Research Computing

Becker Library has partnered with the Center for High Performance Computing (CHPC) and the Institute for Informatics (I2) to offer free trainings to the Washington University Medical Center community on a variety of research computing topics, including:

  • Computing 101
  • Python
  • R

These workshops are meant to serve as an introduction to research computing basics and prepare participants for ongoing learning. Check below to see what’s coming up or sign up for the mailing list to be notified each time a new workshop is scheduled.

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Contact Maze Ndukum ( or Marcy Vana ( with any questions.

Upcoming Workshops

There are no workshops scheduled at this time. Check back later for upcoming workshops or use the link above to sign up for the mailing list.

View a comprehensive list of Library classes and workshops

Previous Workshops

These workshops were geared toward researchers new to high performance computing and the command line interface. During each workshop session, important background concepts related to computing were introduced in a simple presentation format, followed by hands-on exercises. While these workshops were focused on using the CHPC, the knowledge gained could be applied to other computing environments. The materials from these workshops can be found here.

#1 Tools to Connect and Move Data & Getting Around the Linux Command Line Interface – 3/26/19

Goals: to develop a basic understanding of the tools needed to connect to the CHPC and transfer data back and forth, and become familiar with the Unix file system and basic Unix commands

#2 Text Editors and Shell Scripts – 4/2/19

Goals: to gain knowledge of some of the options for text editors and learn how to write and execute basic shell scripts

#3 Running Jobs on the CHPC Cluster – 4/9/19

Goal: to learn how to write and submit batch scripts to run applications on the CHPC cluster

These MATLAB training sessions were led by MathWorks Engineers. See below for a description of each workshop and links to the workshop materials.

Image Processing for Medical Applications Using MATLAB – 5/3/2018

This MATLAB training seminar included the following topics:

  • Analyzing medical images using MATLAB Apps
  • Image thresholding
  • Finding ROI properties
  • Automating your workflow with MATLAB

Workshop slides and other materials can be found here.

Demystifying Deep Learning: A Practical Approach in MATLAB – 5/14/2019

This seminar discussed MATLAB features that make it easy to:

  • Manage extremely large sets of images
  • Visualize networks and gain insight into the black box nature of deep networks
  • Perform classification and pixel-level semantic segmentation on images
  • Import training data sets from networks such as GoogLeNet and ResNet
  • Import and use pre-trained models from TensorFlow and Caffe
  • Speed up network training with parallel computing on a cluster
  • Automate manual effort required to label ground truth
  • Automatically convert a model to CUDA to run on GPUs

Workshop slides and other materials can be found here.

Parallel and GPU Computing with MATLAB – 5/14/2019

This hands-on workshop was focused on using MATLAB on the CHPC cluster. The following topics were discussed:

  • Toolboxes with built-in algorithms for parallel computing
  • Creating parallel applications to speed up independent tasks
  • Scaling up to computer clusters, grid environments or clouds
  • Employing GPUs to speed up your computations

Workshop slides and hands-on exercises can be found here.

These workshops were geared toward researchers new to programming and Python. Each workshop started with a 30-minute presentation covering important background information and then the remaining 90 minutes was devoted to hands-on activities.

Introduction to Python #1 – Getting Started with Python – 9/25/19 and 9/26/19

Goals: to develop a basic understanding of the Python programming language and to run basic Python code in the interactive Python environment, Jupyter Notebook

Previous workshop slides and hands-on activities

Introduction to Python #2 – Using Python for Data Analysis – 10/2/19 and 10/3/19

Goals: to learn to write Python code to perform data analysis and visualization, and create a Python virtual environment on a remote system

Previous workshop slides, hands-on activities, and data (weather_data_newyork, snow_data)

These workshops were geared toward researchers new to programming and R. During each workshop session important background concepts were introduced in a simple presentation format, followed by hands-on exercises.

Introduction to R #1 – 10/30/19 and 12/4/19

Objectives: introduce R objects and classes, provide an overview of some popular data structures (vectors, matrices, and data frames), and touch on basic data manipulation and visualization

Slides, hands-on-activities, and data (study data)

Introduction to R #2 – 11/6/19 and 12/11/19

Objectives: introduce advanced data visualization using ggplot2

Slides, hands-on-activities, and data (nsclc_pd1_msk_2018_clinical_data)

Introduction to R #3 – 11/13/19 and 12/18/19

Objectives: introduce genomic data analysis using R/Bioconductor and associated visualizations

Slides, hands-on-activities, and data (example, counts)