Linkedin’s latest site redesign reduced the font-size to eye-straining smallness. When I tried to enlarge the text (OmniWeb, Safari, MacBook Pro), I found text enlargement didn’t work.

What?

How did they disable text enlargement? And why would someone purposely make their website difficult to read?

I don’t have a desire to hunt down how linkedin disabled text enlargement. Even if I did find the cause, I’m sure people who could fix the problem already know yet choose to not fix the problem.

I’ll set aside my cynicism and charitably speculate an answer to the first question.

Maybe El Queso Grande–the all powerful wizard who signs off on the look and feel–is a PC type and has a low resolution monitor. In order to finish the project, the CSS designers needed to ensure that the site “Looked right on the boss’ monitor.”

A peek at the CSS shows that the font-size is hard coded to 13 pixels. {{sigh}}

Assume El Queso Grande has a Dell computer. Not a bad assumption given Dell’s penetration into the corporate market.

My display is the 15″ MacBook Pro. How does the Dell and Apple products compare?

MacBook Pro 15"
900 1440 1698  pixels
         15.4  inches

X**2 + (1.6X)**2  = 15.4**2
X**2 + 2.56(X**2) = 237.16
       3.56(X**2) = 237.16
                x = 8.16
110 pixels per inch

Dell Vostro 1015
768 1366 1567  pixels
         15.6  inches

X**2 + (1.78X)**2 = 15.6**2
X**2 + 3.16(X**2) = 243.36
       4.16(X**2) = 243.36
                x = 7.65
100 pixels per inch

Maybe they have an older desktop monitor, which could drop the density down to 90 or even 80 pixels per inch. Older CRT monitors generally had 72 pixels per inch.

We can now calculate how large (or small) the text appears on the different monitors by converting pixels to points. A point in typography is simply 1/72 of an inch. A pixel does not imply measurement.

Let’s see how much of a differnce that makes.

 pixels
per inch    pixels     inches     points
--------   --------   --------   --------
   72         13       0.1806      13
   80         13       0.1625      11
   90         13       0.1444      10.4
  100         13       0.13         9.4
  110         13       0.1182       8.5

Text that is defined in pixels becomes smaller on higher resolution monitors. A lot smaller. In my case, linkedin renders at 8½ point text. That’s painful. I prefer reading 12 to 14 point text.

Fortunately for me, OmniWeb has per site settings. One of those settings allows the user to specify a user-supplied stylesheet. And that’s exactly what I did.

/*
 * Stylesheet to override linkedin's stupid small font-size
 */
span, div, h1, h2, h3, h4, li, p, a {
	font-size: 12pt  !important;
}

It’s not convenient but it works.

顿悟之前砍柴挑水，顿悟之后砍柴挑水——吴力。

Dùnwù zhī qián kǎnchái tiāo shuǐ,
Dùnwù zhī hòu kǎnchái tiāo shuǐ.
–Wú Lì

Before enlightenment, chop wood and carry water;
After enlightenment, chop wood and carry water.
–Wu Li

Note: Enlightenment does not relieve one of the details of daily life.

摸着石头过河——邓小平。

Mōzhe shítou guòhé.
–Dèng Xiǎopíng

Cross the river by feeling the stones.
–Deng Xiaoping

Note: We may not see exactly how to get there but we will pragmatically find our way; we will learn as we go.

一步一个脚印

yībù yīgè jiǎoyìn

one step, one footprint (idiom);
steady progress; reliable

Note: Perhaps my favorite idiom.

画龙点睛

huàlóngdiǎnjīng

to paint a dragon and dot in the eyes (idiom);
fig. to add the vital finishing touch;
the crucial point that brings the subject to life;
a few words to clinch the point

I read a paper some time ago–but for the life of me cannot remember where–presenting study findings on student recall and comprehension. The irony of not recalling the details of a paper on the subject of recall spurred me to examine my own recall in other areas. I may have forgotten the source but the gist of the paper… that I remember: The best way to improve comprehension and recall is to write an essay. I’ve long believed that writing develops a concept more fully (Galbraith, Torrance & Hallam, 2006) but the lost paper suggests that essay writing on a new subject internalizes the content.

