IS&T RCS Summer 2026 Trainings

May 26 – June 23, 2026

Registration is open for the RCS Summer 2026 Tutorials. Please also be aware that we have lots of recordings and slides available from past tutorials by RCS staff and vendors.

Note that we switched in Fall 2024 to using a new registration system, Terrier eDevelopment, that will send calendar invites to attendees, supports a waiting list, and has various other new features. For those who have taken our tutorials earlier, the new registration process is quite different. Follow the process outlined here to register for tutorials.

  1. Go to the tutorial you want to register for by clicking on its name or just scrolling down on this page.
  2. Click the appropriate green ‘Register for this session’ link.
  3. This will take you to a page on Terrier eDevelopment. Click the blue ‘Register’ button which will take you to another page on Terrier eDevelopment.
  4. Click the blue ‘Add’ button and then click the blue ‘Register’ button on the bottom right of that same page.
  5. If you wish to register for additional tutorials, return to this page and follow the same process for each.
  • For hands-on sessions where you wish to use your own computer, please have the appropriate software installed on your computer before the session starts.
  • Tutorials are tagged based on experience required (Beginner, Intermediate, or Advanced), location (details below), and if they are new.
  • Tutorial sessions are held either in-person or over Zoom. Note that Zoom sessions will be recorded; keep your camera off if you do not want your image recorded. The recorded sessions may be made available to the BU community.

The IS&T Research Computing Services (RCS) group offers a tutorial series on programming, data analysis, high performance computing, and domain specific topics three times each year. These tutorials are free and open to all members of the Boston University community.

The RCS tutorials cover concepts, techniques, and tools which researchers can use in their own computing environments. Many are designed to help you make effective use of the Boston University Shared Computing Cluster (SCC). The RCS staff can also deliver extra, or customized, tutorial sessions to your course, group, or lab. Please contact us at help@scc.bu.edu if you are interested.

Trainings Schedule

You may register for as many tutorials as you like. Registration is required and is accessed with your BU Kerberos password.

If you don’t have a Kerberos password, or if you find that a tutorial is full, or have any other questions, please send email to rcs-tutorial@bu.edu.

Tutorial Locations

BSC Biological Science Center, 2 Cummington Mall, Room 107
Zoom Online over Zoom After you register, you will be sent a calendar invite that includes the Zoom link.

Tutorial Descriptions and Times

Research Computing Basics Tutorials

BeginnerIntroduction to Linux (Hands-on)

Instructor: Augustine Abaris (augustin@bu.edu)

BSCTuesday May 26, 2026 10:00am - 12:00pm
This tutorial will give attendees a hands-on introduction to Linux. Topics covered will include a short history of Linux, logging in with ssh, the Bash shell and shell scripts, I/O redirection (pipes), file system navigation, and job control. Time permitting, attendees will edit, compile, and run a simple C program. If you have not connected to the SCC from your laptop before, please read and follow these instructions prior to attending the tutorial.

BeginnerIntroduction to BU's Shared Computing Cluster (Hands-on)

Instructor: Aaron Fuegi (aarondf@bu.edu)

ZoomTuesday May 26, 2026 12:30pm - 2:30pm
This tutorial will introduce Boston University's Shared Computing Cluster (SCC) in Holyoke, MA. This Linux cluster has more than 28000 processors and over 14 petabytes of storage available for Research Computing by students and faculty on the Charles River and BUMC campuses. A very large number of software packages for programming, mathematics, data analysis, plotting, statistics, visualization, and domain-specific disciplines are available as well on the SCC. You will get a general overview of the SCC and the facility that houses it and then a hands-on introduction covering connecting to and using the SCC for new users. This tutorial will cover a few basic Linux commands but we strongly encourage people to also take our more extensive "Introduction to Linux" tutorial. There will also be ample time for questions of all types about the SCC. For those in the BU community interested in using a particular package on the SCC, after taking this tutorial we also recommend viewing one of our short videos on that package if one is available.   Please read and follow these instructions prior to attending the tutorial.

