Panorama 360: Performance Data Capture and Analysis for End-to-end Scientific Workflows

 

Scientific workflows are now being used in a number of scientific domains including astronomy, bioinformatics, climate modeling, earth science, civil engineering, physics, and many others. Unlike monolithic applications, workflows often run across heterogeneous resources distributed across wide area networks. Some workflow tasks may require high performance computing resources, while others can run efficiently on high throughput computing systems. Workflows also access data from potentially different data repositories and use data, often represented as files to communicate between the workflow components. As the result of the data access patterns, workflow performance can be greatly influenced by the performance of networks and storage devices.

 

https://panorama360.github.io

 

Funding Agency: DOE