Blogging is (or can be) a form of essay writing. I read a lot for both work and school. Would writing about what I read improve my recall? The lost paper seems to suggest so. With that in mind, I have decided 2011 is my year to write book reports. Since I’m writing for myself, these reports may be peculiar and I make no apology for it. I make no claim of their utility in anyone’s purchasing consideration. In fact, I may not even write about the content but rather the mechanics of the content.

My recent review of Beginning Rails 3 (Carniero & Al Barazi, 2010) dated February 23, 2011 can be found on safari.oreilly.com [repeated below]. I don’t know if it’s a proper or even a traditional review. It contains my pressing thoughts upon finishing the book. Reading back over it, I can think of several essay topics that have little to do with Rails but rather with the construction of a book on Rails. That, however, is a different posting.

I found Beginning Rails 3 to be a gentle introduction to rails. I came from a C/java background and comfortable with ruby, sql and bash.

Intro: Ch 1,2,3 contain the obligatory ‘getting started’ material. Fortunately the material is easily digestible and relatively brief. I wanted to build the sample application as I read the material and went through processes of updating rails (on OS X) and getting the first app running. Everything here worked on my laptop as described in the book.

Models: Ch 4,5 walk through just enough ORM to carry the reader through the rest of the book. The authors didn’t get wrapped up in sidebar discussions of ActiveRecord outside the scope of the sample project. I liked using the rails console to learn the minimum basics of creating and using models.

Controllers/Views: Ch. 6,7 walk through building the ‘web side’ of the app based on the models from the previous two chapters. A good understanding of the models before building the controllers and views made the exercise much easier to follow and anticipate.

Samplers: Ch 8, 10, 11 are sampler chapters each of which could warrant an entire volume. A consistent theme throughout the book is ‘just enough’ and these sampler chapters give the flavor if not the feast. The chapter on ajax replaces prototype with jquery (thank you) and ajaxifies a single form. It’s enough to get started. The chapter on internationalization gives just one approach to creating a multilingual site. It’s an ugly problem and this book should only be viewed as an introduction–a good introduction but an introduction nonetheless. The same can be said for the chapter on testing. For someone just getting into rails, the material on writing tests is enough without being overwhelming.

Skipped: I read but skipped working the tutorial for Ch 9, 12, 13. The material seemed simple enough and I felt the other chapters gave me an adequate base of understanding to start working on a simple app of my own.

These guys really worked to keep their code clean and in sync with the book. I kept getting a warning (Object#id will be deprecated; use Object#object_id) on a partial when working through the chapter on testing. It turned out that the error was upstream (a case of id vs. :id). I downloaded the chapter source and diff’d against my work. Aside from some whitespace differences (and typo’s on my part), the files matched.

This is where I’d normally offer my suggested revisions. I really don’t have any. This is, after all, *Beginning* Rails 3. No book can cover everything. Nor should it try. So, what’s next? Speaking for myself, the next book to read is on test development.

Speak a new language
so that the world
will be a new world.
—Rumi

2010 sucked.

Don’t get me wrong. There was a lot good happened in 2010. But as a vintage, it sucked. Big donkey balls.

At 2010′s wake, we make New Year’s resolutions in hopes that doing so will wash the taste out of our mouths. It’s what we do. Like paying taxes in April. Creatures of habit, that’s what we are. One of those habits is making resolutions at year’s end.

Sometimes a resolution is vague…as in, “I will lose weight.” But being the innately masochistic sufferers that we are, a resolution usually details the burden…as in, “I will wake at 5am and work out at Gold’s Gym for 2 hours every workday morning.”

In either case, we are liars and know it. Still, we make the resolution. And still yet, we can’t get that donkey ball taste out of our mouths. But for a short while, we live the fantasy that we are doing something about our pathetic lives.

2010 sucked and my mouth tastes of donkey balls.

Such is the nature of being human, its essence intrinsic in our art. Maybe that’s why Country Music is so popular. It’s raw, authentic and touches on a universal truth: Life is Suffering.

I’m not making resolutions this year. No empty promises to the gods in hopes they shine a little fortune my way. Nope. This year, I’m going tactical. Search and destroy: looking past; looking present; looking future.

