We'd like to take a brief moment to reflect with gratitude on what went right this year, at least in the (small) realm of our work on this research testbed. So here’s one year in review, representing combined “changelog” information from the entire year.
Is your instance not launching? Are your Floating IPs drifting aimlessly through the ether? Do you have a PI eligibility request? Chameleon tickets are the fastest way to reach the Chameleon support team and receive assistance for all your testbed needs. It’s 2020. Everyone could use a little extra help.
As 2021 and Oscars season approaches, the Chameleon team has compiled “Tickets of the Year” designed to help you avoid (at least some of) the same stumbling blocks of 2020. Read on to learn about some of the most common tickets, their solutions, and some special ticket award categories. You ...
Dr. Xiaoyi Lu is a research assistant professor at The Ohio State University focusing on High Performance Interconnects and Protocols, Big Data Computing, Deep Learning, Parallel Computing, Virtualization, and Cloud Computing. In this blog post, we explore his research and usage of Chameleon Cloud.
Trovi is the next iteration of the Chameleon experiment management and sharing platform. With Trovi, you can set up and configure your experimental environment from within a Jupyter notebook, document and save your experiment similarly in notebook form, and privately share it with collaborators or publish it for any Chameleon user to build on. Learn more inside!
This summer, a team of students worked on an experiment that ultimately became part of the LinnOS paper that infers the SSD performance with the help of its built in light neural network architecture. The LinnOS paper, which utilizes Chameleon testbed to provide a public executable workflow, will be presented in OSDI ’20 and is available here.
Two of the students, Levent Toksoz and Mingzhe Hao, write about their experience in this Chameleon User Stories series. Toksoz is a recent graduate of the University of Chicago computer science masters program. He studied physics and math as an undergrad at ...
Chameleon integrates directly with Jupyter Notebook to provide an experimental environment that has everything you could need for research - a cloud testbed, a way to combine actionable code with written documentation, and sharing capabilities through Zenodo. Learn more about how to take advantage of all these capabilities and package your notebooks for publishing.
The way you access the testbed will change -- for the bettter! You will be able to access the testbed via federated login allowing you to log in with your instritutional credentails or even your Google account -- read about the impact and schedule of this important change!
We have created and shared a new Jupyter notebook that shows a better way to combine standard isolated Chameleon networks with DirectStitch capabilities. This more advanced method shows how to separate management of the stitched links from the compute nodes.
Chameleon eliminates the need to involve campus IT staff and enables access to direct public cloud network connections to all Chameleon users. It is now possible for any user to experiment with these advanced cloud networking technologies using Chameleon resources without the need for complicated campus networking configuration. Learn more about the capability in this blog.
- Tickets of the Year: Solutions to Your 2020 (Ticket) Problems
- Performance Analysis of Deep Learning Workloads Using Roofline Trajectories on Chameleon
- Reproducing Solid State Drive Simulator Research Results on Chameleon
- Trovi: the Google Drive for Chameleon Experiments
- Chameleon and Reproducibility: LinnOS Case Study