We may earn an affiliate commission when you visit our partners.
Dmitri Nesteruk

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)
Read more
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

Save this course

Save High-performance Computing in C++ to your list so you can find it easily later:
Save

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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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++.
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.
Provides the definitive reference for the Message-Passing Interface (MPI) standard. It covers topics such as MPI basics, MPI communicators, and MPI collective operations.
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.
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.
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.
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.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to High-performance Computing in C++.
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser