Parallel Programming

 

 


 

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E.g., 2016-12-09
E.g., 2016-12-09
E.g., 2016-12-09
Dec 5th 2016

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.

Average: 4.8 (5 votes)
Aug 15th 2016

Learn how to apply data science techniques using parallel programming in Apache Spark to explore big data.

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Jun 1st 2015

Learn how to apply data science techniques using parallel programming in Apache Spark to explore big (and small) data.

Average: 9 (1 vote)
Jan12th 2015

This course introduces concepts, languages, techniques, and patterns for programming heterogeneous, massively parallel processors. Its contents and structure have been significantly revised based on the experience gained from its initial offering in 2012. It covers heterogeneous computing architectures, data-parallel programming models, techniques for memory bandwidth management, and parallel algorithm patterns.

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Self Paced Course - Start anytime

Using CUDA to Harness the Power of GPUs.

Average: 9 (1 vote)
Self Paced

The openHPI online course “Parallel Programming Concepts” presents relevant theoretical and practical foundations for parallel programming. We show crucial theoretical ideas such as semaphores and actors, the architecture of modern parallel hardware, different programming models such as task parallelism, message passing and functional programming, and several patterns and best practices.

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