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
ofrecido por
Acerca de este Curso
60,330 vistas recientes
Resultados profesionales del estudiante
12%
comenzó una nueva carrera después de completar estos cursos
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 19 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), Ruso (Russian), Inglés (English), Español (Spanish)
Habilidades que obtendrás
DataflowParallel ComputingJava ConcurrencyData Parallelism
Resultados profesionales del estudiante
12%
comenzó una nueva carrera después de completar estos cursos
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 19 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (de Brasil), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad Rice
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.
Programa - Qué aprenderás en este curso
1 hora para completar
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.
1 hora para completar
1 video (Total 1 minutos), 5 lecturas, 1 cuestionario
1 video
5 lecturas
General Course Info5m
Course Icon Legend5m
Discussion Forum Guidelines5m
Pre-Course Survey10m
Mini Project 0: Setup10m
4 horas para completar
Task Parallelism
In this module, we will learn the fundamentals of task parallelism. Tasks are the most basic unit of parallel programming. An increasing number of programming languages (including Java and C++) are moving from older thread-based approaches to more modern task-based approaches for parallel programming. We will learn about task creation, task termination, and the “computation graph” theoretical model for understanding various properties of task-parallel programs. These properties include work, span, ideal parallelism, parallel speedup, and Amdahl’s Law. We will also learn popular Java APIs for task parallelism, most notably the Fork/Join framework.
4 horas para completar
7 videos (Total 42 minutos), 6 lecturas, 2 cuestionarios
7 videos
1.2 Tasks in Java's Fork/Join Framework5m
1.3 Computation Graphs, Work, Span7m
1.4 Multiprocessor Scheduling, Parallel Speedup8m
1.5 Amdahl's Law5m
ReciprocalArraySum using Async-Finish (Demo)4m
ReciprocalArraySum using RecursiveAction's in Java's Fork/Join Framework (Demo)5m
6 lecturas
1.1 Lecture Summary5m
1.2 Lecture Summary5m
1.3 Lecture Summary5m
1.4 Lecture Summary5m
1.5 Lecture Summary5m
Mini Project 1: Reciprocal-Array-Sum using the Java Fork/Join Framework10m
1 ejercicio de práctica
Module 1 Quiz30m
4 horas para completar
Functional Parallelism
Welcome to Module 2! In this module, we will learn about approaches to parallelism that have been inspired by functional programming. Advocates of parallel functional programming have argued for decades that functional parallelism can eliminate many hard-to-detect bugs that can occur with imperative parallelism. We will learn about futures, memoization, and streams, as well as data races, a notorious class of bugs that can be avoided with functional parallelism. We will also learn Java APIs for functional parallelism, including the Fork/Join framework and the Stream API’s.
4 horas para completar
7 videos (Total 40 minutos), 6 lecturas, 2 cuestionarios
7 videos
2.2 Futures in Java's Fork/Join Framework5m
2.3 Memoization6m
2.4 Java Streams5m
2.5 Data Races and Determinism9m
ReciprocalArraySum using RecursiveTask's in Java's Fork/Join Framework (Demo)3m
Parallel List Processing Using Java Streams (Demo)4m
6 lecturas
2.1 Lecture Summary10m
2.2 Lecture Summary10m
2.3 Lecture Summary10m
2.4 Lecture Summary10m
2.5 Lecture Summary10m
Mini Project 2: Analyzing Student Statistics Using Java Parallel Streams10m
1 ejercicio de práctica
Module 2 Quiz30m
23 minutos para completar
Talking to Two Sigma: Using it in the Field
Join Professor Vivek Sarkar as he talks with Two Sigma Managing Director, Jim Ward, and Software Engineers, Margaret Kelley and Jake Kornblau, at their downtown Houston, Texas office about the importance of parallel programming.
