Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster from Coursera

This is a self-paced lab that takes place in the Google Cloud console.

In this lab, you create a complete turn-key High Performance Computing (HPC) environment in Google Cloud. This environment will provide the familiar look and feel of on-prem HPC systems but with the added elasticity and scalability of Google Cloud.

In this lab you see how CloudyCluster can easily create HPC/HTC jobs that will run on-prem or in CloudyCluster on Google Cloud. You can rely on the familiar look and feel of a standard HPC environment while embracing the capabilities and elasticity of Google Cloud. The HPC jobs can be easily configured to support many instance types including GPU, preemptible, and any number of memory & CPU configurations. You will always have the latest computational technology at your fingertips.

With CloudyCluster, users can now take advantage of the GUI developed by Open OnDemand. In this lab you will be able to experience many of the Open OnDemand HPC tools. Upload and download files with a file browser-like interface. Draft job scripts with the built-in web editor. Spin-up new computing instances and have them tear down automatically after your specified work window. The current release includes JupyterLab via JupyterHub and Cloudy desktop capabilities.

As part of Google Cloud and CloudyCluster you have a vast array of storage technologies available to you. In this lab you will take advantage of High Performance Parallel Storage for job execution.

What's inside

Syllabus

Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a thorough study of High Performance Computing (HPC) in the cloud

Hands-on experience using Google Cloud console

Utilizes CloudyCluster to easily create and manage HPC/HTC jobs

Introduces Open OnDemand tools for file management, job scripting, and more

Leverages High Performance Parallel Storage for efficient job execution

Suitable for those seeking to expand their knowledge in cloud computing and HPC

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 Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster with these activities:

Review basic Linux commands

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Ensure a strong foundation by reviewing basic Linux commands that are essential for working in the cloud.

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Create a Linux virtual machine or use a Linux distribution on your local machine.
Practice navigating the file system, creating and editing files, and running basic commands.
Refer to online tutorials or documentation for specific commands and their usage.

Attend a Google Cloud or HPC Meetup

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Connect with professionals in the field of HPC and Cloud Computing by attending industry meetups.

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Find a Google Cloud or HPC Meetup in your area.
Attend the Meetup and introduce yourself to others.
Participate in discussions and learn from the experiences of others.

Create a notebook for collecting resources

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Prepare for success in the course by gathering external resources such as articles, tutorials, and code snippets.

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Set up a notebook in your preferred note-taking app.
Include sections for different topics covered in the course, such as HPC environments, job configurations, and storage technologies.
Throughout the course, add relevant resources to the notebook as you encounter them.

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Form a study group with classmates

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Enhance your understanding by collaborating with peers in a study group setting.

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Reach out to classmates and form a study group.
Establish regular meeting times and set goals for each session.
Take turns presenting concepts, solving problems, and discussing course materials.

Practice using CloudyCluster command-line tools

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Solidify your command of CloudyCluster by practicing with its command-line tools.

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Install the CloudyCluster command-line tools.
熟悉自己 with the basic commands for creating and managing HPC environments.
Try out different commands to create, start, and stop HPC jobs.
Refer to the CloudyCluster documentation for detailed instructions and examples.

Explore additional Google Cloud documentation

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Enhance your understanding of HPC and Cloud Computing by delving deeper into the official Google Cloud documentation.

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Identify specific areas or concepts that you want to learn more about.
Search for relevant documentation on the Google Cloud website.
Read through the documentation carefully, taking notes and highlighting important sections.
Try out code examples or tutorials provided in the documentation.

Configure an HPC job with specific requirements

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Apply your knowledge by creating a custom HPC job in Google Cloud, tailoring it to meet specific requirements.

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Identify the type of computation you need to perform.
Choose the appropriate instance type and configuration.
Create a job script that includes the necessary commands and instructions.
Submit the job to the Cloud and monitor its progress.

Document your learning journey with a technical blog

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Solidify your understanding by documenting your learning process and sharing your insights with others.

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Create a blog or website to share your technical learnings.
Regularly post articles about the concepts you're learning in the course.
Include code snippets, diagrams, and examples to illustrate your explanations.
Invite others to read your blog and provide feedback.

