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High-performance Computing in C++

Dmitri Nesteruk

A course on topics related to high-performance computation. Covers SIMD, OpenMP, C++ AMP, and MPI.

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A course on topics related to high-performance computation. Covers SIMD, OpenMP, C++ AMP, and MPI.

Do you want to get the absolute most performance out of your hardware? Want to write code that scales across CPU registers, multi-core, and machine clusters? Then this is the course for you!

Enroll now

What's inside

Syllabus

Single Instruction Multiple Data (SIMD)
Open Multi-Processing (OpenMP)
Message Passing Interface (MPI)
C++ Accelerated Massive Parallelism (C++ AMP)
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Generative Art Demo

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational knowledge in high-performance computation, a field that is fundamental to various fields in engineering, science, and big data
Provides hands-on experience with industry-standard tools and technologies, including SIMD, OpenMP, C++ AMP, and MPI
Taught by Dmitri Nesteruk, a recognized expert in the field of high-performance computing
Covers the latest advancements and trends in high-performance computing, making it relevant to industry needs
May be suitable for individuals with a background in computer science or engineering, as it requires some familiarity with programming concepts
Students may need to invest in additional resources, such as a high-performance computing environment, to fully benefit from the course

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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 High-performance Computing in C++ with these activities:
Review basic linear algebra
Linear algebra is a recurring theme throughout this course. Reviewing basic concepts will help you follow along during class and speed up your progress.
Browse courses on Matrices
Show steps
  • Review matrix operations such as addition, multiplication and inverses.
  • Brush up on concepts such as eigenvalues and eigenvectors.
  • Solve a few practice problems to test your understanding.
Create a cheat sheet of important formulas and concepts
Creating a cheat sheet is a great way to organize your notes and quickly reference important information during class and while studying.
Browse courses on Formulas
Show steps
  • Go through your notes and identify the most important formulas and concepts.
  • Create a cheat sheet that is well-organized and easy to read.
  • Review your cheat sheet regularly to reinforce your understanding.
Watch tutorials on YouTube to learn about C++ AMP
C++ AMP is a powerful tool for parallel programming. Watching tutorials will help you get started with C++ AMP and learn how to use it effectively.
Show steps
  • Search for tutorials on YouTube that cover C++ AMP.
  • Watch a few tutorials to get an overview of C++ AMP.
  • Follow along with the tutorials and try out the examples.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve coding challenges on LeetCode
Solving coding challenges is a great way to improve your problem-solving skills and reinforce the concepts you learn in class.
Browse courses on Data Structures
Show steps
  • Pick a topic you want to focus on, such as arrays or linked lists.
  • Solve a few easy problems to get started.
  • Gradually increase the difficulty of the problems you solve.
Write a blog post about a topic you learned in class
Writing a blog post is a great way to solidify your understanding of a topic and share your knowledge with others.
Browse courses on High-Performance Computing
Show steps
  • Choose a topic that you are interested in and that you think others would find helpful.
  • Do some research on the topic to gather information and insights.
  • Write a blog post that is well-organized, informative, and engaging.
Mentor a junior student in the same course
Mentoring a junior student is a great way to reinforce your understanding of the material and help others succeed.
Browse courses on Mentoring
Show steps
  • Identify a junior student who is struggling with the material.
  • Offer your help and support.
  • Meet with the student regularly to go over the material and answer their questions.
Participate in a hackathon or coding competition
Participating in a hackathon or coding competition is a great way to test your skills, learn from others, and build something cool.
Browse courses on High-Performance Computing
Show steps
  • Find a hackathon or coding competition that you are interested in.
  • Team up with others or work on your own.
  • Come up with an idea for a project.
  • Build your project and submit it.

