Parallel Programming in Java from Coursera

This course teaches learners (industry professionals and students) the fundamental concepts of parallel programming in the context of Java 8. Parallel programming enables developers to use multicore computers to make their applications run faster by using multiple processors at the same time. By the end of this course, you will learn how to use popular parallel Java frameworks (such as ForkJoin, Stream, and Phaser) to write parallel programs for a wide range of multicore platforms including servers, desktops, or mobile devices, while also learning about their theoretical foundations including computation graphs, ideal parallelism, parallel speedup, Amdahl's Law, data races, and determinism.

Why take this course?

• All computers are multicore computers, so it is important for you to learn how to extend your knowledge of sequential Java programming to multicore parallelism.

• Java 7 and Java 8 have introduced new frameworks for parallelism (ForkJoin, Stream) that have significantly changed the paradigms for parallel programming since the early days of Java.

• 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.

• During the course, you will have online access to the instructor and the mentors to get individualized answers to your questions posted on forums.

The desired learning outcomes of this course are as follows:

• Theory of parallelism: computation graphs, work, span, ideal parallelism, parallel speedup, Amdahl's Law, data races, and determinism

• Task parallelism using Java’s ForkJoin framework

• Functional parallelism using Java’s Future and Stream frameworks

• Loop-level parallelism with extensions for barriers and iteration grouping (chunking)

• Dataflow parallelism using the Phaser framework and data-driven tasks

Mastery of these concepts will enable you to immediately apply them in the context of multicore Java programs, and will also provide the foundation for mastering other parallel programming systems that you may encounter in the future (e.g., C++11, OpenMP, .Net Task Parallel Library).

What's inside

Syllabus

Welcome to the Course!

Welcome to Parallel 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.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides a theoretical foundation that equips learners to use other parallel programming systems in the future

Covers industry-standard frameworks and techniques for parallel Java programming

Provides hands-on experience through regular mini-projects

Accessible through online forums for individualized support

Taught by Professor Vivek Sarkar, an authority in parallel programming with industry experience

Requires prior programming knowledge but may require additional self-study for those new to parallel programming

Reviews summary

Deep dive into java parallelism

According to learners, this course offers a strong foundation in parallel programming concepts and Java 8 APIs. Many highlight the depth of theoretical topics covered, such as computation graphs, work, span, and Amdahl's Law, finding them crucial for understanding. The hands-on mini-projects are frequently mentioned as a valuable aspect for applying the concepts learned in lectures and gaining practical coding experience. While the course is seen as comprehensive and well-structured, some students note the assignments can be challenging and the pace may be quick, especially for those without significant prior experience in Java or parallel programming. Overall, it's considered a worthwhile introduction to the topic and a solid first step towards the specialization.

Focus on ForkJoin, Stream, Phaser

"Excellent coverage of Java 8's ForkJoin and Stream APIs for parallel programming."

"I learned how to effectively use the ForkJoin and Stream frameworks, which was my primary goal."

"The introduction to the Phaser API was also very clear and helpful."

"The course covers the essential Java APIs needed for parallel programming."

Hands-on coding experience

"The mini-projects were the most helpful part. They solidify the concepts and give real coding practice."

"Assignments were challenging but fair and provided necessary hands-on experience."

"I found the practical assignments essential for grasping the material."

"The coding projects helped me apply the concepts immediately."

Deep dive into core concepts

"The theoretical part, covering computation graphs, work, span, Amdahl's law, was very well explained and crucial for understanding."

"I really appreciate the depth of theory provided. It wasn't just about using APIs, but understanding *why* they work."

"The course provides a strong theoretical backbone for parallel computing."

"I gained a solid theoretical understanding of parallel computing principles."

Assignments and pace can be difficult

"Some assignments were quite difficult and required significant time investment beyond the lectures."

"The pace felt a bit fast, especially when trying to complete the coding assignments."

"Requires a good understanding of Java before starting, otherwise the assignments are very hard."

"I struggled with some of the more complex assignment problems."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Parallel Programming in Java with these activities:

Review algebra

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Algebra is used throughout the course to derive and solve equations.

