CHTC Visualization via CAVE
"UW–Madison runs a high-throughput cluster system using the HTCondor scheduling system which is operated and maintained by the Center for High Throughput Computing (CHTC). This project focuses on visualizing performance and load distribution of the cluster by displaying collected log files. The log files are timestamped and gathered over long time periods; the visualization plays them back one frame at a time and with the ability to pause or reverse. Load of the cluster and of individual nodes can be therefore not only seen, but also traced in time. Questions, such as, “Which part of the cluster is running idle at 2 a.m.?” or “Where is the highest load concentrated?” can be answered quickly and intuitively, with the time-varying datasets showing trends and patterns in the cluster usage. The project is a collaboration between the LEL and the CHTC with Markus Broecker from the LEL, and Becky Gietzel and Nate Yehle from the CHTC."
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