Chevron Left
Back to Parallel programming

Learner Reviews & Feedback for Parallel programming by École Polytechnique Fédérale de Lausanne

4.4
stars
1,821 ratings

About the Course

With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this course, you'll learn the fundamentals of parallel programming, from task parallelism to data parallelism. In particular, you'll see how many familiar ideas from functional programming map perfectly to to the data parallel paradigm. We'll start the nuts and bolts how to effectively parallelize familiar collections operations, and we'll build up to parallel collections, a production-ready data parallel collections library available in the Scala standard library. Throughout, we'll apply these concepts through several hands-on examples that analyze real-world data, such as popular algorithms like k-means clustering. Learning Outcomes. By the end of this course you will be able to: - reason about task and data parallel programs, - express common algorithms in a functional style and solve them in parallel, - competently microbenchmark parallel code, - write programs that effectively use parallel collections to achieve performance Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Functional Program Design in Scala: https://www.coursera.org/learn/progfun2....

Top reviews

AL

Apr 23, 2018

The course is fairly advanced and you would need to review the materials many times to understand the concept. The assignments are definitely fun and not as straightforward as other courses.

RC

Aug 24, 2017

Superb study material. Learnt a lot during this course. I am not much into mathematical stuff, but got a hang of how to break problems and improve efficiency through parallelism.

Filter by:

201 - 225 of 269 Reviews for Parallel programming

By Chet W

Jan 29, 2018

By Hong C

Apr 2, 2020

By Atsuya K

Feb 8, 2018

By Alexey K

Jan 31, 2019

By Vladislav A

Apr 8, 2020

By Patrik I

Dec 17, 2019

By Yiran W

Jul 18, 2018

By Igor R d S

Oct 23, 2016

By Anton B

Dec 10, 2018

By Давиденко А Ю

Mar 19, 2021

By Jędrzej B

May 22, 2020

By Kyoung-Seop P

Jan 24, 2017

By Daniel D

Dec 29, 2016

By Youwei Z

Sep 13, 2016

By Dean T

Jan 3, 2019

By Seoh C

Oct 4, 2017

By Konstantin K

Oct 28, 2016

By Shi Y

Sep 13, 2019

By Ilya D

Jun 22, 2016

By David P

Jan 25, 2017

By rafael f o

May 9, 2020

By EL H C

May 14, 2021

By Théophile G

Jul 17, 2017

By Pedro R

Mar 15, 2017

By c86jeff

Jan 22, 2017