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.
Este curso forma parte de Programa especializado: Parallel, Concurrent, and Distributed Programming in Java
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Acerca de este Curso
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Prueba Coursera para negociosHabilidades que obtendrás
- Dataflow
- Parallel Computing
- Java Concurrency
- Data Parallelism
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Prueba Coursera para negociosOfrecido por
Programa - Qué aprenderás en este curso
Welcome to the Course!
Task Parallelism
Functional Parallelism
Talking to Two Sigma: Using it in the Field
Loop Parallelism
Data flow Synchronization and Pipelining
Continue Your Journey with the Specialization "Parallel, Concurrent, and Distributed Programming in Java"
Reseñas
- 5 stars68,90 %
- 4 stars23,02 %
- 3 stars6,52 %
- 2 stars1,11 %
- 1 star0,42 %
Principales reseñas sobre PARALLEL PROGRAMMING IN JAVA
Very useful course about parallel programming theory and practice.
Could be less examples with custom libraries instead of standard java features looking to practical usage at work.
Very well structured and presented course! Very useful material with good relevant examples! Thank you, Prof. Sarkar for this Parallel Programming in Java course!
This is a great course in parallel programming. The videos were very clear, summaries reinforced the video material and the programming projects and quizzes were challenging but not overwhelming.
I have never known these things existed and changed my perspective how to take advantage of multiple processor. I have used numpy in python but now I know how these are fast.
Acerca de Programa especializado: Parallel, Concurrent, and Distributed Programming in Java

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