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Parallel programming

Prof. Viktor Kuncak and Dr. Aleksandar Prokopec

4.4

Based on 1,844 ratings

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Prof. Viktor Kuncak and Dr. Aleksandar Prokopec

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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Syllabus

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.

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Learners will be able to develop data-parallel code solutions in Scala

Learners will be able to solve functional problems in parallel

Learners will be able to benchmark and optimize parallel code using microbenchmarking

Learners will gain proficiency with Java or C# and at least one year of programming experience is recommended

Familiarity using the command line is required

This course comes after Functional Program Design in Scala

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Reviews summary

Challenging parallel programming with scala

According to learners, this course on Parallel programming is challenging but rewarding, offering great hands-on assignments that solidify concepts. Students praise the clear explanations and logical progression through topics like task and data parallelism and parallel collections. However, a strong background in Scala, particularly from the prerequisite course, is deemed essential and possibly underestimated by some. Some reviewers found parts theoretical, wishing for more practical examples or guidance on real-world application, and noted the pacing could be fast in later modules, with some areas feeling rushed or lacking production-level depth.

Strong functional Scala background needed.

"Prerequisites are important, especially the first Scala course."

"Definitely need a solid grasp of Scala from the previous course."

"Make sure you are very comfortable with Scala beforehand."

"The prerequisites mentioned were underestimated."

Core parallel concepts explained well.

"The concepts of parallel collections and task parallelism were well explained."

"The explanations are clear, and the progression... is logical."

"The material is challenging but presented very well."

"Covers important concepts like work/depth analysis and parallel collections effectively."

Rigorous tasks solidify parallel concepts.

"The assignments were great and really made you think."

"Loved the hands-on assignments! They solidified the concepts perfectly."

"Some exercises are quite difficult, pushing you to apply the concepts rigorously."

"I struggled with the assignments, they require a much deeper understanding than the lectures provide."

Pacing fast, limited depth in some areas.

"Found the pacing a bit fast in the later modules."

"The data structures part was interesting but felt rushed."

"maybe not enough depth for production-ready parallel programming."

Good theory, less real-world application guidance.

"Some parts were quite theoretical, could use more practical examples."

"The theory is sound, but I felt there wasn't enough guidance on real-world application."

"The parallel collections felt a bit abstract without larger projects."

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Gather all course materials, including notes, slides, and assignments.
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Scala Refresher

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Strengthen foundational Scala skills by reviewing basic syntax, data structures, and functional programming concepts, ensuring a solid understanding before delving into parallel programming.

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Review Scala data types, operators, and control flow
Practice working with Scala collections and functional operations

Read 'Parallel Programming in Scala'

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Reinforce your understanding and supplement your knowledge by reading the book 'Parallel Programming in Scala', which covers the key concepts of the course.

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Obtain a copy of the book.
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Solve parallel programming problems on LeetCode

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Enhance your understanding of parallel programming concepts by tackling challenges on LeetCode, a platform known for its coding problems.

Browse courses on Task Parallelism

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Choose a problem that involves task or data parallelism.
Analyze the problem and devise a parallel solution.
Implement your solution and submit it for evaluation.

Parallel Programming Drills

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Enhance understanding of parallel programming concepts through practical exercises, solidifying foundational knowledge and improving problem-solving abilities.

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Solve coding problems involving task parallelism
Implement data parallel algorithms in Scala
Analyze and parallelize sequential code
Experiment with different parallel collection operations

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Participate in discussions on parallel programming principles
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Present and explain parallel programming techniques to peers

Build a data parallel application

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Reinforce your knowledge and practice applying the concepts of task and data parallelism by developing a data parallel application.

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Design the architecture of your application.
Implement the data parallel operations.
Test and benchmark your application.

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Parallel Programming Blog Post

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Career center

Learners who complete Parallel programming will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use their knowledge of mathematics, statistics, and computer science to extract meaningful insights from data. This course in Parallel Programming will help you develop the skills you need to succeed as a Data Scientist. You will learn how to parallelize common data science algorithms, and how to use parallel collections to achieve performance.

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Machine Learning Engineer

Machine Learning Engineers design and implement machine learning models to solve real-world problems. This course in Parallel Programming will help you build a foundation for a career in Machine Learning Engineering. You will learn about the fundamentals of parallel programming, and how to apply these concepts to machine learning algorithms.

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Computer Scientist

Computer Scientists research and develop new computing technologies. This course in Parallel Programming will help you build a foundation for a career in Computer Science. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the design and implementation of new computing technologies.

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Data Engineer

Data Engineers design and implement data pipelines to collect, store, and process data. This course in Parallel Programming can help build a foundation for a career in Data Engineering. You will learn about the fundamentals of parallel programming, and how to apply these concepts to data engineering tasks.

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Software Engineer

Software Engineers analyze user needs and business requirements to design, develop, test, and deploy software applications. This course in Parallel Programming can help build a foundation for a career in Software Engineering. You will learn about task and data parallel programming, and how to apply these concepts to real-world data analysis tasks.

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Systems Analyst

Systems Analysts analyze and design computer systems to meet the needs of businesses and organizations. This course in Parallel Programming may be useful for those interested in a career as a Systems Analyst. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the design of computer systems.

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Software Architect

Software Architects design and develop the overall architecture of software systems. This course in Parallel Programming may be useful for those interested in a career as a Software Architect. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the design of software systems.

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Database Administrator

Database Administrators maintain and administer databases. This course in Parallel Programming may be useful for those interested in a career as a Database Administrator. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the management of databases.

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Teacher

Teachers educate students in a variety of subjects. This course in Parallel Programming may be useful for those interested in a career as a Teacher. You will learn about the fundamentals of parallel programming, and how to teach these concepts to students.

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Technical Writer

Technical Writers create documentation for software and other technical products. This course in Parallel Programming may be useful for those interested in a career as a Technical Writer. You will learn about the fundamentals of parallel programming, and how to write clear and concise documentation for technical products.

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Product Manager

Product Managers manage the development and launch of new products. This course in Parallel Programming may be useful for those interested in a career as a Product Manager. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the development of new products.

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Project Manager

Project Managers plan and manage the development of software and other technical projects. This course in Parallel Programming may be useful for those interested in a career as a Project Manager. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the management of technical projects.

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Business Analyst

Business Analysts analyze the business needs of organizations and develop solutions to meet those needs. This course in Parallel Programming may be useful for those interested in a career as a Business Analyst. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the analysis of business needs and the development of solutions.

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Consultant

Consultants provide advice and guidance to businesses and organizations on a variety of topics. This course in Parallel Programming may be useful for those interested in a career as a Consultant. You will learn about the fundamentals of parallel programming, and how to apply these concepts to the analysis of business needs and the development of solutions.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course in Parallel Programming may be useful for those interested in a career as a Quantitative Analyst. You will learn about task and data parallel programming, and how to apply these concepts to financial data analysis.

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Reading list

We've selected 29 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Parallel programming.

An Introduction to Parallel Programming

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Offers a comprehensive introduction to parallel programming, covering various parallel programming models and paradigms, as well as practical techniques for writing efficient parallel code.

Parallel programming

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Challenging parallel programming with scala

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