23 minutos para completar
2 videos (Total 13 minutos), 1 lectura
2 videos
Industry Professionals on Parallelism - Jake Kornblau and Margaret Kelley, Software Engineers6m
1 lectura
About these Talks10m
4 horas para completar
Loop Parallelism
Welcome to Module 3, and congratulations on reaching the midpoint of this course! It is well known that many applications spend a majority of their execution time in loops, so there is a strong motivation to learn how loops can be sped up through the use of parallelism, which is the focus of this module. We will start by learning how parallel counted-for loops can be conveniently expressed using forall and stream APIs in Java, and how these APIs can be used to parallelize a simple matrix multiplication program. We will also learn about the barrier construct for parallel loops, and illustrate its use with a simple iterative averaging program example. Finally, we will learn the importance of grouping/chunking parallel iterations to reduce overhead.
4 horas para completar
7 videos (Total 41 minutos), 6 lecturas, 2 cuestionarios
7 videos
3.2 Parallel Matrix Multiplication4m
3.3 Barriers in Parallel Loops5m
3.4 Parallel One-Dimensional Iterative Averaging8m
3.5 Iteration Grouping/Chunking in Parallel Loops6m
Parallel Matrix Multiplication (Demo)4m
Parallel One-Dimensional Iterative Averaging (Demo)5m
6 lecturas
3.1 Lecture Summary10m
3.2 Lecture Summary10m
3.3 Lecture Summary10m
3.4 Lecture Summary10m
3.5 Lecture Summary10m
Mini Project 3: Parallelizing Matrix-Matrix Multiply Using Loop Parallelism10m
1 ejercicio de práctica
Module 3 Quiz30m
5 horas para completar
Data flow Synchronization and Pipelining
Welcome to the last module of the course! In this module, we will wrap up our introduction to parallel programming by learning how data flow principles can be used to increase the amount of parallelism in a program. We will learn how Java’s Phaser API can be used to implement “fuzzy” barriers, and also “point-to-point” synchronizations as an optimization of regular barriers by revisiting the iterative averaging example. Finally, we will also learn how pipeline parallelism and data flow models can be expressed using Java APIs.
5 horas para completar
7 videos (Total 38 minutos), 7 lecturas, 2 cuestionarios
7 videos
4.2 Point-to-Point Sychronization with Phasers4m
4.3 One-Dimensional Iterative Averaging with Phasers4m
4.4 Pipeline Parallelism5m
4.5 Data Flow Parallelism5m
Phaser Examples6m
Pipeline & Data Flow Parallelism7m
7 lecturas
4.1 Lecture Summary10m
4.2 Lecture Summary10m
4.3 Lecture Summary10m
4.4 Lecture Summary10m
4.5 Lecture Summary10m
Mini Project 4: Using Phasers to Optimize Data-Parallel Applications10m
Exit Survey10m
1 ejercicio de práctica
Module 4 Quiz30m
20 minutos para completar
Continue Your Journey with the Specialization "Parallel, Concurrent, and Distributed Programming in Java"
The next two videos will showcase the importance of learning about Concurrent 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.
20 minutos para completar
2 videos (Total 10 minutos), 1 lectura
2 videos
Industry Professional on Distribution - Dr. Eric Allen, Senior Vice President, Two Sigma6m
1 lectura
Our Other Course Offerings10m
Reseñas
Principales reseñas sobre PARALLEL PROGRAMMING IN JAVA
por LG12 de dic. de 2017
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.
por JC25 de jun. de 2020
Great introduction to parallel programming. Lectures were clear, summaries were helpful, quizzes were not trivial, discussion forum is good, but the assignments' grading system could be improved.
por SD25 de may. de 2020
I found the explanation of how to precisely code phasors lacking as the Thread stuff was already provided in sample code and never explained. Quite satisfied with the rest of the course though.
por KK18 de jun. de 2018
Excellent Course.I always wanted a good course on java concurrency and parallel programming.And finish->async, isolated, forAsync constructs are awesome.I have learnt much from this course.
Acerca de Programa especializado: Parallel, Concurrent, and Distributed Programming in Java
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
- es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
- Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
¿Recibiré crédito universitario por completar el Curso?
Este Curso no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del curso para obtener crédito. Consulta con tu institución para obtener más información. Los Títulos en línea y los Certificados Mastertrack™ de Coursera brindan la oportunidad de obtener créditos universitarios.
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