Blog Archives

USL Scalability Modeling with Three Parameters

May 20, 2018
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USL Scalability Modeling with Three Parameters

NOTE: Annoyingly, the remote mathjax server often takes it's sweet time rendering LaTex equations (like, up to a minute or more!!!). I don't know if this is deliberate on the part of Google or a bug. It used to be faster. If anyone knows, I'd be interested to hear; especially if there is a way to speed it up....

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GitHub Growth Appears Scale Free

January 18, 2017
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GitHub Growth Appears Scale Free

In 2013, a blogger claimed that the growth of GitHub (GH) users follows a certain type of diffusion model called Bass diffusion. Growth here refers to the number of unique user IDs as a function of time, not the number project repositories, which can have a high degree of multiplicity. In a response, I tweeted a plot that...

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PDQ 7.0 Dev is Underway

May 14, 2016
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PDQ 7.0 Dev is Underway

The primary goal for this release is to make PDQ acceptable for uploading to CRAN. This is a non-trivial exercise because there is some legacy C code in the PDQ library that needs to be reorganized while, at the same time, keeping it consistent for programmatically porting to other languages besides R—chiefly Perl (for the book) and Python. To...

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PDQ 7.0 Dev is Underway

May 14, 2016
By
PDQ 7.0 Dev is Underway

The primary goal for this release is to make PDQ acceptable for uploading to CRAN. This is a non-trivial exercise because there is some legacy C code in the PDQ library that needs to be reorganized while, at the same time, keeping it consistent for programmatically porting to other languages besides R—chiefly Perl (for the book) and Python. To...

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PDQ Version 6.2.0 Released

August 24, 2015
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PDQ Version 6.2.0 Released

PDQ (Pretty Damn Quick) is a FOSS performance analysis tool based on the paradigm of queueing models that can be programmed natively in R Python Perl C and several other languages. This minor release is now available for download. If you're new to PDQ, here's a simple queueing model written R that you can paste directly into...

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PDQ Version 6.2.0 Released

August 24, 2015
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PDQ Version 6.2.0 Released

PDQ (Pretty Damn Quick) is a FOSS performance analysis tool based on the paradigm of queueing models that can be programmed natively in R Python Perl C and several other languages. This minor release is now available for download. If you're new to PDQ, here's a simple queueing model written R that you can paste directly...

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Hockey Elbow and Other Response Time Injuries

July 29, 2015
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Hockey Elbow and Other Response Time Injuries

You've heard of tennis elbow. Well, there's a non-sports, performance injury that I like to call hockey elbow. An example of such an "injury" is shown in Figure 1, which appeared in a recent computer performance analysis presentation. It's a reminder of how easy it is to become complacent when doing performance analysis and possibly end up reaching the...

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Hockey Elbow and Other Response Time Injuries

July 29, 2015
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Hockey Elbow and Other Response Time Injuries

You've heard of tennis elbow. Well, there's a non-sports, performance injury that I like to call hockey elbow. An example of such an "injury" is shown in Figure 1, which appeared in a recent computer performance analysis presentation. It's a reminder of how easy it is to become complacent when doing performance analysis and possibly end up reaching the...

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Restaurant Performance Sunk by Selfies

July 17, 2014
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Restaurant Performance Sunk by Selfies

An interesting story appeared over the weekend about a popular NYC restaurant realizing that, although the number of customers they served on a daily basis is about the same today as it was ten years ago, the overall service has significantly slowed. Naturally, this situation has led to poor online reviews so, the restaurant hired a firm to investigate...

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How to Remember the Poisson Distribution

July 3, 2014
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How to Remember the Poisson Distribution

The Poisson cumulative distribution function (CDF) \begin{equation} F(α,n) = \sum_{k=0}^n \dfrac{α^k}{k!} \; e^{-α} \label{eqn:pcdf} \end{equation} is the probability of at most $n$ events occurring when the average number of events is α, i.e., $\Pr(X \le n)$. Since \eqref{eqn:pcdf} is a probability function, it cannot have a value greater than 1. In R, the CDF is given by the...

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