IntermediateIntermediate Usage of the SCC (Lecture)

Instructor: Katia Bulekova (ktrn@bu.edu)

BSCThursday May 28, 2026 10:00am - 12:00pm
ZoomMonday June 8, 2026 10:00am - 12:00pm
This tutorial will provide some more advanced techniques and common strategies used for interacting with the Shared Computing Cluster and its resources. The topics discussed during the tutorial include:
  •    Customizing your environment
  •    Parallel computing on the SCC
  •    Jobs monitoring and profiling: CPU and GPU utilization, memory usage
  •    Profiling programs for performance optimization
  •    General optimization strategies
Prerequisites: some prior experience with high performance computing or attendance of our “Introduction to BU's Shared Computing Cluster” tutorial.

Computer Programming Tutorials

BeginnerIntroduction to Parallel Programming (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

BSCMonday June 1, 2026 12:30pm - 2:30pm
This “Introduction to Parallel Programming” tutorial is recommended for anyone interested in learning more about the topic or who plans on taking our language-specific tutorials on parallel programming. This tutorial is not oriented towards any program language in particular and is intended for anyone with programming experience. This tutorial covers basic topics such as the use of processes and threads, types of computer hardware for parallel computing, and the limits of parallelization as a strategy. Additionally, several common data and algorithm patterns in software will be discussed along with effective strategies on how to parallelize them.

BeginnerNatural Language Processing Basics (LLMs Part 1) (Hands‐on)

Instructor: Josh Bevan (jbevan@bu.edu)

BSCTuesday June 2, 2026 12:30pm - 2:30pm
This is part one of a three part series but those wanting a brief introduction to Natural Language Processing (NLP) should feel free to attend just this session.   Human language/communication can be studied computationally through NLP. We'll explore the basics of NLP using Python and PyTorch; no prior machine learning experience is necessary, basic Python knowledge is helpful but not necessary. We will create a bigram character model and use it to generate random first names of people; we will build statistical and neural network implementations.

IntermediateIntermediate Language Models (LLMs Part 2) (Hands‐on)

Instructor: Josh Bevan (jbevan@bu.edu)

BSCThursday June 4, 2026 12:30pm - 3:30pm
Large Language Models (LLMs) first require successful "non-large" language models. We'll look at word embeddings, a technique for encoding words as vectors that capture their semantic meaning. We’ll examine the popular word2vec method and build/train a model to generate our own word embeddings. Finally we’ll explore how to perform linguistic operations using vector arithmetic with word2vec.

AdvancedGPT & Transformers (LLMs Part 3) (Hands‐on)

Instructor: Josh Bevan (jbevan@bu.edu)

BSCTuesday June 9, 2026 12:30pm - 2:30pm
Training Large Language Models (LLMs) requires a large neural network, large data, and large compute. We will discuss these difficulties. We’ll look at the Transformer architecture in detail to develop a quantitative understanding of how it works and how specifically tools like ChatGPT, DeepSeek, Llama, etc. work. We will then use a pre-trained SentenceTransformer model to do a range of classification on real-world data.

AdvancedPython Parallelization (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

BSCWednesday June 3, 2026 12:30pm - 2:30pm
This tutorial is an introduction to the variety of ways that parallel computations can be performed in Python. Ways of identifying code that can benefit from parallelization will be discussed. Several parallelization methods using the Python language and external libraries will be covered with examples. This tutorial assumes an intermediate understanding of the Python language and parallel computing concepts. It is strongly recommended that the “Introduction to Parallel Programming” tutorial be taken first for those new to parallel software development. If you do not have Python installed on your home machine, please read and follow these instructions prior to attending the tutorial.

AdvancedPython Optimization (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

BSCMonday June 8, 2026 12:30pm - 2:30pm
This tutorial is for those with intermediate Python experience who are interested in optimizing their code to maximize performance. The topics covered are profiling and timing Python code, selecting data structures, avoiding common pitfalls, using external libraries, and tuning Python code. If you do not have Python installed on your home machine, please read and follow these instructions prior to attending the tutorial.

