This document discusses the increasing trend and success of using open source numerical analysis software in heterogeneous enterprise computing environments. It notes that open source operating systems like Linux and Android as well as open source hardware are becoming more common. Open source numerical software like Octave, Scilab, and SciPy are attractive to businesses and users because they are free to use and support massive parallel processing to improve time-to-market. The document advocates for using open source tools to enable large-scale simultaneous simulations to save significant time and resources.

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© 2018. Qualcomm Technologies, Inc. All rights reserved.
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Using Open Source Numerical Analysis Software in
Heterogenous Enterprise Computing Environment
Botao Lee
Senior Staff Engineer / Manager
Qualcomm Technologies, Inc.
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Open Source Trend
 Open source OS
Linux*, Android*, etc.
 Open source hardware
openRISC*, Amber*, etc.
 Open source numerical analysis software
Octave*, Scilab*, SciPy*, etc.
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*trademarks are owned by their respective owners

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 Free to use !
• Attractive to many businesses
• Wireless: Mobile, WIFI
• Automotive: telematics, infotainment, connectivity
• IOT
• Attractive to new individual users
• No initial cost
• Ability to run massive parallel sessions (improved time-to-market)
 Easy to use
• Familiar UI
• Easy to install
• Supports all major OS
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The Success of Open Source Tools

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Why Use Open Source Numerical Tools
300 days
2 days
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e.g. Enables massive parallel simulation to save time

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#ofsimulations
Date
Number of Simultaneous Simulation Runs

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For Improvement
 Increase speed
• Implement Just-In-Time compiler
• Use optimized math libraries
 Improve “peripheral” features – toolboxes
• Focus on Signal, statistics, optimization, image, control
 Raise visibility among potential users
• Get into college classes
• Increase exposure in major conferences
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