What does that mean? It means, I will not make a list of habitual patterns of behavior and how I will change them. What I will do am doing is practicing awareness of my life: lived, living, and to be lived.

• Which relationships are toxic?
• Which relationships are neglected?
• Which loose ends need attention?
• Which loose ends can I write off?
• What dreams have been tabled?
  • For more than a year?
  • For more than 2 years?
  • For more than 10 years?
• Where do I compromise?

Stuff like that.

Aristotle noted that, “We are what we repeatedly do.”

It’s a chicken and egg dilemma but Ari gets it right. We are creatures of habit.

Look, life happens each moment and in each moment we handle life. Spouting resolutions at years end doesn’t change a thing. It’s the myriad small changes at each moment during the year that alters a course. All we really have is now, the present moment. But that’s all you need. In each moment, you can see your whole life.

To see a World in a Grain of Sand
And a Heaven in a Wild Flower,
Hold Infinity in the palm of your hand
And Eternity in an hour… –W. Blake

To bend what you do in any moment is to bend the universe. It’s in each single moment that habits are broken and entire new worlds are born.

The closest thing I have to a resolution this year is to practice standing in each moment, eight sides open.

The petabyte is required not just for the finished product. It’s needed to store all the sensor and camera data as well. Okay. I accept that Weta needed 1PB. How does one go about creating a petabyte storage facility? What are the tradeoffs? How much does it cost to build and then to maintain?

I need to get this out of my head and free up some brain cycles to continue with my Seeds of Discontent series. This article is a sidebar.

Disclaimer: I’m using a server build derived from the Seeds of Discontent serial (see also, Seeds of Discontent: System Benchmarking Hardware). It isn’t a traditional server room server but it serves as a baseline talking point. Besides, I can get budgetary pricing off newegg.com. It’s good enough for the purposes of this discussion. I’m sure the staff at Weta (or ILM or Dreamworks or Pixar) would have more insight into what *really* works.

I’ll choose the 4U chassis for this exercise since it better approximates the airflow of a desktop chassis. The 50U rack is taller than usual but it allows for 12 4-U servers plus a switch.

In the Seeds of Discontent serial, the HDD array uses the cheapest drives available; The final size is not important. In this sidebar discussion, final HDD capacity *is* important. This is not a single desktop box but a compute and storage cluster.

Each server functions as a compute unit as well as a storage unit.

A commodity multi-core CPU together with two commodity PCI Express GPU subsystems comprise the compute unit. Primary storage and swap for the compute unit is a two-disk RAID 0 SSD. The GPU cards have their own RAM while the CPU has two triple-channel banks of DDR3.

The server also hosts an HDD array which is not private storage but part of a larger storage cluster. For this exercise, I arbitrarily choose GlusterFS.

I’ve budgeted $2,500 USD per server (less the HDD array).

(circa mid-November 2010)
case+PSU       $ 200
mainboard        230
SSD              135
SSD              135
DDR3 24GB        550
CPU              850
GPU              200
CPU              200
--------------------
             $25,000 USD
              $2,500 USD

In addition, I’ve budgeted $1,000 per rack and $1,000 per switch. A fully constructed rack sans HDD is $32,000. YMMV.

rack         $ 1,000
switch         1,000
servers       30,000 (2,500 * 12 servers/rack)
--------------------
             $32,000 USD

Let’s add the HDD to build out a petabyte cluster. Since I’m using the Asus Rampage III (admitedly not a server mainboard), the two GPU fully consume the PCI Express lanes. There aren’t any lanes left for a RAID card. The two SSD drives occupy the two SATA III channels leaving the seven SATA II channels for the HDD array. Each server then adds seven HDD (and each rack adds 84 HDD) to the cluster.

As seen from this list (circa mid-November 2010), the lower capacity drives are not the cheapest drives per gigabyte.

