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Noel Araujo Moreira

Welcome. I was waiting for you.

This course dives headfirst into the world of parallel programming.

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Welcome. I was waiting for you.

This course dives headfirst into the world of parallel programming.

We'll equip you with the skills to tackle problems by harnessing the power of multiple processors. Forget the tired old "pi calculation" examples – we'll explore practical applications that showcase the true potential of parallel computing.

Leveraging the JuliaHub infrastructure and its rich ecosystem of packages, we'll guide you through the core concepts with clear, concise explanations and plenty of real-world examples. We'll also equip you with performance optimization tips to ensure your code runs as efficiently as possible.

On this course, you can expect:

  • Practical Examples: Dive into hands-on examples that go beyond simple tasks, helping you understand and apply parallel programming concepts effectively.

  • JuliaHub Infrastructure: Utilize the JuliaHub platform to run and manage your computations seamlessly.

  • Julia Package Ecosystem: Explore and use a wide range of Julia packages that enhance your parallel programming capabilities.

  • Performance Tips: Learn valuable tips and techniques to optimize the performance of your parallel programs.

  • Focused Content: The course is designed to be straight to the point, emphasizing core messages and essential concepts to maximize your learning experience.

So, buckle up and get ready to unlock the power of parallel programming.

Enroll now

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What's inside

Learning objectives

  • Students will gain an understanding of fundamental commands in parallel computing in multi-threading and distributed computing paradigms in julia.
  • Students will be exposed to julia's tools and packages for parallel programming.
  • Students will explore common and also unusual applications of parallelism.
  • Students will be able to use multi-threading and distributed computing at the same time.

Syllabus

Videos aimed to setup some expectations
Introduction



Multi-threading
Read more
Welcome to Multi-threading
Before Getting Started
@threads
@spawn
@sync
Atomics
Locks
Channels
Channels Application - Producer-Consumer
Threading going wrong
Threading going right - prologue
Threading going right - code
Threading going right - alternative
Image Processing Algorithm
Image Processing with Threads
Distributed Computing
Welcome to Distributed Computing
addprocs local machine
addprocs remote machine
@everywhere
Fine control
Distributed + Multi-threading part 1
Distributed + Multi-threading part 2
SharedArrays
Parallel k-means part 1
Parallel k-means part 2
DistributedArrays part 1
DistributedArrays part 2
Digging
RemoteChannels
Channels + Workpool
Pipeline part 1
Pipeline part 2
Pipeline part 3

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Ideal for learners looking to get started with parallel programming in Julia
Suitable for those with an interest in multi-threading and distributed computing
Provides a basis for more complex parallel programming topics
May require some prior experience in programming

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Parallel Computing in Julia with these activities:
Review your linear algebra and calculus skills
Reviewing your linear algebra and calculus skills will help you better understand the mathematical concepts behind parallel programming.
Browse courses on Linear Algebra
Show steps
  • Review your notes from your linear algebra and calculus courses.
  • Take practice problems on linear algebra and calculus.
  • Find a tutor or online resources to help you with any areas where you need additional support.
Follow a tutorial on parallel programming in Julia
Following a tutorial will help you get started with parallel programming in Julia
Browse courses on Parallel Programming
Show steps
  • Find a tutorial on parallel programming in Julia.
  • Follow the tutorial step-by-step.
Create a study guide for the course
Creating a study guide will help you organize your notes and better prepare for exams.
Browse courses on Parallel Programming
Show steps
  • Gather your notes, assignments, and other course materials.
  • Organize your materials into a logical order.
  • Create a study guide that includes key concepts, definitions, and examples.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice solving multithreading problems
Solving problems will help you deeply understand how multi-threading works and how to apply it.
Show steps
  • Solve easy multithreading problems on platforms like Leetcode or Hackerrank.
  • Try to solve more complex multithreading problems.
Practice solving distributed computing problems
Solving problems will help you deeply understand how distributed computing works and how to apply it.
Browse courses on Distributed Computing
Show steps
  • Solve easy distributed computing problems on platforms like Leetcode or Hackerrank.
  • Try to solve more complex distributed computing problems.
Write a blog post about a parallel programming project
Writing a blog post will help you solidify your understanding of parallel programming and share your knowledge with others.
Browse courses on Parallel Programming
Show steps
  • Choose a parallel programming project that you have worked on.
  • Write a blog post about your project, including the problem you solved, the approach you took, and the results you achieved.
  • Publish your blog post and share it with others.
Build a parallel programming application
Building a parallel programming application will give you hands-on experience with the concepts you learn in this course.
Browse courses on Parallel Programming
Show steps
  • Choose a problem that you want to solve using parallel programming.
  • Design and implement a parallel programming solution to the problem.
  • Test and debug your solution.
  • Deploy your solution to a real-world environment.

Career center

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