About this Course
4.4
1,343 ratings
•
218 reviews
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....
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Functional Programming in Scala Specialization
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Intermediate Level

Intermediate Level

Clock

Suggested: 5 hours/week

Approx. 16 hours to complete
Comment Dots

English

Subtitles: English

Skills you will gain

Parallel ComputingData ParallelismParallel AlgorithmData Structure
Stacks

Course 3 of 5 in the

Functional Programming in Scala Specialization
Globe

100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Clock

Suggested: 5 hours/week

Approx. 16 hours to complete
Comment Dots

English

Subtitles: English

Syllabus - What you will learn from this course

1

Section
Clock
12 hours to complete

Parallel Programming

We motivate parallel programming and introduce the basic constructs for building parallel programs on JVM and Scala. Examples such as array norm and Monte Carlo computations illustrate these concepts. We show how to estimate work and depth of parallel programs as well as how to benchmark the implementations....
Reading
9 videos (Total 106 min), 5 readings, 3 quizzes
Video9 videos
Course Overview2m
Introduction to Parallel Computing15m
Parallelism on the JVM I13m
Parallelism on the JVM II8m
Running Computations in Parallel13m
Monte Carlo Method to Estimate Pi4m
First-Class Tasks7m
How Fast are Parallel Programs?24m
Benchmarking Parallel Programs17m
Reading5 readings
Tools Setup10m
Eclipse Tutorial10m
IntelliJ IDEA Tutorial10m
Sbt Tutorial10m
Submitting Solutions10m

2

Section
Clock
8 hours to complete

Basic Task Parallel Algorithms

We continue with examples of parallel algorithms by presenting a parallel merge sort. We then explain how operations such as map, reduce, and scan can be computed in parallel. We present associativity as the key condition enabling parallel implementation of reduce and scan....
Reading
6 videos (Total 100 min), 2 quizzes
Video6 videos
Parallel Sorting7m
Data Operations and Parallel Mapping18m
Parallel Fold (Reduce) Operation18m
Associativity I14m
Associativity II17m
Parallel Scan (Prefix Sum) Operation24m

3

Section
Clock
7 hours to complete

Data-Parallelism

We show how data parallel operations enable the development of elegant data-parallel code in Scala. We give an overview of the parallel collections hierarchy, including the traits of splitters and combiners that complement iterators and builders from the sequential case....
Reading
5 videos (Total 51 min), 2 quizzes
Video5 videos
Data-Parallel Programming11m
Data-Parallel Operations I6m
Data-Parallel Operations II8m
Scala Parallel Collections15m
Splitters and Combiners7m

4

Section
Clock
7 hours to complete

Data Structures for Parallel Computing

We give a glimpse of the internals of data structures for parallel computing, which helps us understand what is happening under the hood of parallel collections....
Reading
5 videos (Total 57 min), 2 quizzes
Video5 videos
Implementing Combiners12m
Parallel Two-phase Construction14m
Conc-tree Data Structure14m
Amortized, Constant-time Append Operation11m
Conc-Tree Combiners4m
4.4
Direction Signs

24%

started a new career after completing these courses
Briefcase

83%

got a tangible career benefit from this course

Top Reviews

By AL•Apr 24th 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.

By RC•Aug 25th 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.

Instructors

Prof. Viktor Kuncak

Associate Professor
School of Computer and Communication Sciences

Dr. Aleksandar Prokopec

Principal Researcher
Oracle Labs

About École Polytechnique Fédérale de Lausanne

About the Functional Programming in Scala Specialization

Discover how to write elegant code that works the first time it is run. This Specialization provides a hands-on introduction to functional programming using the widespread programming language, Scala. It begins from the basic building blocks of the functional paradigm, first showing how to use these blocks to solve small problems, before building up to combining these concepts to architect larger functional programs. You'll see how the functional paradigm facilitates parallel and distributed programming, and through a series of hands on examples and programming assignments, you'll learn how to analyze data sets small to large; from parallel programming on multicore architectures, to distributed programming on a cluster using Apache Spark. A final capstone project will allow you to apply the skills you learned by building a large data-intensive application using real-world data....
Functional Programming in Scala

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.

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