Blog Archives

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...

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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...

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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...

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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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Importing an Excel Workbook into R

June 5, 2014
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Importing an Excel Workbook into R

The usual route for importing data from spreadsheet applications like Excel or OpenOffice into R involves first exporting the data in CSV format. A newer (c. 2011) and more efficient CRAN package, called XLConnect, facilitates reading an entire Excel workbook and manipulating worksheets and cells programmatically from within R. XLConnect doesn't require a running installation...

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Importing an Excel Workbook into R

June 4, 2014
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Importing an Excel Workbook into R

usually import Excel data in CVS format A new package in CRAN facilitates reading in entire Excel workbook and selecting worksheets and cells from there. example.... require(XLConnect)# Load Excel workbook into memorywb # Convert a sheet to a data frame df sheet = "SGI-NUMA", startRow = 3, endRow =...

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Melbourne’s Weather and Cross Correlations

April 1, 2014
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Melbourne’s Weather and Cross Correlations

During a lunchtime discussion among recent GCaP class attendees, the topic of weather came up and I casually mentioned that the weather in Melbourne, Australia, can be very changeable because the continent is so old that there is very little geographical relief to moderate the prevailing winds coming from the west. In general, Melbourne...

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Facebook Meets Florence Nightingale and Enrico Fermi

February 18, 2014
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Facebook Meets Florence Nightingale and Enrico Fermi

Highlighting Facebook's mistakes and weaknesses is a popular sport. When you're the 800 lb gorilla of social networking, it's inevitable. The most recent rendition of FB bashing appeared in a serious study authored by a couple of academics in the Depar...

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Response Time Percentiles for Multi-server Applications

December 25, 2013
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Response Time Percentiles for Multi-server Applications

In a previous post, I applied my rules-of-thumb for response time (RT) percentiles (or more accurately, residence time in queueing theory parlance), viz., 80th percentile: $R_{80}$, 90th percentile: $R_{90}$ and 95th percentile: $R_{95}$ to a cellphone application and found that the performance measurements were not completely consistent. Since the data appeared in a journal blog, I...

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Laplace the Bayesianista and the Mass of Saturn

September 15, 2013
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Laplace the Bayesianista and the Mass of Saturn

I'm reviewing Bayes' theorem and related topics for the upcoming GDAT class. In its simplest form, Bayes' theorem is statement about conditional probabilities. The probability of A, given that B has occurred, is expressed as: \begin{equation} \Pr(A|B) = \dfrac{\Pr(B|A)\times\Pr(A)}{\Pr(B)} \label{eqn:bayes} \end{equation} In Bayesian language, $\Pr(A|B)$ is called the posterior probability, $\Pr(A)$ the prior probability, and $\Pr(B|A)$ the...

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