Parallel programming

École Polytechnique Fédérale de Lausanne via Coursera

Go to Course: https://www.coursera.org/learn/scala-parallel-programming

Introduction

**Course Review: Parallel Programming on Coursera** In today's world, where nearly every smartphone and computer comes equipped with multiple processors, the demand for learning parallel programming has never been greater. The Coursera course titled "Parallel Programming" effectively addresses this need by providing a comprehensive overview of parallel programming principles, specifically through the lens of functional programming. In this review, I will detail the course's content, strengths, and my recommendation for potential learners. ### Course Overview The "Parallel Programming" course focuses on fundamental parallel programming concepts, exploring the distinctions between task parallelism and data parallelism. The course is particularly well-structured for those with a background in functional programming, as it illustrates how familiar concepts translate profoundly into the data-parallel paradigm. **Course Syllabus Breakdown:** 1. **Parallel Programming Fundamentals:** The course kicks off by motivating the need for parallel programming, guiding learners through the essential constructs for building parallel programs on the Java Virtual Machine (JVM) using Scala. This segment incorporates relatable examples, including array norm computations and Monte Carlo simulations, to solidify understanding. Moreover, learners assess the work and depth of parallel programs while benchmarking their implementations. 2. **Basic Task Parallel Algorithms:** As the course progresses, it delves into basic task parallel algorithms. A standout topic here is parallel merge sort, a classic algorithm that benefits significantly from parallel execution. Additionally, the course covers essential operations like map, reduce, and scan, emphasizing the significance of associativity—a key trait that allows for efficient parallel implementations of these operations. 3. **Data-Parallelism:** This section focuses on data-parallel operations and introduces learners to elegant code development in Scala. An overview of the parallel collections hierarchy is provided, along with an explanation of how traits like splitters and combiners complement the well-known iterators and builders from sequential programming. 4. **Data Structures for Parallel Computing:** Finally, the course takes a closer look at the internals of data structures used for parallel computing. This insight equips learners with a deeper understanding of what happens beneath the surface when working with parallel collections, fostering a holistic grasp of parallel programming mechanisms. ### Course Highlights - **Practical Examples:** The course stands out by integrating practical examples to illustrate complex concepts, making the material accessible and engaging. - **Focus on Scala:** Given Scala's prominence in functional programming and its seamless integration with JVM, learners gain valuable skills that are directly applicable in the industry. - **Strong Theoretical Foundation:** The balance of theory and practice enhances comprehension, allowing students to not only grasp parallel programming techniques but also understand their underlying principles. ### Recommendations This course is perfect for software developers, computer science students, and tech enthusiasts seeking to expand their programming expertise into the realm of parallelism. Prior knowledge of functional programming concepts is advantageous, but the course is structured to cater to learners from diverse backgrounds. ### Conclusion In summary, the "Parallel Programming" course on Coursera is an invaluable resource for anyone looking to deepen their knowledge of parallel computing. With its compelling curriculum, practical focus, and accessibility, this course offers learners the tools necessary to leverage the power of multi-core processors effectively. I highly recommend this course to those aiming to enhance their programming skills and stay relevant in today's fast-evolving technological landscape. Whether you're a beginner or someone seeking to polish your existing skills, this course promises to elevate your understanding of parallel programming to new heights.

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.

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.

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.

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.

Overview

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 operatio

Skills

Data Structure Parallel Computing Data Parallelism Parallel Algorithm

Reviews

The assignment could be optimized and avoid to be more academic since it may make student lost focus and spend too much time on the question itself rather than the parallel programming

Its a very good course! perhaps the in the practice code, before jumping into the problems they can provide a couple of simple examples/questions such that the main ideas are learnt.

Truly great course. The assignments are designed very well. The instructor and videos were excellent. I only wish there had been more student participation in the forum.

For this course you should have Advanced English level. Cause sentesce construction is so difficult and words so unusual that i had to some times google what i have to do.

Good course but scala understanding is required for this course. So please register for prior course in the certification task to easily complete this course.