Mastering Multithreading Programming with Go (Golang)

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Mastering Multithreading Programming with Go (Golang) (Size: 2.1 GB)
  0 17.1 KB
  01 - Understanding Parallel Computing.mp4 18.5 MB
  02 - More on Parallel Computing.mp4 135.5 MB
  03 - Processes, Threads and Green threads.mp4 154 MB
  04 - Using Goroutines for Boids.mp4 32.3 MB
  05 - Groundwork for our simulation.mp4 29 MB
  06 - Starting our Goroutines.mp4 64.6 MB
  07 - Memory sharing between Threads.mp4 17.3 MB
  08 - Memory Sharing example Part 1.mp4 43.1 MB
  09 - Memory Sharing example Part 2.mp4 58.6 MB
  10 - Why do we need Locking.mp4 67.4 MB
  11 - Using Mutexes in Boid simulation.mp4 27.3 MB
  12 - Adding Synchronization to simulation.mp4 49 MB
  13 - Readers-Writer Locks.mp4 28 MB
  14 - Boid Synchronization with Readers-Writers Locks.mp4 82.6 MB
  15 - Understanding WaitGroups.mp4 52.9 MB
  16 - Concurrent file searching with WaitGroups.mp4 56.9 MB
  17 - Thread Communication using Channels.mp4 78.7 MB
  18 - Pipelining Example.mp4 133.3 MB
  19 - Understanding Thread Pools.mp4 19.7 MB
  20 - Thread Pool Example Part 1.mp4 68.5 MB
  21 - Thread Pool Example Part 2.mp4 35.4 MB
  22 - What's a Condition Variable.mp4 45.3 MB
  23 - Parallel Algorithm for Matrix Multiplication.mp4 27.9 MB
  24 - Implementing Parallel Matrix Multiplication Part 1.mp4 56.3 MB
  25 - Implementing Parallel Matrix Multiplication Part 2.mp4 26 MB
  26 - Deadlocking Robots, Philosophers and Trains.mp4 43.9 MB
  27 - Simple Deadlock Example.mp4 12.4 MB
  28 - Train Deadlock Example Part 1.mp4 10.4 MB
  29 - Train Deadlock Example Part 2.mp4 62 MB
  30 - Solving Deadlocks using Resource Hierarchy.mp4 27.6 MB
  31 - Implementing Resource Hierarchy Solution.mp4 57.3 MB
  32 - Solving Deadlocks using an Arbitrator.mp4 66.1 MB
  33 - Implementing Arbitrator Solution.mp4 32.1 MB
  34 - Barriers Explained.mp4 35 MB
  35 - Building a Barrier.mp4 21.6 MB
  36 - Barriers with Matrix Multiplication.mp4 38.4 MB
  37 - Understanding Atomic Variables.mp4 114.4 MB
  38 - Atomic Variables Example.mp4 8.3 MB
  39 - Building a Letter Frequency Program.mp4 48.5 MB
  40 - Using Atomic Variables in our Example.mp4 26.2 MB
  41 - Locking using Spinning locks.mp4 32.3 MB
  42 - Building our own Spinning locks.mp4 11.4 MB
  43 - Ledger Example.mp4 34.8 MB
  44 - Implementing the Ledger Part 1.mp4 18.9 MB
  45 - Implementing the Ledger Part 2.mp4 33.3 MB
  TutsNode.com.txt 102.4 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614.4 B
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  ▲ 91 total files

Description


Description

The mood in the meeting on the 12th floor of an international investment bank was as bleak as it gets. The developers of the firm met to discuss the best way forward after a critical core application failed and caused a system wide outage.

“Guys, we have a serious issue here. I found out that the outage was caused by a race condition in our code, introduced a while ago and triggered last night.” says Mark Adams, senior developer.

The room goes silent. The cars outside the floor to ceiling windows slowly and silently creep along in the heavy city traffic. The senior developers immediately understand the severity of the situation, realizing that they will now be working around the clock to fix the issue and sort out the mess in the datastore. The less experienced developers understand that a race condition is serious but don’t know exactly what causes it and therefore keep their mouths shut.

Eventually Brian Holmes, delivery manager, breaks the silence with “The application has been running for months without any problems, we haven’t released any code recently, how is it possible that the software just broke down?!”

Everyone shakes their heads and goes back to their desk leaving Brian in the room alone, puzzled. He takes out his phone and googles “race condition”.

Sound familiar? How many times have you heard another developer talking about using threads and concurrent programming to solve a particular problem but out of fear you stayed out of the discussion?

Here’s the little secret that senior developers will never share… Multithreading programming is not much harder than normal programming. Developers are scared of concurrent programming because they think it is an advanced topic that only highly experienced developers get to play with.

This is far from the truth. Our minds are very much used to dealing with concurrency. In fact we do this in our everyday life without any problem but somehow we struggle to translate this into our code. One of the reasons for this is that we’re not familiar with the concepts and tools available to us to manage this concurrency. This course is here to help you understand how to use multithreading tools and concepts to manage your parallel programming. It is designed to be as practical as possible. We start with some theory around parallelism and then explain how the operating system handles multiple processes and threads. Later we move on to explain the multiple tools available by solving example problems using multithreading.

In this course we use Google’s Go programming language with its goroutines, however the concepts learned here can be applied to most programming languages.

All code in this course can be found on github, username/project: cutajarj/multithreadingingo
Who this course is for:

Developers who want to take their career to the next level by improving their skills and learning about concurrent multithreading programming.
College students currently learning about parallel computing who want to see how concepts learned in class relate to practice.
Experienced developers that have recently started working with Go and want to discover the multithreading tools available.
Delivery managers called Brian Holmes.

Requirements

Some experience of programming in Go (enough if you know how to use functions, loops, arrays and a bit of pointers).
Recent version of Go installed.
Being able to do 50 push-ups while shouting a unique prime number on each rep (just kidding).

Last Updated 7/2021

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