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Lab Meeting Workshops

Interested in having a workshop given directly to your lab? Contact Bryce at bdgrier@stanford.edu.

Scheduled Workshops

100 - Bash and the Unix Shell June 06, 2025

200 - Data Transfer and Storage June 13, 2025

220 - LLMs as Tools in Research June 20, 2025

300 - Containerized Analysis Notebooks   June 27, 2025

301 - Containerizing Analyses and Workflows July 2025

310 - Parallel Processing I   July 10 2025 

210 - Efficient Data Storage and Retrieval with HDF5 Late July 2025

110 - Git and Version Control August 2025

Current Offerings

100 - Bash and the Unix Shell (periodically offered in collaboration with Christina Gancayco from Stanford Research Computing)

• introduction to Unix shells

• essential Bash commands

• developing and executing a Bash script

110 - Git and Version Control

• coming soon!

200 - Data Transfer and Storage

• • • Stanford-specific and external resources for data management

    • command line data transfer tools:

      • • rsync (needed for FarmShare/Sherlock/OAK)

        • rclone (useful for cloud services)

210 - Efficient Data Storage and Retrieval with HDF5

• introduction to HDF5 file format

• guided exploration of sample files and tools

• guidelines for storing different neuroscience data types in HDF5

220 - LLMs as Tools in Research

• history, development, and current state of large language models (LLMs)

• building a retrieval-augmented model that allows for management and querying of scientific knowledge

300 - Containerized Analysis Notebooks

• promoting reproducibility through using containerized analysis

• interactive, containerized, brower-based analysis using HPC resources:

  • • FarmShare/Sherlock OnDemand

    • hosting python kernels on FarmShare/Sherlock

301 - Containerizing Analyses and Workflows

• modifying existing containers

• building custom containers from scratch

• making custom containers available to your lab or to the public

310 - Parallel Processing I

• introduction to embarrassingly parallel problems

• methods of parallelization at large scales:

  • • GNU Parallel (powerful, shell-based tool that allows for easy parallization of tasks on a local machine)

    • Pub/Sub (cloud-based service that allows for scalable, aynchronous analysis pipelines)

Future Offerings

311 - Parallel Processing II

320 - Efficient Analysis of Time Series Data

400 - CI/CD Pipelines for Scientific Computing

401 - Scientific Computing Clusters in the Cloud

500 - Integrating HDF5 with Parallel Processing