SKU               $USD  cnt    GB   $/GB $K/PB  HDD/PB
---------------   ----  ---  ----  ----- -----  ----
WD5002ABYS-20PK   1750   20   500  0.175  175   2000
WD7502ABYS-20PK   2500   20   750  0.167  167   1333
0A39289-20PK      2700   20  1000  0.135  135   1000
WD7501AALS-20PK   1550   20   750  0.103  103   1333
WD6401AALS-20PK   1300   20   640  0.102  102   1563
WD5000AADS-20PK    900   20   500  0.090   90   2000
0F10381-20PK       900   20   500  0.090   90   2000
WD1001FALS-20PK   1800   20  1000  0.090   90   1000
WD5000AAKS-20PK    880   20   500  0.088   88   2000
WD6400AARS          55    1   640  0.086   86   1563
WD7500AADS-20PK   1250   20   750  0.083   83   1333
ST3500418AS         40    1   500  0.080   80   2000
WD7500AADS          55    1   750  0.073   73   1333
WD20EVDS-20PK     2800   20  2000  0.070   70    500
0F10383-20PK      1400   20  1000  0.070   70   1000
WD10EALS-20PK     1350   20  1000  0.068   68   1000
WD10EARS            65    1  1000  0.065   65   1000
WD10EARS-20PK     1200   20  1000  0.060   60   1000
WD15EARS-20PK     1700   20  1500  0.057   57    667
ST31000528AS        50    1  1000  0.050   50   1000
ST31500341AS        60    1  1500  0.040   40    667

Downselect the cheapest drive at each capacity point greater than or equal to 1TB.

SKU               $USD  cnt    GB   $/GB $K/PB  HDD/PB
---------------   ----  ---  ----  ----- -----  ----
WD20EVDS-20PK     2800   20  2000  0.070   70    500
ST31000528AS        50    1  1000  0.050   50   1000
ST31500341AS        60    1  1500  0.040   40    667

I want to minimize the number of drives while minimizing costs. The Seagate 1TB drive is both more expensive per GB and requires more drives per PB than the Seagate 1.5TB drive. It is immediately eliminated. The competition is between the Western Digital 2TB and the Seagate 1TB drive.

If cost were the only issue, then the Seagate drive would win. If drive count were the only issue then the Western Digital drive would win. To get closer to an answer, let’s build out the storage cluster.

Petabyte Cluster with Just a Bunch of Disks

        ======= count ======  ========= cost ==========
Drive   HDD   Servers  Racks    HDD     Rack     Total
-----  -----  -------  -----  -------  -------  -------
2.0TB    500       72      6   70,000  192,000  262,000
1.5TB    667       96      8   40,000  256,000  296,000

Even though the 2TB drives cost $30,000 more than the 1.5TB drives, the total cluster cost is $34,000 for the 1.5TB drive choice. Furthermore, there is no redundancy to protect against drive failure. How likely is a drive to fail? It’s not just likely to happen. It will happen. If a single drive will on average fail in five years, then a single drive in a pool of 500 drives will on average fail in 1/100 of a year (or roughly two drives a week).

Without debate, I posit that it is not possible to make nightly backups of a petabyte storage cluster. Firstly, we’d need a second petabyte. Secondly, that’s a lot of data to move and the cluster needs to continuously run compute jobs (rendering). The solution is redundancy either through local machine (e.g., RAID 6) or through GlusterFS replication (analogous to RAID 10 but at the cluster level).

Petabyte Cluster with RAID-6

        ======= count ======  ========= cost ==========
Drive   HDD   Servers  Racks    HDD     Rack     Total
-----  -----  -------  -----  -------  -------  -------
2.0TB    700      100    8.3   98,000  268,000  366,000
1.5TB  1,087      156     13   56,000  416,000  472,000

Petabyte Cluster with RAID-10

        ======= count ======  ========= cost ==========
Drive   HDD   Servers  Racks    HDD     Rack     Total
-----  -----  -------  -----  -------  -------  -------
2.0TB  1,000      144     12  140,000  384,000  524,000
1.5TB  1,334      292     16   80,000  512,000  592,000

The drive count starts to really add leading to more frequent drive failures. With a RAID 10 (or the equivalent GlusterFS replication scheme), the operations team can expect to replace five to six drives per week.

But the larger question is, how many servers are needed for the compute cluster? What if rendering needed no more than 60 compute nodes? If we fixed the compute nodes count to 60, we would need to add more drives per server. For the sake of discussion, assume we could load 24 drives per server but that doubles the cost per server before including drive costs (i.e., 2 * $2,500 = $5,000 per server sans HDD).