Career center

Learners who complete Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster will develop knowledge and skills that may be useful to these careers:

High Performance Computing Specialist

High Performance Computing Specialists design and implement high-performance computing solutions. They use their knowledge of high-performance computing technologies to develop solutions that meet the needs of businesses. This course can help High Performance Computing Specialists learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as high-performance computing architecture and high-performance computing programming, which are important skills for High Performance Computing Specialists.

See salaries and explore the career path for High Performance Computing Specialist

Cloud Architect

Cloud Architects design and implement cloud computing solutions. They use their knowledge of cloud computing technologies to develop solutions that meet the needs of businesses. This course can help Cloud Architects learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as cloud architecture and cloud security, which are important skills for Cloud Architects.

See salaries and explore the career path for Cloud Architect

Data Engineer

Data Engineers build and maintain the infrastructure that stores and processes data. They use their knowledge of cloud computing, databases, and big data technologies to ensure that data is available and accessible to users. This course can help Data Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as data storage and data processing, which are important skills for Data Engineers.

See salaries and explore the career path for Data Engineer

Cloud Computing Specialist

Cloud Computing Specialists design and implement cloud computing solutions. They use their knowledge of cloud computing technologies to develop solutions that meet the needs of businesses. This course can help Cloud Computing Specialists learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as cloud architecture and cloud security, which are important skills for Cloud Computing Specialists.

See salaries and explore the career path for Cloud Computing Specialist

Computer Scientist

Computer Scientists study the theory and practice of computation. They use their knowledge of mathematics, statistics, and computer science to develop new algorithms and technologies. This course can help Computer Scientists learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as parallel programming and distributed computing, which are important skills for Computer Scientists.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. They use their knowledge of mathematics, statistics, and computer science to develop algorithms that can learn from data and make predictions. This course can help Machine Learning Engineers build a foundation in cloud computing, which is essential for working with large datasets. The course also covers topics such as machine learning algorithms and model deployment, which are important skills for Machine Learning Engineers.

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Data Scientist

Data Scientists design, develop, and implement data-driven solutions to business problems. They use their knowledge of mathematics, statistics, and computer science to extract insights from data. This course can help Data Scientists build a foundation in cloud computing, which is essential for working with large datasets. The course also covers topics such as data visualization and machine learning, which are important skills for Data Scientists.

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DevOps Engineer

DevOps Engineers work to bridge the gap between development and operations teams. They use their knowledge of software development and operations to ensure that software is deployed and maintained efficiently. This course can help DevOps Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as continuous integration and continuous delivery, which are important skills for DevOps Engineers.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use their knowledge of programming languages and software development tools to create software that meets the needs of users. This course can help Software Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as software architecture and software testing, which are important skills for Software Engineers.

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IT Manager

IT Managers plan, implement, and manage information technology systems. They use their knowledge of computer systems, networks, and software to ensure that IT systems meet the needs of businesses. This course can help IT Managers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as IT strategy and IT governance, which are important skills for IT Managers.

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Security Engineer

Security Engineers design and implement security measures to protect computer systems and data. They use their knowledge of security technologies to identify and mitigate security risks. This course can help Security Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as security architecture and security monitoring, which are important skills for Security Engineers.

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Network Engineer

Network Engineers design, build, and maintain computer networks. They use their knowledge of networking technologies to ensure that networks are reliable and efficient. This course can help Network Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as network design and network security, which are important skills for Network Engineers.

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Systems Engineer

Systems Engineers design, build, and maintain computer systems. They use their knowledge of hardware, software, and networking to ensure that systems are reliable and efficient. This course can help Systems Engineers learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as system administration and system monitoring, which are important skills for Systems Engineers.

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Database Administrator

Database Administrators design, build, and maintain databases. They use their knowledge of database technologies to ensure that databases are reliable and efficient. This course can help Database Administrators learn how to create and manage a high-performance computing environment in Google Cloud. The course also covers topics such as database design and database optimization, which are important skills for Database Administrators.

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Data Analyst

Data Analysts collect, clean, and analyze data to extract insights. They use their knowledge of mathematics, statistics, and computer science to identify trends and patterns in data. This course can help Data Analysts learn how to use cloud computing to store and process large datasets. The course also covers topics such as data visualization and data mining, which are important skills for Data Analysts.

See salaries and explore the career path for Data Analyst