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Take notes on the concepts and procedures of algebra.
Do 10 практике problems in algebra.
Take a practice quiz in algebra.

Practice writing Java code

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Writing practice code helps prepare for the coding projects in the course.

Browse courses on Java Programming

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Create a Java program that prints "Hello, world!"
Write a Java program that takes two numbers as input and prints their sum.
Write a Java program that takes a number as input and prints its factorial.

Review Java fundamentals

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Refreshing your knowledge of Java fundamentals will help you understand the core concepts of parallel programming more easily.

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Review the basics of Java syntax, data types, and control flow.
Practice writing simple Java programs to reinforce your understanding.

One other activity

Expand to see all activities and additional details

Show all four activities

Explore Java concurrency tutorials

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Following tutorials on Java concurrency will provide you with practical examples and hands-on experience in parallel programming.

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Find online tutorials or courses that cover Java concurrency.
Go through the tutorials and practice the examples provided.
Implement the concepts learned in your own Java programs.

Career center

Learners who complete Parallel Programming in Java will develop knowledge and skills that may be useful to these careers:

Software Developer

A Software Developer is responsible for designing, developing, testing, and deploying software applications. This course can help you build a foundation in parallel programming, a valuable skill for Software Developers who need to create high-performance software applications. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Software Developer

Computer Programmer

Computer Programmers write and maintain code for a variety of software applications. This course can help you develop the skills you need to write parallel code, which can improve the performance of your applications. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Computer Programmer

Computer Scientist

Computer Scientists conduct research in various areas of computing, including parallel programming. This course can help you build a foundation in parallel programming, which can be beneficial for Computer Scientists who want to conduct research in this area. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Computer Scientist

Data Scientist

Data Scientists use data to solve problems and make predictions. This course can help you develop the skills you need to use parallel programming to analyze large datasets more efficiently. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Data Scientist

Systems Engineer

Systems Engineers design, develop, and maintain computer systems. This course can help you build a foundation in parallel programming, which can be valuable for Systems Engineers who need to design and develop high-performance computing systems. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Systems Engineer

Software Architect

Software Architects design the architecture of software applications. This course can help you develop the skills you need to design parallel software applications. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for designing efficient parallel software.

See salaries and explore the career path for Software Architect

Software Engineer

Software Engineers design, develop, test, and deploy software applications. This course can help you build a foundation in parallel programming, which can be valuable for Software Engineers who need to create high-performance software applications. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Software Engineer

Web Developer

Web Developers design and develop websites. This course can help you develop the skills you need to create high-performance websites. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

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Mobile Developer

Mobile Developers design and develop mobile applications. This course can help you develop the skills you need to create high-performance mobile applications. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Mobile Developer

Game Developer

Game Developers design and develop video games. This course can help you develop the skills you need to create high-performance video games. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Game Developer

Embedded Systems Engineer

Embedded Systems Engineers design and develop embedded systems. This course can help you build a foundation in parallel programming, which can be valuable for Embedded Systems Engineers who need to design and develop high-performance embedded systems. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Embedded Systems Engineer

Robotics Engineer

Robotics Engineers design and develop robots. This course can help you build a foundation in parallel programming, which can be valuable for Robotics Engineers who need to design and develop high-performance robots. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

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Artificial Intelligence Engineer

Artificial Intelligence Engineers design and develop artificial intelligence systems. This course may be useful for Artificial Intelligence Engineers who want to learn about parallel programming, which can be used to improve the performance of artificial intelligence systems. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

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Machine Learning Engineer

Machine Learning Engineers design and develop machine learning systems. This course may be useful for Machine Learning Engineers who want to learn about parallel programming, which can be used to improve the performance of machine learning systems. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course may be useful for Data Analysts who want to learn about parallel programming, which can be used to analyze large datasets more efficiently. The course covers topics such as task parallelism, functional parallelism, loop parallelism, and data flow synchronization, all of which are essential for writing efficient parallel code.

See salaries and explore the career path for Data Analyst