Building a Mini-Google: High-Performance Computing in Ruby

Location: Pavilion 9 - 10 Level:
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High-performance computing may not be Ruby’s strength on the surface, but there is a great number of gems and third party packages which are often overlooked when it comes to this topic. We will assume no prior knowledge of PageRank (Google’s ranking algorithm) and will walk through the basic theory and computational challenges behind it. Along the way, we will look at a hands on example of computing PageRank for a 1-million page web, and the tools behind it:

  • Ruby GSL – Working with GNU Scientific Library
  • Linalg – Ruby Linear Algebra
  • NArray – Numerical Ruby
  • And others…

As a bonus, you’ll find that the ideas behind PageRank are surprisingly simple and powerful (no math-wiz certification required) and can be easily applied to many existing social and content networks – better recommendations, search, and discovery.

Photo of Ilya Grigorik

Ilya Grigorik


Ilya Grigorik is the founder and CTO of AideRSS, a social engagement monitoring and analytics platform. He has been active in the Ruby and cloud computing community for the last three years, documenting and sharing hands on knowledge and experience with the latest architecture, design patterns, and FOSS projects (blog:, twitter: @igrigorik). He is an active speaker at many Ruby and Cloud Computing events.

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Picture of Frederick Cheung
Frederick Cheung
05/05/2009 11:28am PDT

One of those fun talks that makes you want to rush out and try some the ideas presented on your own data / tools

Russ Schissler
05/05/2009 7:50am PDT

interesting topic, great prep, plenty of useful links to grab tools and explore with, well presented.

Picture of Ryan Schenk
Ryan Schenk
05/05/2009 7:45am PDT

This was very interesting, although I was hoping for a few more implementation details regarding “high-performance computing”

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