Category – User Experiments

Automated Calibration of CyberInfrastructure Simulations Based on Real-World Chameleon Executions

Learn about using Chameleon to develop automated calibration for cyberinfrastructure research as part of WRENCH research team member's William Koch's Master's thesis. A M.S. student at the University of Hawai`i at Manoa (UHM), Koch explores cyberinfrastructure research, this research project's approach, and his research background in this blog post.

Using AI to Direct Traffic: Building Self Learning Networks on Chameleon

Dr. Mariam Kiran is a research scientist in the Scientific Networking Division, as a member of the Prototypes and Testbed group at ESnet, LBNL, and is leading research efforts in AI solutions for operational network research and engineering problems. In this blog, she discusses her research project DAPHNE (Deep and Autonomous High-speed Networks), her use of Chameleon, and her research background.

Biometric Research in The Cloud

January’s User Experiment’s blog features Keivan Bahmani, a PhD candidate at Clarkson University. Learn more about Bahmani and his use of Chameleon for biometric research.

Performance Analysis of Deep Learning Workloads Using Roofline Trajectories on Chameleon

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.

Reproducing Solid State Drive Simulator Research Results on Chameleon

November’s Chameleon User Experiments blog features Nanqinqin Li, a first-year PhD student at Princeton University. Learn more about Li, his summer research on reproducibility and Solid-State Drive Simulators, and learn where to replicate his experiment on Trovi!

Chameleon and Reproducibility: LinnOS Case Study

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 ...

Towards an Elastic Data Transfer Infrastructure

Motivated by the opportunity to optimize the architecture of data transfer infrastructure, we recently prototyped an elastic architecture for data transfer on Chameleon Cloud in which the DTNs expand and shrink based on the demand...

Exploring Custom InfiniBand Drivers for Specialized OS Kernels

Exploring custom high-performance drivers in specialized operating systems with an aim to scale HPC applications in order to meet the future needs of exascale computing has motivated us to build a high-performance InfiniBand driver for Nautilus (Aero-Kernel) and evaluate its performance. In this blog, we would like to share our experimental framework and results achieved.


Application-based QoS support with P4 and OpenFlow

This blog describes a prototype of a system that leverages the capabilities of flexible switches that incorporate protocol-independent packet processing in order to intelligently route traffic based on application headers.