Career center

Learners who complete High-performance Computing in C++ will develop knowledge and skills that may be useful to these careers:
Parallel Programming Engineer
Parallel Programming Engineers design, develop, and implement parallel software applications. They work on a variety of tasks, including thread synchronization, load balancing, and performance optimization. This course is a perfect fit for Parallel Programming Engineers who want to learn more about the latest high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all essential for the development of high-performance parallel software applications.
See salaries and explore the career path for Parallel Programming Engineer
High-Performance Computing Engineer
High Performance Computing Engineers design, develop, and maintain high-performance computing systems. They work on a variety of tasks, including hardware selection, software optimization, and performance analysis. This course is a perfect fit for High Performance Computing Engineers who want to learn more about the latest high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all essential for the development of high-performance computing systems.
See salaries and explore the career path for High-Performance Computing Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work on a variety of tasks, including requirements gathering, system design, and code implementation. This course may be useful for Software Engineers who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance software systems.
See salaries and explore the career path for Software Engineer
Computer Scientist
Computer Scientists conduct research on the theory and practice of computation. They develop new algorithms and data structures, and study the complexity and efficiency of computational problems. This course may be useful for Computer Scientists who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance computing applications.
See salaries and explore the career path for Computer Scientist
Software Developer
Software Developers design, develop, and maintain software applications. They work on a variety of tasks, including requirements gathering, system design, and code implementation. This course may be useful for Software Developers who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance software applications.
See salaries and explore the career path for Software Developer
Systems Analyst
Systems Analysts design and implement computer systems. They work on a variety of tasks, including requirements gathering, system design, and code implementation. This course may be useful for Systems Analysts who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the design and implementation of high-performance computing systems.
See salaries and explore the career path for Systems Analyst
Software Architect
Software Architects design and develop software systems. They work on a variety of tasks, including requirements gathering, system design, and code implementation. This course may be useful for Software Architects who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance software systems.
See salaries and explore the career path for Software Architect
Research Scientist
Research Scientists conduct research in a variety of scientific fields. They design and conduct experiments, analyze data, and develop new theories. This course may be useful for Research Scientists who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance computing applications.
See salaries and explore the career path for Research Scientist
Technical Lead
Technical Leads lead teams of software developers and engineers. They work on a variety of tasks, including project planning, team management, and technical guidance. This course may be useful for Technical Leads who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance software systems.
See salaries and explore the career path for Technical Lead
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful for Data Scientists who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance data science applications.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning systems. They work on a variety of tasks, including data collection, feature engineering, model training, and model evaluation. This course may be useful for Machine Learning Engineers who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance machine learning applications.
See salaries and explore the career path for Machine Learning Engineer
Quantum Computing Engineer
Quantum Computing Engineers design, develop, and maintain quantum computing systems. They work on a variety of tasks, including hardware design, software development, and algorithm optimization. This course may be useful for Quantum Computing Engineers who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the development of high-performance quantum computing systems.
See salaries and explore the career path for Quantum Computing Engineer
Computer Hardware Engineer
Computer Hardware Engineers design, develop, test, and evaluate computer hardware systems. They may also work on the integration of hardware and software systems. This course may be useful for Computer Hardware Engineers who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the design and development of high-performance computer systems.
See salaries and explore the career path for Computer Hardware Engineer
Performance Analyst
Performance Analysts evaluate the performance of computer systems and applications. They identify bottlenecks and recommend improvements. This course may be useful for Performance Analysts who want to learn more about high-performance computing techniques. The course covers topics such as SIMD, OpenMP, C++ AMP, and MPI, which are all relevant to the analysis of high-performance computing systems.
See salaries and explore the career path for Performance Analyst

