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 faz parte do Programa de cursos integrados Parallel, Concurrent, and Distributed Programming in Java
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Informações sobre o curso
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Resultados de carreira do aprendiz
12%
comecei uma nova carreira após concluir estes cursos
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 19 horas para completar
Inglês
Legendas: Inglês
Habilidades que você terá
DataflowParallel ComputingJava ConcurrencyData Parallelism
Resultados de carreira do aprendiz
12%
comecei uma nova carreira após concluir estes cursos
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 19 horas para completar
Inglês
Legendas: Inglês
oferecido por
Universidade 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 - O que você aprenderá com este curso
1 hora para concluir
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 concluir
1 vídeo (Total 1 mín.), 5 leituras, 1 teste
1 vídeos
Course Welcome1min
5 leituras
General Course Info5min
Course Icon Legend5min
Discussion Forum Guidelines5min
Pre-Course Survey10min
Mini Project 0: Setup10min
4 horas para concluir
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 concluir
7 vídeos (Total 42 mín.), 6 leituras, 2 testes
7 videos
1.2 Tasks in Java's Fork/Join Framework5min
1.3 Computation Graphs, Work, Span7min
1.4 Multiprocessor Scheduling, Parallel Speedup8min
1.5 Amdahl's Law5min
ReciprocalArraySum using Async-Finish (Demo)4min
ReciprocalArraySum using RecursiveAction's in Java's Fork/Join Framework (Demo)5min
6 leituras
1.1 Lecture Summary5min
1.2 Lecture Summary5min
1.3 Lecture Summary5min
1.4 Lecture Summary5min
1.5 Lecture Summary5min
Mini Project 1: Reciprocal-Array-Sum using the Java Fork/Join Framework10min
1 exercício prático
Module 1 Quiz30min
4 horas para concluir
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 concluir
7 vídeos (Total 40 mín.), 6 leituras, 2 testes
7 videos
2.2 Futures in Java's Fork/Join Framework5min
2.3 Memoization6min
2.4 Java Streams5min
2.5 Data Races and Determinism9min
ReciprocalArraySum using RecursiveTask's in Java's Fork/Join Framework (Demo)3min
Parallel List Processing Using Java Streams (Demo)4min
6 leituras
2.1 Lecture Summary10min
2.2 Lecture Summary10min
2.3 Lecture Summary10min
2.4 Lecture Summary10min
2.5 Lecture Summary10min
Mini Project 2: Analyzing Student Statistics Using Java Parallel Streams10min
1 exercício prático
Module 2 Quiz30min
23 minutos para concluir
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 concluir
2 vídeos (Total 13 mín.), 1 leitura
2 videos
Industry Professionals on Parallelism - Jake Kornblau and Margaret Kelley, Software Engineers6min
1 leituras
About these Talks10min
4 horas para concluir
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 concluir
7 vídeos (Total 41 mín.), 6 leituras, 2 testes
7 videos
3.2 Parallel Matrix Multiplication4min
3.3 Barriers in Parallel Loops5min
3.4 Parallel One-Dimensional Iterative Averaging8min
3.5 Iteration Grouping/Chunking in Parallel Loops6min
Parallel Matrix Multiplication (Demo)4min
Parallel One-Dimensional Iterative Averaging (Demo)5min
6 leituras
3.1 Lecture Summary10min
3.2 Lecture Summary10min
3.3 Lecture Summary10min
3.4 Lecture Summary10min
3.5 Lecture Summary10min
Mini Project 3: Parallelizing Matrix-Matrix Multiply Using Loop Parallelism10min
1 exercício prático
Module 3 Quiz30min
5 horas para concluir
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 concluir
7 vídeos (Total 38 mín.), 7 leituras, 2 testes
7 videos
4.2 Point-to-Point Sychronization with Phasers4min
4.3 One-Dimensional Iterative Averaging with Phasers4min
4.4 Pipeline Parallelism5min
4.5 Data Flow Parallelism5min
Phaser Examples6min
Pipeline & Data Flow Parallelism7min
7 leituras
4.1 Lecture Summary10min
4.2 Lecture Summary10min
4.3 Lecture Summary10min
4.4 Lecture Summary10min
4.5 Lecture Summary10min
Mini Project 4: Using Phasers to Optimize Data-Parallel Applications10min
Exit Survey10min
1 exercício prático
Module 4 Quiz30min
20 minutos para concluir
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 concluir
2 vídeos (Total 10 mín.), 1 leitura
2 videos
Industry Professional on Distribution - Dr. Eric Allen, Senior Vice President, Two Sigma6min
1 leituras
Our Other Course Offerings10min
Avaliações
Principais avaliações do PARALLEL PROGRAMMING IN JAVA
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 LG12 de Dez 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 SD25 de Mai 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.
Sobre Programa de cursos integrados 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.
To see an overview video for this Specialization, click here! For an interview with two early-career software engineers on the relevance of parallel computing to their jobs, click here.
Acknowledgments
The instructor, Prof. Vivek Sarkar, would like to thank Dr. Max Grossman for his contributions to the mini-projects and other course material, Dr. Zoran Budimlic for his contributions to the quizzes, Dr. Max Grossman and Dr. Shams Imam for their contributions to the pedagogic PCDP library used in some of the mini-projects, and all members of the Rice Online team who contributed to the development of the course content (including Martin Calvi, Annette Howe, Seth Tyger, and Chong Zhou).
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
O acesso a palestras e tarefas depende do tipo de inscrição. Se você participar de um curso como ouvinte, você poderá ver quase todo o conteúdo do curso gratuitamente. Para acessar tarefas valendo nota e obter um Certificado, você precisará adquirir a experiência do Certificado, durante ou após a participação como ouvinte. Se você não vir a opção de participar como ouvinte:
- o curso pode não oferecer essa opção. Você pode experimentar um teste gratuito ou solicitar o auxílio financeiro.
- Em vez disso, o curso pode oferecer 'Curso completo, sem Certificado'. Com esta opção, é possível ver todo o conteúdo do curso, enviar as avaliações necessárias e obter uma nota final. Isso também significa que você não poderá comprar uma experiência de Certificado.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Qual é a política de reembolso?
Se você se inscrever, terá 7 dias para testar sem custo e, durante este período, pode cancelar sem multa. Depois disso, não reembolsamos, mas você pode cancelar sua inscrição a qualquer momento. Veja nossa política para o reembolso total.
Existe algum auxílio financeiro disponível?
Sim, a Coursera oferece auxílio financeiro ao aluno que não possa pagar a taxa. Faça a solicitação clicando no link Auxílio Financeiro, abaixo do botão "Inscreva-se" à esquerda. Preencha uma solicitação e será notificado caso seja aprovado. Você terá que completar esta etapa para cada curso na Especialização, incluindo o Trabalho de Conclusão de Curso. Saiba mais .
Ganharei créditos universitários por concluir o curso?
Este curso não oferece créditos universitários, mas algumas universidades podem aceitar certificados de cursos que podem ser convertidos em créditos. Entre em contato com sua instituição para saber mais. Com os cursos on-line e os certificados Mastertrack™ do Coursera, é possível ganhar créditos universitários.
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