Sharing transient data and preliminary results from XSEDE resources via SeedMe platform
Presented at XSEDE 2015 conference, St. Louis, MO, Jul 26-28, 2015
Instructor: Amit Chourasia, San Diego Supercomputer Center, UC San Diego
Overview
High performance computing (HPC) processes and workflows often include several steps for example input preparation, computation monitoring, output validation, analysis and visualizations. All these processes yield small-scale consumable information for e.g. computation progress, statistics, plots which are of high value for research team. Sharing and accessing consumable information by team members is often slow and cumbersome in current HPC environment. This tutorial will introduce attendees to the SeedMe (Stream encode explore and disseminate My experiment) platform and show how this platform can be leveraged to share consumable information rapidly with easy to use tools in ad hoc and/or automated manner.
Instructor: Amit Chourasia, San Diego Supercomputer Center, UC San Diego
Date: To be announced
Duration: 90 minutes
Skill Level: Level: Introductory/Beginner
Pre-requisites: Basic familiarity with command line tools like changing directory and executing commands.
Requirements:
- Computer/Laptop (Mobile devices are not sufficient for this tutorial)
- Account on SeedMe.org (Attendees could create one during the tutorial)
- Download SeedMe tools – Either standalone or Python client/module (recommended)
- Download sample data
The tutorial will cover the following topics
- SeedMe platform overview (Lecture - 10 mins)
- Web Browser interaction –(Hands On – 10 mins) Learn organization, navigation and usage via web browser for editing, uploading, commenting, sharing and notifying.
- Automation Set up (Hands On - 5 mins) Learn to set up the environment for command line and programmatic interaction
- Command line interaction (Hands On – 25 mins) Learn to use SeedMe command line tools. These tools could be used on HPC platform.
- Programmatic interaction (Hands On – 25 mins) Learn methods available in Python client/module and use them in sample example.