Lessons Learned from the Chameleon Testbed


Kate Keahey, Argonne National Laboratory; Jason Anderson and Zhuo Zhen, University of Chicago; Pierre Riteau, StackHPC Ltd; Paul Ruth, RENCI UNC Chapel Hill; Dan Stanzione, Texas Advanced Computing Center; Mert Cevik, RENCI UNC Chapel Hill; Jacob Colleran and Haryadi S. Gunawi, University of Chicago; Cody Hammock, Texas Advanced Computing Center; Joe Mambretti, Northwestern University; Alexander Barnes, François Halbah, Alex Rocha, and Joe Stubbs, Texas Advanced Computing Center


The Chameleon testbed is a case study in adapting the cloud paradigm for computer science research. In this paper, we explain how this adaptation was achieved, evaluate it from the perspective of supporting the most experiments for the most users, and make a case that utilizing mainstream technology in research testbeds can increase efficiency without compromising on functionality. We also highlight the opportunity inherent in the shared digital artifacts generated by testbeds and give an overview of the efforts we've made to develop it to foster reproducibility.

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@inproceedings {254394,
author = {Kate Keahey and Jason Anderson and Zhuo Zhen and Pierre Riteau and Paul Ruth and Dan Stanzione and Mert Cevik and Jacob Colleran and Haryadi S. Gunawi and Cody Hammock and Joe Mambretti and Alexander Barnes and Fran{\c c}ois Halbah and Alex Rocha and Joe Stubbs},
title = {Lessons Learned from the Chameleon Testbed},
booktitle = {2020 {USENIX} Annual Technical Conference ({USENIX} {ATC} 20)},
year = {2020},
isbn = {978-1-939133-14-4},
pages = {219--233},
url = {https://www.usenix.org/conference/atc20/presentation/keahey},
publisher = {{USENIX} Association},
month = jul,

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