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High Performance Computing

High Performance Computing (HPC), or as it's sometimes referred to, High-Performance Technical Computing, generally falls under the umbrella of Computer Science. HPC focuses on the study and design of powerful computers, clusters, and other advanced computation tools. HPC focuses on creating computing systems that meet the needs of computationally intensive scientific simulation. HPC is used in a variety of fields such as finance, aerospace, energy, and pharmaceutical research, to support computationally demanding research and modeling.

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High Performance Computing (HPC), or as it's sometimes referred to, High-Performance Technical Computing, generally falls under the umbrella of Computer Science. HPC focuses on the study and design of powerful computers, clusters, and other advanced computation tools. HPC focuses on creating computing systems that meet the needs of computationally intensive scientific simulation. HPC is used in a variety of fields such as finance, aerospace, energy, and pharmaceutical research, to support computationally demanding research and modeling.

Types of High Performance Computing

Within the broad umbrella of HPC, there exist a variety of different types:

  • Cluster Computing: Thousands of individual servers are merged together to form one large computing unit. This means that clusters can have tens of thousands of processors working towards a single computational goal.
  • Blade Servers: These servers are specifically designed to be as energy-efficient as possible and are very densely packed within a chassis. Systems with 200 nodes are not uncommon.
  • Grid Computing: Grid computing is a type of distributed computing that has access to resources from several different sites and makes them into one computing unit.
  • Cloud Computing: Cloud computing focuses on providing computing power via the internet, making massive computation power available to anyone with an internet connection.
  • Hybrid Computing: Hybrid computing combines the power of on-premises IT systems with public cloud services through a unified platform to provide greater flexibility and agility.

Due to the fast growth of data, including structured, unstructured, and big data, the demand for qualified professionals in the field of HPC is on the rise. These professionals work on projects that involve a wide range of scientific computational and engineering applications, commonly including: weather forecasting, climate, aerospace engineering, computational finance, oil and gas exploration, medical research, automotive engineering, molecular modeling, and cryptology.

Getting Started with High Performance Computing

There are many different ways to learn about High Performance Computing. Some people choose to self-study, while others enroll in online courses or degree programs. There are many different online courses available that can teach you the basics of HPC. These courses can help you learn about the different types of HPC, how to use HPC software, and how to design and implement HPC systems.

Online courses can be a great way to learn about High Performance Computing. They offer a flexible and affordable way to learn at your own pace. Many online courses also offer interactive labs and projects that can help you apply what you learn. However, it is important to note that online courses alone may not be enough to fully understand this topic. They can be a helpful learning tool, but they should be supplemented with other resources, such as books, articles, and hands-on experience.

Careers in High Performance Computing

There are a variety of different careers available in the field of High Performance Computing. Some of the most common careers include:

  • HPC Engineer: Designs, implements, and maintains HPC systems.
  • HPC Scientist: Uses HPC systems to conduct scientific research.
  • HPC Consultant: Provides advice and guidance to organizations on how to use HPC.
  • HPC Educator: Teaches courses on HPC.
  • HPC Writer: Writes articles, books, and other materials about HPC.

The field of High Performance Computing is constantly evolving, and new developments are being made all the time. This makes it an exciting and challenging field to work in. If you are interested in a career in HPC, there are many different resources available to help you get started.

Personality Traits and Personal Interests of an HPC Professional

There are likely many different traits and interests that could fit well with someone wanting to study High Performance Computing. Some of these could include:

  • A strong interest in mathematics and science
  • A strong work ethic
  • The ability to think critically and solve problems
  • The ability to work independently and as part of a team
  • The ability to communicate effectively

Benefits of Learning High Performance Computing

There are many benefits to learning about High Performance Computing. Some of the benefits include:

  • Increased job opportunities: The demand for qualified HPC professionals is on the rise.
  • Higher salaries: HPC professionals earn higher salaries than the average computer scientist.
  • More challenging and rewarding work: HPC professionals work on projects that are at the cutting edge of science and engineering.
  • Greater job security: The HPC field is growing rapidly, so there is a high demand for qualified professionals.

If you are interested in a career in High Performance Computing, there are many different resources available to help you get started. You can find online courses, degree programs, and books that can teach you the basics of HPC. You can also find online communities and forums where you can connect with other HPC professionals and learn from their experiences.

Path to High Performance Computing

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We've curated eight courses to help you on your path to High Performance Computing. Use these to develop your skills, build background knowledge, and put what you learn to practice.
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Reading list

We've selected ten 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.
Provides a comprehensive overview of the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides a comprehensive overview of the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides a comprehensive overview of the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides a comprehensive overview of the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields. This book is suitable for students and researchers in the field of high performance computing.
Provides a comprehensive overview of the field of parallel computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields. This book is suitable for students and researchers in the field of high performance computing.
Provides a comprehensive overview of the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides a practical introduction to the field of high performance computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides an introduction to the field of high performance scientific computing. It covers a wide range of topics, including parallel programming, performance optimization, and applications in various fields.
Provides an introduction to the topic of high performance computing. It covers the basics of parallel computing, as well as more advanced topics such as performance optimization and programming models. This book is suitable for students and researchers in the field of high performance computing.
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