Blog Archives

Q-Q Plots for Multi-modal Performance Data

August 3, 2011
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Q-Q Plots for Multi-modal Performance Data

I'm in the process of putting together some slides on how to apply Quantile-Quantile plots to performance data. Q-Q plots are a handy tool for visually inspecting how well your data matches a known probability distribution (prob dsn). If the match is g...

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A Winking Pink Elephant

June 27, 2011
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A Winking Pink Elephant

The title of chapter 5 in my Guerrilla Capacity Planning book is, "Evaluating Scalability Parameters," and underneath it you'll see this quote:"With four parameters I can fit an elephant. With five I can make his trunk wiggle." —John von NeumannIn that vein, Guerrilla alumnus Stephen O'C. pointed me at a recent blog post and paper (PDF) that draws an...

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Go Guerrill-R on Your Data

May 31, 2011
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Go Guerrill-R on Your Data

The Guerrilla Data Analysis Techniques training course (GDAT) will be held during the week of August 8-12 this year. As usual, the focus will be on applying R to your performance and capacity planning data, as well as how to use the PDQ-R modeling too...

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May 2011 Guerrilla Classes: Light Bulb Moments

May 23, 2011
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It's impossible to know what will constitute a light bulb moment for someone else. In the recent Guerrilla classes (GBoot and GCaP), we seemed to be having many more than our usual quota of such moments. So much so, that I decided to keep a list. The first was mine. Asa H. was having trouble setting up PDQ under...

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Applying PDQ in R to Load Testing

May 19, 2011
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Applying PDQ in R to Load Testing

PDQ is a library of functions that helps you to express and solve performance questions about computer systems using the abstraction of queues. The queueing paradigm is a natural choice because, whether big (a web site) or small (a laptop), all computer systems can be represented as a network or circuit of buffers and a buffer is a type...

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Reporting Standard Errors for USL Coefficients

November 13, 2010
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In a recent Guerrilla CaP Group discussion, Baron S. wrote:....BS__ Using gnuplot against the dataset I gave, I get BS__    sigma   0.0207163 +/- 0.001323 (6.385%) BS__    kappa   0.000861226 +/- 5.414e-05 (6.287%) The Gnuplot output includes the errors for each of the universal scalability law (USL) coefficients. A question about the magnitude of these errors also...

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Confidence Bands for Universal Scalability Models

September 7, 2010
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Confidence Bands for Universal Scalability Models

In the recent GDAT class, confidence intervals (CI) for performance data were discussed. Their generalization to confidence bands (CB) for scalability projections using the USL model also came up informally. I showed a prototype plot but it was an ugly hack. Later requests from GDAT attendees to apply CBs to their own data meant I had to do...

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Where to Start with PDQ?

August 30, 2010
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Where to Start with PDQ?

Once you've downloaded PDQ with a view to solving your performance-related questions, the next step is getting started using it. Why not have some fun with blocks? Fun-ctional blocks, that is. Since all digital computers and network systems can be considered as a collection of functional blocks and these blocks often contain buffers, their performance can be modeled as...

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Excel Errors and Other Numerical Nightmares

August 25, 2010
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Excel Errors and Other Numerical Nightmares

Although I use Excel all the time, and I strongly encourage my students to use it for performance analysis and CaP, I was forced to include a warranty disclaimer in my GCaP book because I discovered a serious numerical error while writing Appendix B. There, my intention was just to show that Excel gives essentially the same results as...

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Gone Guerrill_ R on Our Data

August 16, 2010
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Here's a summary of some things we learnt about applying R to computer performance and capacity planning data in the GDAT Class last week. Neural nets pkg nnet applied to CPU performance data in the Ripley and Venables book (see Section 8.10). How to do stacked plots that Jim calls "spark plots." Jim told us that...

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