acm - an acm publication

2009 - February

  • The Fallacy of Premature Optimization
    Moore's Law makes it seem as if resource limitations are always a minor consideration. If there will be twice as much memory for the same price in 18 months, why bother to squeeze a factor of 2 from an application's memory requirements? If the CPU will be twice as fast by then, why bother to shave some running time from a program? In other words, why bother to optimize programs? Isn't it better to just get them running and let Moore's Law take us off the hook when resources are constrained? Randall Hyde argues that optimization is important even when memory and processor double regularly. Trying to do the optimization too early can be a futile time-waster.

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Ubiquity Symposium: Big Data

Table of Contents

  1. Big Data, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
  2. Big Data and the Attention Economy by Bernardo A. Huberman
  3. Big Data for Social Science Research by Mark Birkin
  4. Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
  5. High Performance Synthetic Information Environments: An integrating architecture in the age of pervasive data and computing By Christopher L. Barrett, Jeffery Johnson, and Madhav Marathe
  6. Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk
  7. When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic
  8. Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic
  9. Big Data: Business, technology, education, and science by Jeffrey Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, and Marco Amador
  10. Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic