Jeremy Cowles, Eric Heien, Adam Kornafeld,

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Jeremy Cowles, Eric Heien, Adam Kornafeld,
Yusuke Takata, Kenichi Hagihara, Nicolás Alvarez
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Overview

• PyMW Summer of Code
• Recent Enhancements in 0.3
• PyBOINC Distributable Python Interpreter
• BOINC PyMW at U.C. Berkeley
• Future plans for PyMW

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Google Summer of Code

• Proposal accepted via Python Foundation
• Worked with Eric Heien as project mentor
• Goals
• Improve BOINC integration in PyMW
• Reduce barriers to creating BOINC apps
• Remove the Python requirement on the Client

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PyMW v0.2 Limitations

• Need to compile assimilator from C source
• Manual project setup via script
• Modules, libraries data bundled by BOINC
  application, not by work unit
• No direct support for BOINC API
• Python installation is assumed on client

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Enhancements in v0.3

• Pure-Python assimilator
• Abstract base class, easy to extend
• Leverage existing Python code
• Automated project setup
• Validates project setup on every execution
• Installs required daemons
• Installs/upgrades science application

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Enhancements in v0.3

• Bundle arbitrary files with work units
• Individual Python libraries
• Domain-specific data
• Customizable work unit generation
• Number of target results, output size, etc
• Native Python support for BOINC API

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PyBOINC Python Interpreter

• Collaboration with Nicolás Alvarez
• Official Python interpreter (embedded)
• BOINC compatible, distributable
• Statically compiled for
• Windows
• Linux
• Mac OS X

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PyBOINC Features

• Customizable standard library
• Uses Pythons support for zipped modules
• 2.6 bundled with current release
• Add or remove components as needed
• 3rd party libraries
• BOINC API module included by default
• Compiled C modules dynamic libraries

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PyMW 0.3 Workflow

• Download PyMW PyBOINC
• Write PyMW science application
• Install BOINC server create a project
• Run the application
• myapp.py d /projects/my_proj
• Does it work with real applications?

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PyMW BOINC _at_ Berkeley
CS188 Introduction to Artificial
Intelligence Pacman AI Tournament
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Pacman AI Tournament

• Large framework in Python w/data files
• Student teams submit agents
• Matches run nightly
• Takes 16 hours to run tournament (serial)

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Using PyMW BOINC

• BOINC formulation
• Wrapped tourney framework with PyMW
• One match per work unit
• 99 orthogonal to PyMW/BOINC
• Students can volunteer compute time
• PyMW multi-core for debugging
• New tourney runs in about 1 hour

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Future Plans for PyMW

• Security signing scripts
• Support for BOINC Graphic API
• Python 3.0 Support
• Check-pointing support

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Online Resources

• PyMWhttp//pymw.sourceforge.net/
• PyMW Documentation http//pymw.sourceforge.net/do
  c/
• PyBOINChttp//bitbucket.org/jeremycowles/pyboinc