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in High-performance Computing in C++.
Cover image
Programming Massively Parallel Processors
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Provides a practical guide to programming massively parallel processors, focusing on C++ as the programming language. It covers topics such as SIMD programming, OpenMP programming, and MPI programming.
Programming Massively Parallel Processors: A Hands...
Paperback
$$$
Cover image
Using MPI-2
Save
Provides the definitive reference for the Message-Passing Interface (MPI) standard. It covers topics such as MPI basics, MPI communicators, and MPI collective operations.
Using MPI-2: Advanced Features of the Message...
Paperback
$$$
Using MPI-2: Advanced Features of the Message...
Paperback
$$$$
Cover image
Computer Architecture
Save
Provides a comprehensive overview of computer architecture, covering topics such as processor design, memory organization, and I/O systems. It valuable resource for understanding the underlying hardware that supports high performance computing.
Computer Architecture: A Quantitative Approach (The...
Paperback
$$$
Computer Organization and Design MIPS Edition: The...
Paperback
$$$
Computer Organization and Design RISC-V Edition:...
Paperback
$$$
Computer Architecture: A Quantitative Approach...
Kindle Edition
$$$
Computer Organization and Design ARM Edition: The...
Paperback
$$$
Computer Organization and Design MIPS Edition: The...
Paperback
$$$$
Computer Organization and Design, Third Edition:...
Kindle Edition
$
Computer Architecture: A Quantitative Approach, 3rd...
Hardcover
$$
Computer Organization and Design RISC-V Edition:...
Paperback
$$$$
Computer Organization and Design: The...
Paperback
$$$
Cover image
Modern Operating Systems, Global Edition
Save
Provides a comprehensive overview of operating systems, covering topics such as process management, memory management, and file systems. It valuable resource for understanding the software that manages the hardware resources used by high performance computing applications.
Modern Operating Systems, Global Edition
Paperback
Check
Modern Operating Systems, Global Edition
Kindle Edition
Check
Cover image
Numerical Recipes in C++
Save
Provides a comprehensive collection of numerical recipes and algorithms for scientific computing. It valuable resource for implementing high performance computing applications that require complex mathematical calculations.
Numerical Recipes in C++
Paperback
Check
Numerical Recipes in C++
Kindle Edition
Check
Cover image
High Performance Parallel Runtimes
Save
Provides a practical guide to parallel programming in C++ using MPI and OpenMP. It covers topics such as parallel programming models, performance optimization, and debugging.
High Performance Parallel Runtimes: Design and...
Perfect Paperback
$$$
High Performance Parallel Runtimes: Design and...
Kindle Edition
$$$
CUDA Programming
Save
Provides a practical guide to CUDA programming, focusing on developing parallel applications for GPUs. It covers topics such as CUDA basics, CUDA programming model, and CUDA performance optimization.
CUDA Programming: A Developer's Guide to Parallel...
Paperback
$$
CUDA Programming: A Developers Guide to Parallel...
Paperback
$$
CUDA Programming: A Developer's Guide to Parallel...
Kindle Edition
$$

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Course image
Time
243 hours
Level
Advanced
Via
Pluralsight
Instructor
Dmitri Nesteruk
Language
English
This course belongs to a collection called C++. It's comprised of 17 courses:
  1. C++ Fundamentals Including C++ 17
  2. Practical C++14 and C++17 Features
  3. C++ Unit Testing Fundamentals Using Catch2
  4. Introduction to Data Structures and Algorithms in C++
  5. Beautiful C++: Updating Legacy Code
  6. Beautiful C++: STL Algorithms
  7. Design Patterns in C++: Creational
  8. Design Patterns in C++: Structural - Adapter to Decorator
  9. Design Patterns in C++: Structural - Façade to Proxy
  10. Learn How to Program with C++
  11. Modern C++ Concurrency
  12. High-performance Computing in C++ (viewing)
  13. C++ Standard Library: Sequential Containers
  14. Advanced C++ Mocking Using Google Mock 1
  15. C++ 17: Beyond the Basics
  16. Reading Legacy C++
  17. C++ Standard Library: Associative Containers
Good to know
Develops foundational knowledge in high-performance computation, a field that is fundamental to various fields in engineering, science, and big data
Provides hands-on experience with industry-standard tools and technologies, including SIMD, OpenMP, C++ AMP, and MPI
Taught by Dmitri Nesteruk, a recognized expert in the field of high-performance computing
Covers the latest advancements and trends in high-performance computing, making it relevant to industry needs
May be suitable for individuals with a background in computer science or engineering, as it requires some familiarity with programming concepts
Students may need to invest in additional resources, such as a high-performance computing environment, to fully benefit from the course
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