Learn Parallel Computing in Python from Udemy

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 and Multiprocessing 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 and multiprocessing 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 concurrent programming.

In this course we use the Python language, 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/multithreadinginpython

What's inside

Learning objectives

Discover how to create responsive and high performance software.
See how to use multithreading and multiprocessing for modeling certain types of problems.
Develop programs with python that are highly concurrent and parallel.

Understand the advantages, limits and properties of parallel computing.
Improve your programming skills in python with more advanced, mulithreading and multiprocessing topics.
Learn about threads, processes, mutexes, barriers, waitgroups, queues, pipes, condition variables, deadlocks and more.

Discover how to create responsive and high performance software.
See how to use multithreading and multiprocessing for modeling certain types of problems.
Develop programs with python that are highly concurrent and parallel.
Understand the advantages, limits and properties of parallel computing.
Improve your programming skills in python with more advanced, mulithreading and multiprocessing topics.
Learn about threads, processes, mutexes, barriers, waitgroups, queues, pipes, condition variables, deadlocks and more.

Syllabus

Introduction

Understanding Parallel Computing

More on Parallel Computing

Links and Resources for this course

Creating Threads and Processes

Processes and Threads

Threads in Python and the GIL (Global Interpreter Lock)

Creating our first Thread

Processes in Python

Creating our first Processes

Memory Sharing between Threads

Memory Sharing

Letter count Implementation

Letter count using Memory Sharing

Thread Synchronization with Mutexes

Why do we need Synchronization?

Adding Mutexes to Letter Count

Adding Mutexes to Letter Count Implementation

Waiting for Completed tasks using Joins

Understanding Joins

File Search Example

Concurrent File Search

Synchronization using Condition Variables

Introduction to Condition Variables

Condition Variables for Wait Groups

Implementing Wait Groups with Condition Variables

Using Wait Groups

Barriers Explained

What’s a Barrier?

Example Barrier Application: Matrix Multiplication

Matrix Multiplication Implementation

Multi Threaded Matrix Multiplication with Barriers

Multi Threaded implementation with Barriers

Memory Sharing between Processes

How can Processes share Memory?

Using Process Memory Sharing

Process Memory Sharing in Practice

Communication using Message passing

Communication with Pipes and Queues

Examples of using Pipes and Queues

Pipelining Example

Single Process implementation

Multi Process implementation

Thread and Process Pools

Process Pool Example Part 1

Process Pool Example Part 2

Shoelace algorithm explained (optional)

Avoiding Deadlocks

Deadlocking Robots, Philosophers and Trains

Simple Deadlock Example

Train Deadlock Example Part 1

Train Deadlock Example Part 2

Solving Deadlocks using Resource Hierarchy

Implementing Resource Hierarchy Solution

Solving Deadlocks using an Arbitrator

Implementing Arbitrator Solution

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches multithreading and multiprocessing, which are essential for creating high performance software

Uses Python, which is a popular programming language used in industry

Provides practical examples and hands-on exercises

Requires students to have some experience with programming

Covers a wide range of topics, from basic concepts to advanced techniques

Taught by instructors with industry experience

Career center

Learners who complete Learn Parallel Computing in Python will develop knowledge and skills that may be useful to these careers:

Software Engineer

Software Engineers apply engineering principles to the design, development, and maintenance of software systems. They work with a variety of software development tools and technologies to create and maintain software applications. This course provides Software Engineers with the skills they need to develop more efficient and scalable software systems. By understanding how to use multithreading and multiprocessing, Software Engineers can design and implement systems that can handle a high volume of traffic and provide a better user experience.

See salaries and explore the career path for Software Engineer

Computer Scientist

Computer Scientists study the theory and practice of computation. They work with a variety of computational tools and techniques to solve problems in a wide variety of fields, including artificial intelligence, machine learning, and data science. This course provides Computer Scientists with the skills they need to develop more efficient and scalable algorithms. By understanding how to use multithreading and multiprocessing, Computer Scientists can design and implement algorithms that can run faster and more efficiently on multiple processors.

See salaries and explore the career path for Computer Scientist

Software Developer

Software Developers are responsible for analyzing user needs and designing, creating, modifying, and testing software applications. They work across industries to build and maintain software systems that meet specific business needs. This course provides a strong foundation in multithreading and multiprocessing, which are essential skills for Software Developers who want to create responsive and high-performance software. By understanding how to use these techniques, Software Developers can develop more efficient and scalable applications.

See salaries and explore the career path for Software Developer

Computer Programmer

Computer Programmers write, test, and maintain the code that makes software and applications run. They work closely with Software Developers to translate designs and specifications into functional code. This course provides Computer Programmers with the skills they need to develop concurrent and parallel programs, which can improve the performance and efficiency of software applications.

