このコースについて
4.6
596件の評価
125件のレビュー

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約15時間で修了

推奨:Four weeks of study, 4-8 hours/week depending on past experience with sequential programming in Java...

英語

字幕:英語

習得するスキル

DataflowParallel ComputingJava ConcurrencyData Parallelism

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約15時間で修了

推奨:Four weeks of study, 4-8 hours/week depending on past experience with sequential programming in Java...

英語

字幕:英語

シラバス - 本コースの学習内容

1
1時間で修了

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件のビデオ (合計1分), 5 readings, 1 quiz
1件のビデオ
5件の学習用教材
General Course Info5 分
Course Icon Legend5 分
Discussion Forum Guidelines5 分
Pre-Course Survey10 分
Mini Project 0: Setup10 分
4時間で修了

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....
7件のビデオ (合計42分), 6 readings, 2 quizzes
7件のビデオ
1.2 Tasks in Java's Fork/Join Framework5 分
1.3 Computation Graphs, Work, Span7 分
1.4 Multiprocessor Scheduling, Parallel Speedup8 分
1.5 Amdahl's Law5 分
ReciprocalArraySum using Async-Finish (Demo)4 分
ReciprocalArraySum using RecursiveAction's in Java's Fork/Join Framework (Demo)5 分
6件の学習用教材
1.1 Lecture Summary5 分
1.2 Lecture Summary5 分
1.3 Lecture Summary5 分
1.4 Lecture Summary5 分
1.5 Lecture Summary5 分
Mini Project 1: Reciprocal-Array-Sum using the Java Fork/Join Framework10 分
1の練習問題
Module 1 Quiz30 分
2
4時間で修了

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....
7件のビデオ (合計40分), 6 readings, 2 quizzes
7件のビデオ
2.2 Futures in Java's Fork/Join Framework5 分
2.3 Memoization6 分
2.4 Java Streams5 分
2.5 Data Races and Determinism9 分
ReciprocalArraySum using RecursiveTask's in Java's Fork/Join Framework (Demo)3 分
Parallel List Processing Using Java Streams (Demo)4 分
6件の学習用教材
2.1 Lecture Summary10 分
2.2 Lecture Summary10 分
2.3 Lecture Summary10 分
2.4 Lecture Summary10 分
2.5 Lecture Summary10 分
Mini Project 2: Analyzing Student Statistics Using Java Parallel Streams10 分
1の練習問題
Module 2 Quiz30 分
23分で修了

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....
2件のビデオ (合計13分), 1 reading
2件のビデオ
Industry Professionals on Parallelism - Jake Kornblau and Margaret Kelley, Software Engineers6 分
1件の学習用教材
About these Talks10 分
3
4時間で修了

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....
7件のビデオ (合計41分), 6 readings, 2 quizzes
7件のビデオ
3.2 Parallel Matrix Multiplication4 分
3.3 Barriers in Parallel Loops5 分
3.4 Parallel One-Dimensional Iterative Averaging8 分
3.5 Iteration Grouping/Chunking in Parallel Loops6 分
Parallel Matrix Multiplication (Demo)4 分
Parallel One-Dimensional Iterative Averaging (Demo)5 分
6件の学習用教材
3.1 Lecture Summary10 分
3.2 Lecture Summary10 分
3.3 Lecture Summary10 分
3.4 Lecture Summary10 分
3.5 Lecture Summary10 分
Mini Project 3: Parallelizing Matrix-Matrix Multiply Using Loop Parallelism10 分
1の練習問題
Module 3 Quiz30 分
4
4時間で修了

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. ...
7件のビデオ (合計38分), 7 readings, 2 quizzes
7件のビデオ
4.2 Point-to-Point Sychronization with Phasers4 分
4.3 One-Dimensional Iterative Averaging with Phasers4 分
4.4 Pipeline Parallelism5 分
4.5 Data Flow Parallelism5 分
Phaser Examples6 分
Pipeline & Data Flow Parallelism7 分
7件の学習用教材
4.1 Lecture Summary10 分
4.2 Lecture Summary10 分
4.3 Lecture Summary10 分
4.4 Lecture Summary10 分
4.5 Lecture Summary10 分
Mini Project 4: Using Phasers to Optimize Data-Parallel Applications10 分
Exit Survey10 分
1の練習問題
Module 4 Quiz30 分
20分で修了

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....
2件のビデオ (合計10分), 1 reading
2件のビデオ
Industry Professional on Distribution - Dr. Eric Allen, Senior Vice President, Two Sigma6 分
1件の学習用教材
Our Other Course Offerings10 分
4.6
125件のレビューChevron Right

25%

コース終了後に新しいキャリアをスタートした

12%

コースが具体的なキャリアアップにつながった

人気のレビュー

by LGDec 13th 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.

by SVAug 28th 2017

Great course. Introduces Parallel Programming in Java in a gentle way.\n\nKudos to Professor Vivek Sarkar for simplifying complex concepts and presenting them in an elegant manner.

講師

Avatar

Vivek Sarkar

Professor
Department of Computer Science

ライス大学(Rice University)について

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....

Parallel, Concurrent, and Distributed Programming in Javaの専門講座について

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)....
Parallel, Concurrent, and Distributed Programming in Java

よくある質問

  • 修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題(該当する場合)にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。

  • コースに登録する際、専門講座のすべてのコースにアクセスできます。コースの完了時には修了証を取得できます。電子修了証が成果のページに追加され、そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。