We would like to congratulate Alicia Esquivel Morel and the team for the acceptance of their paper, AutoLearn: Learning in the Edge to Cloud Continuum, to the SC '23 conference as well as two summer REU students who had posters accepted to SC.

This month, we're featuring an interview with Professor Prasad Calyam, a distinguished educator and researcher at the University of Missouri-Columbia. In the interview, he shares insights on effectively utilizing innovative tools like testbeds for teaching, offering valuable recommendations based on his own experiences.

We hope everybody had a lovely Juneteenth! Our User Experiment Blog is coming out slightly late this month due to the holiday but good things come to those who wait ;-). In this month’s blog we are talking with Jacob Goldverg, a student at University of Buffalo who used Chameleon to investigate how we can efficiently move large amounts of data while minimizing energy consumption.

Today, two UChicago students share with us their thoughts on how to create reproducible experiments in a cost effective manner. Ray Sinurat and Yuyang (Roy) Huang talk about the experiment patterns for storage experiments they created and describe how they can serve as a basis for developing storage experiments. Best of all – they share the experiment patterns with the Chameleon community – we hope you will find them useful! 

This month's user experiment blog discusses a group's experience in reproducing machine learning research on Chameleon!

Today we share a very unique user experience -- a conversation with Rafael Tolosana Calasanz who is an Associate Professor in the Department of Informatics of the University of Zaragoza, Spain and has participated in the reproducibility initiative at SC. Rafael shares with us his experiences reproducing artifacts on Chameleon and his insights on reproducibility and its importance to the modern scientific process. 

This month's user experiment blog covers some interesting work on tensor analysis from researchers at Arizona State University.

This month, we talk to Rick Anderson from Rutgers University about his experience using Chameleon to experiment with autonomous vehicles!

In this month's user experiment blog we get a fascinating insight into how much power training deep neural networks (DNNs) consumes – and how to make it less. The authors’ discuss research presented as part of their NSDI ’23 paper, describe how they structured their experiments on Chameleon, and explain why bare metal resources are essential for power management research. 

Learn how Radar Operations Center (ROC) used Chameleon resources as a standing backup for a planned outage.