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As part of Harvard Medical School's response to COVID-19, HMS Research Computing is now working remotely. All training classes will be held online until further notice, via Zoom meetings. |
Registrations are now managed through the Harvard Training Portal, which requires a Harvard ID (HUID). Those members of the extensive HMS community who do not currently have HUIDs - such as employees at affiliate hospitals, or collaborators from other institutions - may self-register for one as a "Person of Interest" with their faculty member's sponsorship. This form may take several days to process, and is available here:
https://iam.harvard.edu/files/iam/files/sponsored-identity-request-form_v1.pdf
Fall 2021 (Part 1) Registration will open!
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Current Training Schedule: Spring 2024
Info |
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Please note the location for your selected class. We are offering both in-person and virtual classes this year. Important note: for virtual classes, you should receive an confirmation email from the Harvard Training Portal with a Zoom link. If you do not have your email address on file in the Training Portal, such messages cannot be |
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sent to you. Please contact us for the Zoom meeting details if you |
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do not get a confirmation email. |
Class | Date | Time | Location |
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Training Materials | Registration |
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Intro to O2 | Wednesday, |
4-5pm
Virtual
35
February 21, 2024 | 10am to 12pm | In-person |
O2 Portal - Simplifying the Interaction and Experience of Using an HPC Environment | Wednesday, |
March 6, |
2024 | 10am to 12pm | Virtual |
Intro to |
MATLAB | Wednesday, |
March 13, |
3-5pm
Virtual
50
RCBio: easy and quick HPC pipeline builder & runner
Wednesday, September 29, 2021
3-5pm
Virtual
35
2024 | 10am to 12pm | In-person |
Intro to Parallel Computing | Wednesday, |
3-5pm
Virtual
March 20, 2024 | 10am to 12pm | In-person |
Optimizing O2 Jobs | Wednesday, |
3-5pm
Virtual
April 3, 2024 | 10am to 12pm | In-person |
Intro to |
Python | Wednesday, |
3-5pm
Virtual
April 10, 2024 | 10am to 12pm | In-person |
Troubleshooting O2 Jobs | Wednesday, |
April 24, |
2024 | 10am to 12pm | Virtual |
Intro to |
O2 | Wednesday, |
May 1, |
2024 | 10am to 12pm | Virtual |
Medical Image Processing and Machine Learning Workflow (Taught by Mathworks) | Wednesday, |
3-5pm
Virtual
35
Intermediate O2
Wednesday, November 17, 2021
3-5pm
Virtual
35
No class
Wednesday, November 24, 2021
Intro to R/Bioconductor
Wednesday, December 1, 2021
3-5pm
Virtual
35
Introduction to Globus Data Transfer and Data Collaboration on O2
Wednesday, December 8, 2021
3-5pm
Virtual
35
RCBio: easy and quick HPC pipeline builder & runner
RCBio is a HPC pipeline runner and workflow tool supported by HMS RC consultants. It was first designed for a Neubiology lab and later opened to all O2 users. RCBio helps users to quickly build and run multiple steps data analysis pipeline on a computer cluster. RCBio automatically keeps logs on all job status and use email to notify user. When re-run the same pipeline, RCBio automatically submit failed jobs and ask user if she/he want to re-run the successful jobs. Here is our wiki page about the RCBio project: RC workflows
BioGrids Academic Software Platform: No Installation Required
Academic Software Platform (ASP) integrates two major stacks of scientific software: BioGrids stack of ~400 biomedical applications (https://biogrids.org/software/) as well as SBGrid stack of ~500 structural biology applications. Multiple versions of applications are maintained, and users can also easily install the same stack of software on laptops, research workstations or cloud resources, under Linux or Mac OS X operating systems. More information about this resource is available on O2 wiki: https://harvardmed.atlassian.net/wiki/spaces/O2/pages/1630994700/Using+Software+Provided+by+BioGrids
Intro to O2
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May 15, 2024 | 10am to 12pm | In-person | |||
RCBio: easy and quick HPC pipeline builder & runner | Wednesday, May 22, 2024 | 10am to 12pm | Virtual |
Additional classes will be added for the Summer semester.
