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.
Этот курс входит в специализацию ''Специализация Functional Programming in Scala'
от партнера
Специализация Functional Programming in ScalaФедеральная политехническая школа ЛозанныОб этом курсе
Приобретаемые навыки
- Data Structure
- Parallel Computing
- Data Parallelism
- Parallel Algorithm
от партнера
Программа курса: что вы изучите
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.
Рецензии
- 5 stars59,81 %
- 4 stars28,36 %
- 3 stars9,18 %
- 2 stars1,92 %
- 1 star0,71 %
Лучшие отзывы о курсе ПАРАЛЛЕЛЬНОЕ ПРОГРАММИРОВАНИЕ
Very good introduction to the topic. Examples and programming exercises were very good, although last assignment was visibly less polished than earlier ones.
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.
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.
Very good. Only things I wish were better is more comments in some assignments and more prepared tests. Also I miss not having "Statement of Accomplishment" like some other Scala courses :-(.
Специализация Functional Programming in Scala: общие сведения
Discover how to write elegant code that works the first time it is run.
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