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Is financial aid available?
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