MICE

MAUS Online Data Quality - Chris Tunnell and Mike Jackson

Within the Muon Ionization Cooling Experiment (MICE), the MICE

Analysis User Software (MAUS) framework performs both online analysis

of live data and detailed offline data analysis, simulation, and

accelerator design.

The MAUS Map-Reduce API parallelizes computing in the control room,

ensures that code can be run both offline and online, and displays

plots for users in an easily extendable manner. 

The original Map-Reduce design can be advantageous for offline

computing but cannot be used in online settings. It expects all map

operations to terminate before running the reduction; however, the

data flow for online analysis requires the continuous updating of live

plots as data arrives. 

For online running, the "map" and "reduce" steps must happen

concurrently; therefore, new parallelization routines were developed 

specifically for this use.   

The "map" step is parallelized using a Python-based distributed task

queue called Celery, and output from these tasks is then written into

a NoSQL database called CouchDB. 

As the "mapper" writes output, the plotting "reducers" query the

database, request data from a user-specified window in time, and make

plots using Matplotlib or PyRoot. 

The "reducers" serialize the plots into the data stream after which

all the data is written to the database by the output routines. 

Finally, plots are displayed on the web using the Django platform,

which queries the database and displays the plots to the control room

and the world. 

By maintaining the API and modifying the data flow, MICE is able to

use identical analysis software in both offline and online scenarios,

thus avoiding a common issue in experimental particle physics.