Furthermore, assume we’re using GlusterFS replication for the storage cluster redundancy. This presses the drive count up but lowers the complexity of building and maintaining local RAID systems each with 24 drives.

Petabyte 60 Server Cluster with RAID-10

        ======= count ======  ========= cost ==========
Drive   HDD   Servers  Racks    HDD     Rack     Total
-----  -----  -------  -----  -------  -------  -------
2.0TB  1,000       60      5  140,000  160,000  300,000
1.5TB  1,334       60      5   80,000  160,000  240,000

There is a $60,000 capital cost difference between the two clusters. Drive failure rates are a third lower for the 2TB drive cluster but the larger drive costs more per GB.

Drive Failure Rate
(5 Year time to fail)
Petabyte 60 Server Cluster with RAID-10

       == failure cost ==   HDD   failrate  === month ===
Drive  HDD  labor  subtot  units   (days)   fails   cost
-----  ---  -----  -----   -----  --------  -----  ------
2.0TB  140     70  $ 210   1,000     1.825   16.4  $3,518
1.5TB   60     70    130   1,334     1.368   21.9   2,851

These number presumed that both drives had the same MTBF. Digging a bit further we find that the WD20EVDS claims 1 million hours MTBF and the ST31500341AS claims 750,000 hours MTBF. That is, the operations staff can expect the Seagate drives to fail at a rate 1/3 greater than that of the Western Digital drives.

Sidenote: The two drives are in different classes. The Seagate drive spins at a faster rate (7,200 RPM) and claims performance. The slower Western Digital drive (5,400 RPM) claims consistency and lower power. However, the slower rate is fine for the storage cluster which acts as secondary storage.

I will not attempt to sort the apples to oranges comparisons between the two drive manufacturers. I shall take my previous calculations and adjust the 1.5TB drive cost up by a third.

Drive Failure Rate
(Adjusted Fail Rate)
Petabyte 60 Server Cluster with RAID-10

                        original      adjusted
       fail    HDD   === month ===  === month ===
Drive  cost   units  fails   cost   fails   cost
-----  -----  -----  -----  ------  -----  ------
2.0TB  $ 210  1,000   16.4  $3,518   16.4  $3,518
1.5TB    130  1,334   21.9   2,851   29.2  $3,801

A reversal of recurring costs. Does it matter? No. Not really. In my opinion, it’s more important to minimize the day-to-day operation hassles. The three hundred bucks a month (one way or the other) is noise. The $60K difference in initial capital costs is significant but not as significant as reliable operations.

Rumor has it that both Seagate and Western Digital will soon release a 3TB drive.

Update 2010-12-17: Xbit Labs reports on Hitachi’s new sixth-generation perpendicular magnetic recording (PMR) which “enable 3.5″ hard drives with 4TB or even 5TB capacities.”

My final ponderings on this fantasy cluster looks at the impact of future HDD capacities. For this, I simply speculate on the cost per gigabyte. If you have pricing information more closely tied to reality, please let me know.

Drive Failure Rate
(unadjusted 5year rates)
Petabyte 60 Server Cluster with RAID-10 (or equivalent)

       $/GB   == failure cost ==   HDD   failrate  === month ===
Drive         HDD  labor  subtot  units   (days)   fails   cost
-----  -----  ---  -----  -----   -----  --------  -----  ------
5.0TB  0.100  500     70    570     400     4.564    6.6  $3,762
4.0TB  0.090  360     70    430     500     3.651    8.2   3,526
3.0TB  0.080  240     70    310     667     2.737   11.0   3,410
2.0TB  0.070  140     70    210   1,000     1.825   16.4   3,518
1.5TB  0.040   60     70    130   1,334     1.368   21.9   2,851

This isn’t the end of the tradeoff line. At some point, 3.5 inch HDD will yield to the 2.5 inch form factor. The larger larger drives just won’t be available. That dynamic will change the equation. GPU cards will become increasingly more capable. CPU core counts will increase. RAM costs decline. Fewer servers will be needed. Fewer racks. Less power. I’m sure in my naïveté I’ve underestimated much here. However, I do believe one day the entire data center used to build Avatar will fit inside a 40 foot shipping container. And then, some time later–but not much later–that compute power will shrink to fit in a 20 foot container. And so on. The important point is that the capital costs (exluding facilities) for this fantasy cluster is under a million dollars. And it gets cheaper by the day.

