6 Best Parallel Computing Courses

Parallel computing is a type of computing architecture in which several processors execute or process an application or computation simultaneously. Parallel computing helps in performing large computations by dividing the workload between more than one processor, all of which work through the computation at the same time. Most supercomputers employ parallel computing principles to operate. Parallel computing is also known as parallel processing.

Best Parallel Computing Courses List

Multithreading and Parallel Computing in Java
Parallel Programming
Learn Parallel Programming with C# and .NET
Akka Essentials with Scala | Rock the JVM
Introduction to High-Performance and Parallel Computing
Parallel Computing for Professionals

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1. Introduction To Parallel Computing And Multithreading in Java

In the 21st century, with the rise of Big Data and Machine Learning, the importance of multithreading and concurrent programming has reached new heights. This course delves into the basics of this fascinating topic, covering both multithreading concepts and parallel computing principles.

Course rating: 4.7 out of 5.0 (3,352 Rating total)
Duration: 10.5 Hours
Certificate: Certificate of completion

With this Parallel processing course, you will:

Understand basic concurrency
Understand the basics of multithreading
Understand parallel processing
Able to use the concepts in real-life scenarios

The course begins by exploring low-level concepts such as threads, synchronization, and locks. You'll gain a solid understanding of how threads operate and the challenges involved in ensuring thread safety and proper synchronization.

Moving forward, the course delves into the concurrent library, where you'll discover the built-in classes and interfaces that facilitate the implementation of multithreaded applications. You'll explore these powerful tools that simplify complex concurrency scenarios and enable you to develop efficient and robust multithreaded programs.

To reinforce your understanding, the course presents practical examples in the form of show-case programs. You'll tackle classic multithreading problems, such as the dining philosopher problem and the students in the library simulation. These real-world scenarios will challenge your skills and deepen your comprehension of multithreading concepts.

In the final chapter, you'll explore parallel computing and delve into the world of MapReduce. With the exponential growth of data, parallel computing has become essential for processing vast amounts of information efficiently. You'll learn how to leverage parallel computing techniques to accelerate computations and tackle complex data processing tasks.

By the end of this course, you'll have a solid foundation in multithreading and concurrent programming. You'll be equipped with the knowledge to develop multithreaded applications, handle synchronization challenges, and harness the power of parallel computing using MapReduce.

2. Parallel Programming

Learn Parallel programming tutorials from École Polytechnique Fédérale de Lausanne. With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread.

Course rating: 4.4 out of 5.0 (1,838 Rating total)
Duration: 32 Hours
Certificate: Certificate of completion

With this Parallel programming tutorial, you will:

Learn about task and data parallel programs,
Learn common algorithms in a functional style and solve them in parallel,
Learn competently microbenchmark parallel code,
Write programs that effectively use parallel collections to achieve performance

With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this Parallel programming tutorial, 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 the data parallel paradigm.

This Parallel programming course starts with the nuts and bolts of how to effectively parallelize familiar collections operations and will 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.

You can take the Parallel Programming Certificate Course on Coursera.

3. Learn Parallel Programming with C# and .NET

In this comprehensive course, you'll dive into the world of .NET Parallel Programming with C#. You'll explore the core multithreading facilities offered by the .NET Framework, specifically focusing on the Task Parallel Library (TPL) and Parallel LINQ (PLINQ).

Course rating: 4.5 out of 5.0 (4,016 Rating total)
Duration: 5.5 Hours
Certificate: Certificate of completion

With this Parallel Processing course online, you will:

Create and run independent tasks
Manage synchronized access to data
Effectively use parallel collections
Work with task continuations
Write parallel loops
Leverage the power of Parallel LINQ
Master asynchronous programming (async/await)

The course covers a wide range of topics to equip you with the necessary skills and knowledge to leverage the power of parallel programming in your .NET applications. You'll start by delving into Task Programming, learning how to create, run, cancel, wait on, and handle exceptions in tasks. Ensuring safe and consistent access to shared data is vital, and the course will guide you through Data Sharing and Synchronization techniques.

Concurrent Collections, such as ConcurrentBag, will be introduced, providing you with tools to work with shared data in a thread-safe manner. Task Coordination concepts, including continuations and synchronization primitives, will allow you to effectively coordinate tasks in your applications.

Parallel Loops will be explored, enabling you to iterate over data while partitioning and processing it on separate threads effortlessly. Additionally, you'll delve into Parallel LINQ (PLINQ), the parallel version of .NET's Language-Integrated Query (LINQ) technology. PLINQ allows you to harness the power of parallelism while querying data, improving performance and scalability.