Class Registration Process
Registrations are managed through the Harvard Training Portal, which requires a Harvard ID (HUID). Those members of the extensive HMS community who do not currently have HUIDs - such as employees at affiliate hospitals, or collaborators from other institutions - may self-register for one as a "Harvard Sponsored Role” with their faculty member's sponsorship. This form may take several days to process, please visit this page for details: https://it.hms.harvard.edu/our-services/accounts-and-user-access/person-interest-poi
Class Descriptions
Classes taught by HMS Research Computing Staff:
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Intermediate O2 is for current O2 users who would like to brush up on their bash skills, learn more advanced file transfer techniques, and unleash some of the powerful features of the SLURM scheduler. |
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This course introduces Git and GitHub and covers topics including: Getting Started with Git for version control, Using GitHub Desktop effectively, Collaborating with others on GitHub, and Utilizing GitHub Flow for better workflow. No previous exposure is assumed. We hope attendees will leave the class with the knowledge and tools necessary to start integrating Git into their workflows and excited to begin collaborating on GitHub. |
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Matlab has become the “language of science” in the past few decades. It is simple to use, yet powerful enough to be productive on large computing infrastructures. If you need: 1) Fast prototyping of research ideas; or 2) avoid spending too much time in coding instead of doing real science by taking advantage of Matlab’s built-in functions; 3) User friendly graphical interface and educational documentation; 4) Simplicity of code; 5) Easy access to GPU computing power; 6) Easy plotting and presentation of data; you will find this introduction course useful. This course will introduce the basics of the MATLAB coding language with O2-scalability and data presentation. |
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Intro to O2 addresses the needs of users who have very little linux experience, and are just getting started with |
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the O2 high performance compute cluster. We will cover linux basics, and the |
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concept of |
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the Slurm scheduler and jobs, |
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as well as data management best practices. |
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This is a short introduction to Parallel Computing that will include an overview of the basic concepts of parallel programming: from running your job in an embarrassingly parallel way to writing simple shared and distributed memory parallelization codes in different languages. The seminar will cover several examples of actual parallel codes however it will not have any "hands on" components. A basic programming experience (of any language, no parallelization) is preferred in order to better follow the topics presented during the seminar. |
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Python is a popular scripting language for scientific computing and available across all computer platforms. The course will introduce you to some of the basics of the Python language as well as some of the nuances involved with its use specific to the O2 environment. The goal is to provide users with a foundational level of familiarity. Topics covered include basic data types and declaration, flow control (if/else), loops, a brief introduction to constructing a script, and a briefer introduction to modules. The course will be taught on O2, but general concepts are easily translatable to desktop and local installations. |
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Intro to using R and Bioconductor. R is a powerful, open-source, highly adaptable statistical language useful for crunching numbers to datasets like those produced by next-gen sequencing. This class covers R basics and learning to think like/understand R. Users will learn how to set up personal R libraries on O2, and use O2 R for its high memory allocations and parallelization. Topics include how to install packages, learn about variables, data types. data manipulation, flow control, and functions, perform simple statistical tests, and create a variety of plots. Laptops are encouraged. |
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Intro to MATLAB
Matlab has become the “language of science” in the past few decades. It is simple to use, yet powerful enough to be productive on large computing infrastructures. If you need: 1) Fast prototyping of research ideas; or 2) avoid spending too much time in coding instead of doing real science by taking advantage of Matlab’s built-in functions; 3) User friendly graphical interface and educational documentation; 4) Simplicity of code; 5) Easy access to GPU computing power; 6) Easy plotting and presentation of data; you will find this introduction course useful. This course will introduce the basics of the MATLAB coding language with O2-scalability and data presentation.
Intro to Parallel Computing
This is a short introduction to Parallel Computing that will include an overview of the basic concepts of parallel programming: from running your job in an embarrassingly parallel way to writing simple shared and distributed memory parallelization codes in different languages. The seminar will cover several examples of actual parallel codes however it will not have any "hands on" components. A basic programming experience (of any language, no parallelization) is preferred in order to better follow the topics presented during the seminar.
Intermediate O2
Intermediate O2 is for current O2 users who would like to brush up on their bash skills, learn more advanced file transfer techniques, and unleash some of the powerful features of the SLURM scheduler.