This system uses most of the Rampage III resources. The two Radeon cards will completely consume the PCI Express lanes (2 x16). The 24GB DDR3 will fill the six DRAM slots.

There are 7 SATA II and 2 SATA III ports.

The two SATA III ports connect the two SSD drives as a RAID Level 0. All non-user data is served from this drive (e.g., the operating system and benchmark applications).

One SATA II port connects the DVD writer.

Six SATA II ports connect the six HDD as a RAID Level 0. The HDD were selected for their cache (64MB), interface (SATA III, though connected to SATA II), spindle speed (7200 rpm, not as fast as 10,000 or 15,000 rpm but much, much cheaper) and price (cheap).

The two video cards were selected for being current and for being cheap (sort of).

Not shown in the picture are four 1920 x 1080 LCD monitors. These monitors pivot making them nice for a development (4320 x 1920).

Item 1                                         $  60
Antec Three Hundred Computer Case
Black Steel ATX Mid Tower

Item 2                                           180
CORSAIR AX850 850W Power Supply

Item 3                                           230
ASUS Rampage III LGA 1366 Intel X58
Micro ATX Intel Motherboard
N82E16813131658

Item 4                                           880
Intel Core i7-970 Gulftown 3.2GHz LGA 1366
130W Six-Core Desktop Processor
L2 Cache: 6 X 256KB
L3 Cache: 12MB
BX80613I7970

Item 5                                           225
Item 6                                           225
Patriot Gamer Series (3 x 4GB)
SDRAM DDR3 1333 (PC3 10666)
PGS312G1333ELK

Item 7                                            70
Item 8                                            70
Item 9                                            70
Item 10                                           70
Item 11                                           70
Item 12                                           70
Western Digital 3.5" Caviar
640GB 7200 RPM SATA 6.0Gb/s
Cache: 64MB
WD6402AAEX

Item 13                                          134
Item 14                                          134
Crucial RealSSD C300 2.5" SSD
64GB MLC SATA 6.0Gb/s
CTFDDAC064MAG-1G1

Item 15                                           10
SilverStone Bay Converter
mounting bracket 3.5" to 2 x 2.5"
SDP08

Item 16                                          185
Item 17                                          185
ASUS Radeon HD 6850
EAH6850 DirectCU/2DIS/1GD5
1GB 256-bit GDDR5 PCI Express 2.1 x16
EAH6850

Item 18                                           11
HIS CrossFire Bridge Interconnect Cable
HCFBC4065

Item 19                                          250
Item 20                                          250
Item 21                                          250
Item 22                                          250
Acer 1920 x 1080 LCD Monitor
B243H

Item 23                                           25
LITE-ON 24X DVD Writer Black
iHAS424-98

These are my notes made while looking for an Aikido dojo in the San Francisco Bay’s mid-peninsula region. Specifically the communities in and around Palo Alto, CA. (image: wikimedia.org)

[Update 2011-12-20: I have chosen to train at Aikido Center and started attending Zazen and Aikido classes in October 2011.]

I won’t get into the ‘why’ I’m looking for an Aikido dojo in this posting. Most of what I would say can be gleaned from Stan Wrobel’s excellent book, Aikido for Self Discovery: Blueprint for an Enlightened Life. I’ve included a short book review.

I made this handy google map of the Aikido dojos listed below. There is a KML file for the Google Earth crowd. Longitude and latitude coordinates were converted from the street addresses using capelinks.com.

I have included the Sensei for each dojo. It’s partly out of respect and partly out of a sense that the Sensei defines the nature of a particular dojo.

I met Doran Sensei once, briefly, some ten years ago. In those few minutes, he made a lasting impression. You cannot honestly talk about Aikido on the mid-peninsula without including Doran Sensei and his contributions.