Finally, the course will cover Async/Await and .NET's support for asynchronous programming. You'll learn how to leverage asynchronous programming patterns to enhance the responsiveness and efficiency of your applications.

By the end of this course, you'll have a comprehensive understanding of .NET Parallel Programming with C#. You'll be equipped with the skills to create efficient and scalable multithreaded applications using the TPL, PLINQ, and asynchronous programming techniques.

Whether you're a seasoned .NET developer or a beginner looking to explore the realm of parallel programming, this course is designed to expand your knowledge and empower you to leverage the full potential of multithreading and parallelism in your .NET applications.

4. Akka Essentials with Scala | Rock the JVM

In this comprehensive course, you'll delve into the world of concurrent and resilient application development using Akka actors. With hands-on guidance, you'll learn to write over 2000 lines of Akka code, equipping you with the skills to become a rockstar in building robust and scalable applications.

Course rating: 4.8 out of 5.0 (2,044 Rating total)
Duration: 13 Hours
Certificate: Certificate of completion

With this Parallel processing course on Scala, you will:

Create concurrent applications with actors instead of threads and locks
Design fault-tolerant systems with supervision
Configure Akka for various scenarios
Confidently test actor systems
Use Akka patterns and best practices

This Parallel processing course on Scala deconstructs all concepts into the critical pieces you need selects the most important ideas and separates them into what's simple but critical and what's powerful sequences ideas in a way that "clicks" and makes sense throughout the process of learning applies everything in live code.

The course focuses on Akka actors, a powerful model for concurrent and distributed programming. You'll explore the fundamental concepts of actor-based systems, understanding how actors communicate, collaborate, and handle failures. Through practical exercises and real-world examples, you'll gain a deep understanding of writing Akka code and effectively utilizing its features.

By the end of the course, you'll be proficient in designing and implementing concurrent and resilient applications using Akka actors. You'll be equipped with the skills to handle complex scenarios, distribute workloads, and build fault-tolerant systems.

This Parallel processing course on Scala is for established programmers with experience with Scala and with functional programming at the level of the Rock the JVM Scala beginners course.

You can take Rock the JVM! Akka Essentials with Scala Certificate Course on Udemy.

5. Introduction to High-Performance and Parallel Computing

Learn the fundamentals of high-performance and parallel computing.

Course rating: 15,078 total enrollments
Duration: 17 Hours
Certificate: Certificate of completion

With this parallel computing course, you will be able to:

The components of a high-performance distributed computing system.
Types of parallel programming models and the situations in which they might be used.
High-throughput computing.
Shared memory parallelism.
Distributed memory parallelism.
Navigating a typical Linux-based HPC environment.
Assessing and analyzing application scalability including weak and strong scaling.
Quantifying the processing, data, and cost requirements for a computational project or workflow.

Get to know the basics of an HPC system. Initially, you will learn how to work with common high-performance computing systems they may encounter in future efforts.

This includes navigating filesystems, working with a typical HPC operating system (Linux), and some of the basic concepts of HPC. It will also provide users with some key information that is specific to the logistics of this course.

Next, you will actually begin to use HPC infrastructure. Some concepts we will learn are - how to load software appropriately onto an HPC system, what the different types of nodes a user can expect to encounter on a system, and how to submit a job to conduct work, such as perform calculations.

After that, the course will introduce users to the nuances of memory on a high-performance computing system. We will also cover some ways to conduct work on a system most efficiently. You will also introduce some beginning components of parallel programming.

Finally, the course will continue to review topics related to using a high-performance computing system most efficiently, including scaling your workflow measuring how efficient your work on a system is, and how to utilize as much of the computing resource as possible.

You can take the Introduction to High-Performance and Parallel Computing Certificate Course on Coursera.

6. Parallel Computing for Professionals

These tutorials on Parallel Computing for professionals are an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines.

Numerical topics include: dense and sparse linear algebra, N-body problems, multigrid, fast-multipole, wavelets, and Fourier transforms. Geometrical topics include partitioning and mesh generation. Other topics include applications-oriented architecture, understanding parallel programming paradigms, MPI, data-parallel systems, Star-P for parallel Python and parallel MATLAB®, graphics processors, virtualization, caches, and vector processors.

One emphasis for this tutorial on Parallel Computing for professionals will be VHLLs or Very High-Level Languages for Parallel Computing. This includes the Julia programming language. Julia is a high-level, high-performance dynamic language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

You can take the Parallel Computing Certificate Course on MIT OpenCourseWare.

Thank you for reading this. We hope our course curation will help you to pick the right course to learn Parallel Computing. In case you want to explore more, you can take the free Parallel Computing courses.

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