Intro to Git and GitHub
This course introduces Git and GitHub and covers topics including: Getting Started with Git for version control, Using GitHub Desktop effectively, Collaborating with others on GitHub, and Utilizing GitHub Flow for better workflow. No previous exposure is assumed. We hope attendees will leave the class with the knowledge and tools necessary to start integrating Git into their workflows and excited to begin collaborating on GitHub.
Introduction to Globus Data Transfer and Data Collaboration on O2
This course is designed to showcase the Globus specific data transfer and sharing functionality that is available to anyone with o2 access. We will be going over not only how to share data with collaborators outside of HMS, but also how to receive data from outside collaborators. The class will delve into the Globus features that are available via the Globus website at first and eventually transition into the functionality provided by the globus cli.
Additional computational trainings are available through other groups:
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Training from the Harvard Chan Bioinformatics Core
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This course is designed to showcase the Globus specific data transfer and sharing functionality that is available to anyone with o2 access. We will be going over not only how to share data with collaborators outside of HMS, but also how to receive data from outside collaborators. The class will delve into the Globus features that are available via the Globus website at first and eventually transition into the functionality provided by the globus cli. |
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Description: |
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Description: |
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RCBio is a HPC pipeline runner and workflow tool supported by HMS RC consultants. It was first designed for a Neubiology lab and later opened to all O2 users. RCBio helps users to quickly build and run multiple steps data analysis pipeline on a computer cluster. RCBio automatically keeps logs on all job status and use email to notify user. When re-run the same pipeline, RCBio automatically submit failed jobs and ask user if she/he want to re-run the successful jobs. Here is our wiki page about the RCBio project: RC workflows |
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The “Troubleshooting O2 Jobs” class will teach you how to debug problems when running analyses on the O2 High Performance Compute Cluster. We will examine faulty job submissions to give you hands-on problem solving experience. You will learn how to request appropriate resources and set up your environment to successfully execute your jobs. Prerequisites: We recommend taking the “Intro to O2” class prior to “Troubleshooting O2 Jobs”. |
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Description: During this short training seminar, we will discuss:
Audience: Primarily focused on HMS related tools and materials. Open to members of the Longwood Medical Area community, including researchers, faculty and staff. Prerequisites: None |
Classes sponsored by HMS Research Computing but taught by our partner organizations:
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Overview Medical images are obtained from various sources including MRI, CT, X-ray, ultrasound, and PET scans. Analyzing these images necessitates a comprehensive environment for data access, visualization, processing, and algorithm development. A key challenge involves extracting quantitative features to generate clinically relevant information using advanced techniques like machine learning algorithms. This presentation will explore radiomics, which captures characteristics not typically visible. Radiomics features can be employed across various medical imaging modalities and applications, enabling the study of associations between imaging features and patient biology, as well as the prediction of clinical outcomes, making radiomics a versatile technique in medical imaging. These features quantify shape, intensity, and texture characteristics within medical images, reducing reliance on subjective interpretation for clinical workflows. Highlights In this session, you will learn how to:
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Academic Software Platform (ASP) integrates two major stacks of scientific software: BioGrids stack of ~400 biomedical applications (https://biogrids.org/software/) as well as SBGrid stack of ~500 structural biology applications. Multiple versions of applications are maintained, and users can also easily install the same stack of software on laptops, research workstations or cloud resources, under Linux or Mac OS X operating systems. More information about this resource is available on O2 wiki: https://harvardmed.atlassian.net/wiki/spaces/O2/pages/1630994700/Using+Software+Provided+by+BioGrids |
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Overview: During this hands-on workshop, you will be introduced to parallel and GPU computing in MATLAB for speeding up your applications and offloading computations. By working through common scenarios and workflows, you will gain an understanding of the parallel constructs in MATLAB, their capabilities, and some of the issues that may arise when using them. Highlights:
Requirements:
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MATLAB Parallel Server™ lets you scale MATLAB® programs and Simulink® simulations to clusters and clouds. This two-part, hands-on workshop is designed to introduce users to parallel computing constructs in MATLAB and to show them how they can scale their jobs to the HPC clusters on campus.
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Additional computational trainings available through other groups
Please reach out directly to the above groups if you are interested in attending their trainings.
Contact us
Please reach out to HMS Research Computing at rchelp@hms.harvard.edu with any questions about training. We are here to assist if you are having difficulty registering for a class, or if you are wondering when a topic will be offered next!