See salaries and explore the career path for Computer Programmer

Research Scientist

Research Scientists conduct research in a variety of fields, including science, engineering, and medicine. They work with a variety of tools and techniques to investigate new phenomena and develop new solutions to problems. This course provides Research Scientists with the skills they need to develop more efficient and scalable research pipelines. By understanding how to use multithreading and multiprocessing, Research Scientists can analyze data faster and more efficiently, which can lead to new discoveries and insights.

See salaries and explore the career path for Research Scientist

Computational Scientist

Computational Scientists use computers to solve scientific problems. They work with a variety of scientific models and simulations to study a wide range of phenomena, including climate change, weather forecasting, and drug discovery. This course provides Computational Scientists with the skills they need to develop more efficient and scalable scientific simulations. By understanding how to use multithreading and multiprocessing, Computational Scientists can run simulations faster and more efficiently, which can lead to better scientific insights and discoveries.

See salaries and explore the career path for Computational Scientist

Web Developer

Web Developers design, create, and maintain websites. They work with a variety of technologies to ensure that websites are functional, accessible, and visually appealing. This course provides Web Developers with the skills they need to develop more responsive and interactive websites. By understanding how to use multithreading and multiprocessing, Web Developers can create websites that can handle a high volume of traffic and provide a better user experience.

See salaries and explore the career path for Web Developer

Systems Analyst

Systems Analysts design, develop, and implement computer systems. They work with a variety of stakeholders to understand their needs and develop solutions that meet their requirements. This course provides Systems Analysts with the skills they need to develop more efficient and scalable systems. By understanding how to use multithreading and multiprocessing, Systems Analysts can design and implement systems that can handle a high volume of traffic and provide a better user experience.

See salaries and explore the career path for Systems Analyst

Network Administrator

Network Administrators design, implement, and maintain computer networks. They work with a variety of network technologies to ensure that networks are reliable, secure, and efficient. This course provides Network Administrators with the skills they need to develop more efficient and scalable networks. By understanding how to use multithreading and multiprocessing, Network Administrators can manage networks faster and more efficiently, which can lead to better performance and reliability.

See salaries and explore the career path for Network Administrator

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. They work with a variety of data sources and algorithms to create models that can solve specific business problems. This course provides Machine Learning Engineers with the skills they need to develop more efficient and scalable machine learning models. By understanding how to use multithreading and multiprocessing, Machine Learning Engineers can train models faster and more efficiently, which can lead to better results.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business Analysts help businesses understand their needs and develop solutions to improve their operations. They work with a variety of stakeholders to gather requirements, analyze data, and recommend solutions. This course provides Business Analysts with the skills they need to develop more efficient and scalable business analysis processes. By understanding how to use multithreading and multiprocessing, Business Analysts can analyze data faster and more efficiently, which can lead to better insights and decision-making.

See salaries and explore the career path for Business Analyst

Data Analyst

Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. They work with a variety of tools and techniques to identify trends and patterns in data. This course provides Data Analysts with the skills they need to develop more efficient and scalable data analysis pipelines. By understanding how to use multithreading and multiprocessing, Data Analysts can process data faster and more efficiently, which can lead to better insights and decision-making.

See salaries and explore the career path for Data Analyst

Database Administrator

Database Administrators design, implement, and maintain databases. They work with a variety of databases and technologies to ensure that data is stored, managed, and accessed efficiently. This course provides Database Administrators with the skills they need to develop more efficient and scalable database systems. By understanding how to use multithreading and multiprocessing, Database Administrators can manage data faster and more efficiently, which can lead to better performance and reliability.

See salaries and explore the career path for Database Administrator

Data Scientist

Data Scientists use data to solve business problems. They work with a variety of tools and techniques to collect, analyze, and interpret data. This course provides Data Scientists with the skills they need to develop more efficient and scalable data processing pipelines. By understanding how to use multithreading and multiprocessing, Data Scientists can process data faster and more efficiently, which can lead to better insights and decision-making.

See salaries and explore the career path for Data Scientist

Information Security Analyst

Information Security Analysts design, implement, and maintain security measures to protect computer systems and networks. They work with a variety of security technologies to ensure that systems and networks are protected from unauthorized access and cyberattacks. This course provides Information Security Analysts with the skills they need to develop more efficient and scalable security systems. By understanding how to use multithreading and multiprocessing, Information Security Analysts can analyze security data faster and more efficiently, which can lead to better detection and prevention of cyberattacks.

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Learn Parallel Computing in Python

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