Event Cloud Computing - IBM Turning Data Centers Into ?Computing Cloud?

 
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Old 11-15-2007
Event Cloud Computing - IBM Turning Data Centers Into ?Computing Cloud?

Tim Bass
Thu, 15 Nov 2007 23:55:07 +0000
*I predict we may experience less*debates*on the use of the term “event cloud”*related to*CEP in the future, now that both IBM and Google* have made announcements about “cloud computing” and “computing cloud”, IBM Turning Data Centers Into ‘Computing Cloud’
“The initiative also builds on IBM’s announcement with Google last* month that they are developing cloud computing environments for* academic use.* But today’s announcement is aimed more widely at*corporations and government users that want the extreme scale made possibly by lashing together pools of computers.”
This also furthers the notion and architecture we have been advocating, that event processing will move toward a distributed, cooperative*computing model..



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LinPred(3)						User Contributed Perl Documentation						LinPred(3)

NAME
PDL::Filter::LinPred - Linear predictive filtering SYNOPSIS
$a = new PDL::Filter::LinPred( {NLags => 10, LagInterval => 2, LagsBehind => 2, Data => $dat}); ($pd,$corrslic) = $a->predict($dat); DESCRIPTION
A filter by doing linear prediction: tries to predict the next value in a data stream as accurately as possible. The filtered data is the predicted value. The parameters are NLags Number of time lags used for prediction LagInterval How many points each lag should be LagsBehind If, for some strange reason, you wish to predict not the next but the one after that (i.e. usually f(t) is predicted from f(t-1) and f(t-2) etc., but with LagsBehind => 2, f(t) is predicted from f(t-2) and f(t-3)). Data The input data, which may contain other dimensions past the first (time). The extraneous dimensions are assumed to represent epochs so the data is just concatenated. AutoCovar As an alternative to Data, you can just give the temporal autocorrelation function. Smooth Don't do prediction or filtering but smoothing. The method predict gives a prediction for some data plus a corresponding slice of the data, if evaluated in list context. This slice is given so that you may, if you wish, easily plot them atop each other. The rest of the documentation is under lazy evaluation. AUTHOR
Copyright (C) Tuomas J. Lukka 1997. All rights reserved. There is no warranty. You are allowed to redistribute this software / documentation under certain conditions. For details, see the file COPYING in the PDL distribution. If this file is separated from the PDL distribution, the copyright notice should be included in the file. perl v5.12.1 2009-10-17 LinPred(3)