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Introduction to High-Performance and Parallel Computing

Master the fundamentals of HPC systems, parallel programming, and distributed computing for scientific applications.

Master the fundamentals of HPC systems, parallel programming, and distributed computing for scientific applications.

This comprehensive course introduces the essentials of high-performance and parallel computing for scientists, engineers, and researchers. Students learn to navigate Linux-based HPC environments, understand distributed computing systems, and develop parallel programming skills. The curriculum covers fundamental concepts from basic Linux commands to advanced topics in parallel efficiency and scalability. Participants gain practical experience with job submission, resource management, and performance optimization techniques.

3.5

(118 ratings)

16,345 already enrolled

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Introduction to High-Performance and Parallel Computing

This course includes

14 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

6,634

Audit For Free

What you'll learn

  • Navigate Linux-based HPC environments effectively

  • Understand distributed computing system components

  • Master parallel programming concepts and models

  • Conduct performance analysis and scaling studies

  • Develop skills in HPC job submission and management

Skills you'll gain

SLURM
scripting
speedup
computing
Linux
parallel programming
HPC systems
distributed computing
performance optimization
resource management

This course includes:

121 Minutes PreRecorded video

4 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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There are 4 modules in this course

This course provides a comprehensive introduction to high-performance and parallel computing fundamentals. Students learn to navigate Linux-based HPC environments and understand the components of distributed computing systems. The curriculum covers essential topics including basic Linux commands, bash scripting, job submission with SLURM, parallel programming models, and performance optimization. Through hands-on assignments and practical exercises, participants learn to assess application scalability, conduct scaling studies, and optimize computational workflows.

High-Performance Computing (HPC) for Non-Computer Scientists

Module 1 · 4 Hours to complete

Nuts and Bolts of HPC

Module 2 · 2 Hours to complete

Basic Parallelism

Module 3 · 3 Hours to complete

Evaluating Parallel Program Performance

Module 4 · 2 Hours to complete

Fee Structure

Payment options

Financial Aid

Instructors

Shelley Knuth
Shelley Knuth

4.2 rating

45 Reviews

16,229 Students

1 Course

Advocate for Research Computing and Data Management

Shelley Knuth serves as the Associate Director of User Services in the Research Computing group at the University of Colorado Boulder, where she plays a pivotal role in enhancing the user experience for researchers. Her responsibilities include leading support initiatives that help scientists optimize their research through effective data management practices. In addition to her primary role, she is the Director of Education and Training at the Center for Research Data and Digital Scholarship (CRDDS), a collaborative effort with CU Libraries aimed at improving research capabilities across disciplines. Dr. Knuth earned her Ph.D. in Atmospheric and Oceanic Sciences in Spring 2014, which complements her expertise in research computing. Her work is instrumental in facilitating high-performance computing resources, such as the Alpine supercomputer, to advance scientific research and innovation within the university community.

Thomas Hauser
Thomas Hauser

4.2 rating

45 Reviews

16,229 Students

1 Course

Leader in Research Computing and Cyberinfrastructure

Dr. Thomas Hauser is the Director of Research Computing at the University of Colorado Boulder, where he oversees the operation of a supercomputer, research data storage services, and a network designed for efficient large data transfers. His team provides essential training and consulting in computational science, engineering, and data management to researchers and students at CU Boulder. In addition to his role in research computing, Dr. Hauser serves as one of the executive directors of the Center for Research Data and Digital Scholarship and chairs the Rocky Mountain Advanced Computing Consortium (RMACC), which fosters collaboration on cyberinfrastructure projects across the Rocky Mountain region. Notably, he played a key role in the development of the RMACC Summit supercomputer, a partnership between CU Boulder and Colorado State University that allocates compute cycles to member institutions. Dr. Hauser's extensive background includes previous leadership positions at Utah State University and Northwestern University, along with a Ph.D. in mechanical engineering specializing in computational fluid dynamics from the University of Technology in Munich, Germany. His work is characterized by a commitment to advancing research capabilities through innovative computing solutions and collaborative initiatives that support scientific inquiry across disciplines.

Introduction to High-Performance and Parallel Computing

This course includes

14 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

6,634

Audit For Free

Testimonials

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3.5 course rating

118 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.