# Presentation: 086539

## McFarm Performance Monitoring(McPerM)

- Richard Thomas
- Benedict College
- Supervisor
- Dr. Hyunwoo Kim
- University of Texas at Arlington

## Introduction

- My Project:
- 	-Improve McPerM.
- 	-To re-implement McPerM with updates.
- But before I delve into the specifics of my project, lets first get some background information...

## Background

- Nature is based on...
- four forces: gravity, the electromagnetic force, the weak
- 	force, and the strong force.
- Many years of experiment and theory have resulted in...
- the Standard Model (SM).
- During the 1960’s and 1970’s, physicists showed that
- Electromagnetic and weak forces could be unified...
- Strong force and gravity are still separate.

## The Standard Model

- Years of experimental and theoretical advances has lead to the Standard Model.
- However, this is believed to be only an approximate theory and current research is being done to improve the theory.

## Fermi National Accelerator Laboratory

- One of the goals of Fermilab is verifying the Standard Model.
- To verify it, Fermilab conducts high energy experiments.
- This is done with the Tevatron; a particle accelerator with 2 collision halls, D-Zero and CDF.

## D-Zero Experiment

- The collision events that occur at D-Zero need to be compared to Monte Carlo (MC) data.
- MC data are simulated re-creations of
- 	events that occur. It uses a series of
- 	mathematical equations to produce sections of
- 	events and randomize them to ensure their
- 	authenticity.

## An Event at D-Zero

- This is an event taken from the D-Zero detector.
- It is also what we are re-creating with the Monte-Carlo Simulations.

## D-Zero Collaboration

- Due to the massive amount of MC data that is needed, it would be impossible to create all of it at Fermilab.
- D-zero relies on remote institutions to supplement MC creation.
- One of the institutions is University of Texas at Arlington (UTA) which is a part of the D0 Southern Analysis Region (D0SAR).

## McFarm

- UTA has developed a computer software which can control MC production that is called McFarm.
- Production itself will be meaningless if it is not accompanied by good monitoring software.
- UTA created a number of monitoring software and one of which is MCPERM, whose main purpose is to show statistical performance of McFarm over a period of time.

## McPerM performs 4 main tasks:

- Converts archived information into XML files.
- XML files are collected by main server.
- Files are then converted into McPerM readable format.
- Database is parsed and statistics are displayed using Ploticus.

## Components of McPerM

- There are 2 major components to McPerM:
- McP_remote: This resides on the remote farm.
- McP_server: This resides on the main farm which hosts the main server.

## Flow of Data

- This is how data is passed to and from the user.

- new_m.htm

- new_cgi_multi.py

- new_mpspeed_multi.py

- new_mpdata.py

- Web Front-End

- Processing Scripts

- new_xml_function.py

- Parsing Script

- Middle Man

## Web Front-End

## Implementation

- Ploticus was used to give graphical representations of the users’ requests.

## Total Event Generated

- Swift Farm at U. Texas, Arlington

## DPCC at U. Texas, Arlington

## CSE farm at U. Texas

## HEP cluster at Oklahoma University

## Conclusion

- The purpose of this project was to improve McPerM and ensure it maintains steady
-    working condition.
- To that extent, the project is complete,
-     however  further work has to be done to fully
-    automate McPerM for it to be working efficiently.

## Acknowledgements

- I would like to thank Hyunwoo Kim, Jae Yu, Dr. Davenport, Dianne Engram and Elliot McCrory for taking the time out to mentor me and making sure that my experience here was the best possible.
- I would also like to give a special thank you to the SIST Committee.