Category – User Experiments

Tensor Analysis

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

Zeus: GPU Energy as a First-Class Resource in DNN Training

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. 

Ring around the edges: self-organizing overlay VPNs linking distributed edge resources

Learn how to use to easily create Virtual Private Networks (VPNs) and run unmodified middleware and applications across edge and cloud computing resources across networks with different firewalls and NATs (Network Address Translators).

Large Scale Ensemble Simulations

Researchers from Arizona State University developed DataStorm -- an easy-to-use platform for large scale ensemble simulations, which enables researchers to collaborate and achieve deep actionable insights.

Chameleon, and Simulating Self Propagating Malware to Evaluate Detection Technology

How do you develop and evaluate a new analytic on a network connection data set across large, enterprise systems without malware used to train machine learning models for cyber attacks? Researchers at the University of Virginia approach the problem by simulating self-propagating malware.

Exploring Process-in-memory Architecture for High-performance Graph Pattern Mining

Graph Pattern Mining (GPMI) applications are considered a new class of data-intensive applications -- they generate massive irregular computation workloads and pose memory access challenges, which degrade the performance and scalability significantly. Researchers at the Illinois Institute of Technology approach the problem by using the emerging process-in-memory architecture. 

Automated Fast-flux Detection using Machine Learning and Genetic Algorithms

Interested in protecting remote devices from malicious actors? Learn about how a researcher at the University of Missouri is approaching this problem with genetic algorithms and host fingerprinting! Also included is a YouTube video where Dr. Aksoy discusses this research.  

One Fish, Two Fish: Choosing Optimal Edge Topologies for Real-Time Autonomous Fish Surveys

Learn how researchers are pairing autonomous vehicles with Chameleon to bridge edge to cloud computation to conduct marine surveys. Featuring work presented at the 2021 Supercomputing conference, with a notebook available on Trovi that you can reproduce yourself, and a YouTube video to accompany it!

Understanding Reliability on Shared Edge

Learn about how researchers at the University of Chicago are using Chameleon’s new edge computing testbed, CHI@Edge to investigate how resource management can be applied to the concept of shared edge to optimize AI applications.