How to Generate Exponential Delays

This question arose while addressing Comments on a previous blog post about exponentially distributed delays. One of my ongoing complaints is that many, if not most, popular load-test generation tools do not provide exponential variates as part of a library of time delays or think-time distributions. Not only is this situation bizarre, given that all load tests are actually performance models (and who doesn't love an exponential distribution in their performance models?), but without the exponential distribution you are less likely to observe such things as buffer overflow conditons due to larger than normal (or uniform) queueing fluctuations. Exponential delays are both simple and useful for that purpose, but we are often left to roll our own code and then debug it.

Plan for Capacity Planning Training in May

Bookings are open for both Guerrilla Boot Camp (GBoot) and Guerrilla Capacity Planning (GCaP) classes in May 2012 at the Early Bird rate.

As usual, classes will be held at our lovely Larkspur Landing location. Click on the image for booking information.

Before registering, take a look at some highlights students contributed from previous Guerrilla classes:

• May 2011
• August 2011

You too can be part of that educational experience.

Attendees should bring their laptops, as course materials are provided on CD or flash drive. The venue also offers free wi-fi to the internet.

The SSD World Will End in 2024

So says the Non-Volatile Systems Lab at UC San Diego. The claim is, in order to achieve higher densities, flash manufacturers must sacrifice both read and write latencies. I haven't had time to explore this claim in any detail, but I thought it might be useful for you to know about it. Some highlights include:

• They tested 45 different NAND flash chips from six vendors that ranged in size from 72 nm circuitry to the current 25nm technology.
• They then took their test results and extrapolated them to the year 2024, when NAND flash development road maps show flash circuitry is expected to be only 6.5 nm in size. At that point, read/write latency is expected to increase by a factor of two or more.
• They did not use specialized NAND flash controllers such as those used by Intel, OCZ or Fusion-io. Their results can be viewed as "optimistic" because they didn't include latency added through error correction or garbage collection algorithms.
• Considering the diminishing returns on performance versus capacity, Grupp said, "it's not going to be viable to go past 6.5 nm ... 2024 is the end."

The technical paper entitled, The Bleak Future of NAND Flash Memory (PDF), was presented and published at the FAST'12 conference held in San Jose, CA on February 14—17, 2012.

Related post: Green Disk Sizing

On the Accuracy of Exponentials and Expositions

The following is a slightly edited version of my response to a Discussion on the Linkedin CPPE group, which is accessible to Members Only. It's written in the style of a journal reviewer. The original Discussion topic was based on a link to a blog-post. I've been asked to make my Linkedin review more widely available so, here tiz...

The blog-post Capacity Planning on a Cocktail Napkin is a really good example of a really bad explanation. There are so many things that are misleading, at best, and flat-out wrong, at worst, it's hard to know where to begin (or where to stop). Nevertheless, I'll try to keep it brief [I failed in that endeavor. — njg].

The author applies the equation:

\begin{equation} E = λ \end{equation}

Why? What is that equation? We don't know because the author does not say yet what all the symbols mean. It's all very well to impress people by slinging equations around, but it's more important to say what the equations actually mean. After all, the author might have chosen the wrong one.

Hotsos Symposium 2012

Time Bandits: How to Analyze Fractal Query Times

Tues, March 6, 2012 @ 2:15 pm

That's the title of my presentation at this year's Hotsos Symposium and no, I won't be trying to make any obscure connections between Terry Gilliam's famous movie and Oracle database products (as interesting as that exercise might be).

Instead, I'll be talking about fractals in time and how they can impact performance—especially Oracle database performance. The responsiveness of your Oracle application can be lost for longer than expected periods of time, ostensibly stolen by time bandits.

Preview Slides (2012). A more detailed explanation of the fractal technique used is now provided in the Guerrilla Data Analytics (GDAT) class: How to Get Beyond Monitoring from Linear Regression to Machine Learning.

Green Disk Sizing

I finally got around to completing item 5 on my 2011 list concerning electrical power consumed by a magnetic hard disk drive (HDD). The semi-empirical statement is:

Power ∝ N_platters × Ω^2.8 × D^4.6    . . .    (1)

where N_platters is the number of platters on the spindle, Ω is the rotational speed in revolutions per minute (RPM) and D the platter diameter in inches. The power consumed is then measured in Watts.

In principle, this makes (1) valuable for doing green HDD storage capacity planning. The bad news is, it is not in the form of an equation but a statement of proportionality, so it can't be used to calculate anything as it stands. More on that shortly. The good news is that all of the quantities in (1) can be read off from the data sheet of the respective disk vendor^†. Note that the disk capacity, e.g., GB (the usual capacity planning metric) does not appear in (1).

The outstanding question is: where do those funny non-integral exponents come from?

Throughput-Delay Curves

A colleague of mine at Yahoo.com asked me if I'd ever seen curves like this:

Not only is the answer, yes (it's a throughput-delay plot or XR plot in my notation), but that particular plot comes from my GCaP course notes. There, I use it to analyze the comparative performance of a functional multiprocessor (NS6000) and a symmetric multiprocessor (SC2000). Note how the two curves cross at around 1500 OPS. You can ask yourself why and if you can't come up with an explanation, you should be registering for a Guerrilla class. :)

The above XR plot also serves as a useful reminder that the throughput and response-time metrics are not only dependent on one another, but they are generally dependent in a nonlinear way—despite what some experts may claim: