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SmartData Collective > Analytics > Modeling > Numbers Everyone Should Know
Modeling

Numbers Everyone Should Know

Editor SDC
Editor SDC
1 Min Read
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Some of you have seen me build simple models to do a reality-check on architecture (see here, for example). Here are some metrics from a great presentation by Jeff Dean, a Google fellow.

Numbers Everyone Should Know

Some of you have seen me build simple models to do a reality-check on architecture (see here, for example). Here are some metrics from a great presentation by Jeff Dean, a Google fellow.

Numbers Everyone Should Know

More Read

ACM Data Mining Talk: Representing Solutions with PMML
How to Unlock the Potential in Your Business Analytics
Why Medians May Not be the Message – for Talent Data
Why Predictive Modelers Should be Suspicious of Statistical Tests
Evaluating Successful Predictive Analytics Solutions
L1 cache reference0.5 ns
Branch mispredict5 ns
L2 cache reference7 ns
Mutex lock/unlock25 ns
Main memory reference100 ns
Compress 1K bytes with Zippy3,000 ns
Send 2K bytes over 1 Gbps network20,000 ns
Read 1 MB sequentially from memory250,000 ns
Round trip within same datacenter500,000 ns
Disk seek10,000,000 ns
Read 1 MB sequentially from disk20,000,000 ns
Send packet CA->Netherlands->CA150,000,000 ns

Of note is the 80X difference between the cost of accessing memory and the cost of accessing disk.

The entire presentation may be found here: http://www.odbms.org/download/dean-keynote-ladis2009.pdf

Happy Modeling…

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