BeginnerVersion Control and Collaboration with Git and GitHub, Part One (Hands-on)

Instructor: Katia Bulekova (ktrn@bu.edu)

ZoomTuesday June 9, 2026 10:00am - 12:00pm
In this interactive, hands-on two-day Git workshop, attendees will learn how to use Git for version control and collaboration with other code developers. We will go over the fundamentals of version control using Git and GitHub and practice the essential git commands. Participants will learn how to systematically store different versions of their code, recover previous versions, and safely integrate changes. We will also explore the connection with GitHub, productive collaboration with others, working with branches, and resolving conflicts. We recommend that you bring your own computer with a recent version of Git installed. You should also have a GitHub account. Prerequisites: No prior programming experience is required.

BeginnerVersion Control and Collaboration with Git and GitHub, Part Two (Hands-on)

Instructor: Katia Bulekova (ktrn@bu.edu)

ZoomThursday June 11, 2026 10:00am - 12:00pm
This session is a continuation of Version Control and Collaboration for Git and GitHub, Part One. Please register for both parts.

AdvancedPython with Dask (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

BSCWednesday June 10, 2026 12:30pm - 2:30pm
Dask is an open source Python library for parallel computing. This helps to scale Python code to large scale problems, including ones where the quantity of data is much greater than the amount of computer memory on hand. It provides a convenient way to adapt existing programs based around libraries such as Pandas and Numpy to run in parallel. This tutorial will cover using Dask to scale up Pandas Dataframes, numpy array processing, parallelizing custom Python code, and scalable file processing.

AdvancedSpecial/Advanced Topics in ML (Hands-on)

Instructor: Josh Bevan (jbevan@bu.edu)

BSCTuesday June 23, 2026 12:30pm - 2:30pm

We will cover several topics, demonstrating how they are useful for applying ML techniques/tools to broader research. We will examine:

  1. "Whisper" for speech recognition and transcription
  2. Model Context Protocol (MCP) for expanding capabilities of AI models to use external data and tools

Topics covered by this tutorial in future semesters will change based on community needs and development of new techniques/tools.

Data Analysis Tutorials

AdvancedAdv Topics in R: Code Optimization and Parallelization (Hands-on)

Instructor: Katia Bulekova (ktrn@bu.edu)

ZoomFriday June 12, 2026 10:00am - 12:00pm

This tutorial is primarily aimed at those who have some experience working in a Linux environment and programming in R. The topics covered in this tutorial:

  • debugging and profiling R code
  • choosing the right functions to speed-up your code
  • parallelization techniques
  • tuning your code for faster performance on the SCC cluster

If you do not have R and RStudio installed on your home machine, please read and follow these instructions prior to attending the tutorial.

High Performance Computing Tutorials

IntermediateIntroduction to MPI - Scaling your code to run on multiple nodes (Hands‐on)

Instructor: Josh Bevan (jbevan@bu.edu)

ZoomThursday June 11, 2026 12:30pm - 2:30pm
Many programs can be sped up by using additional CPU cores. To do this the execution needs to be parallelized and distributed across multiple cores. While “shared-memory” approaches like OpenMP allow you to use many cores on a single machine, if the program can still benefit from additional cores then a “distributed-memory” approach like MPI is needed to use multiple machines/nodes. MPI provides a way to communicate between machines and distribute work/data so that they can work cooperatively. This tutorial will take a hands-on approach at writing several simple MPI programs and along the way demonstrate basic MPI functionality. Prior parallel programming experience for attendees is important. Programs will be written in Fortran so prior experience in Fortran is helpful, but the syntax is straightforward so C/C++ experience can be enough. It is strongly recommended that the “Introduction to Parallel Programming” tutorial be taken first for those new to parallel software development.