I never met Kushida Sensei (he lives in Michigan) but I attribute his influence at Enbukan dojo. I trained for two years under a former student of Kushida Sensei and have respect for the schools under his watch.

The Aikido Center (aka Aikido Center of Mountain View) has been in its current location for many years. The dojo has a strong zen element. That is zen as in ‘zen practice’ not to be confused with ‘zen decor’.

Aikido of Mountain View has roots to the beginnings of Aikido in the area through Nadeau Sensei. I may be mistaken but I believe the dojo was once located on Charleston near what is now REI.

The Institute of Transpersonal Psychology (ITP) has a dojo but I’m under the impression that it is open only to students, faculty and staff. Ironically, I’m a Masters Program student at ITP but since I’m in the Global Program, I don’t attend classes on campus. I live nearby so maybe I will be eligible. In any event, if/when I find out more information, I’ll update the listing. Frager Sensei is also Dr. Robert Frager, co-founder (along with Dr. James Fadiman) of ITP. Aikido is an integral part of the ITP Resident Program.

I don’t know anything more about the remaining dojo than what I’ve read on their websites. I recommend reading their material first hand.

On the matter of dues (or tuition), I included the figures I found on their websites. I feel the amount of the dues is not really important. Note that all the schools charge about the same amount (hundred bucks a month, give or take). This is a really expensive part of the country; it is very expensive to operate a dojo here. My guess is that the dues keep the doors open. Barely.

Only the adult class schedule is given. Most schools have a separate children’s schedule on their website.

The following list is in alphabetical order by dojo name. The information reflects what was listed on each dojo’s respective website cira mid-November, 2010. Things change with time. Check with the school for the latest information.

Aikido Center
Shiohira Sensei

2560 Wyandotte Avenue, #A
Mountain View, CA. 94043

Monday      18:30-20:00        basic
            20:00-20:30        open
Tuesday     17:45-18:30        zazen ?
            18:30-20:00        basic
            20:00-20:30        open
Wednesday   18:30-20:00        beginners
            20:00-20:30        open
Thursday    17:45-18:30        zazen ?
            18:30-20:00        basic
            20:00-20:30        open
Friday      18:30-20:00        beginners
            20:00-20:30        open
Saturday    10:00-11:00        basic
            12:20-13:00        basic

$100/month

Aikido of Mountain View
Nadeau Sensei

1924 Plymouth Street
Mountain View, CA 94043

Monday      18:30-20:00        fundamental
Tuesday     18:30-20:00        basic
Wednesday   18:30-20:00        basic
Thursday    18:30-20:00        basic
Saturday    09:30-11:00        weapons
            11:00-12:30        basic
Sunday      11:00-12:30        basic

$100/month

Aikido West
Doran Sensei

3164 Bay Road
Redwood City, CA 94063

Monday      06:30-07:00        basics
            18:00-19:00        basics
            19:00-20:15        general
Tuesday     18:00-19:00        basics
            19:00-20:15        general
Wednesday   06:30-07:00        basics
            18:00-19:00        basics
            19:00-20:15        general
Thursday    18:00-19:00        basics
            19:00-20:15        general
Friday      18:30-20:00        general
Saturday    08:45-09:45        basics
            10:00-11:00        general
Sunday      08:30-09:45        weapons
            10:00-11:00        general

$95/month

Aikido@Noon
Hale Sensei

501 Laurel Street,
Menlo Park, CA 94025

Monday      12:00-12:50
Wednesday   12:00-12:50

$333/3months resident
 449/3months non-resident
(Through City of Menlo Park)

Enbukan Dojo
Kushida Sensei

209 West Evelyn Avenue
Mountain View, CA 94041

Monday      19:00-19:50        2
            20:00-20:50        3
Tuesday     18:15-18:55        intro
            19:00-19:50        1
            20:00-20:50        2
Wednesday   19:00-19:50        3
            20:00-20:50        2
Thursday    18:15-18:55        intro
            19:00-19:50        2
            20:00-20:50        1
Friday      19:00-20:30        open
            20:00-20:50        3

$90/month

Institute of Transpersonal Psychology
Frager Sensei

1069 East Meadow Circle
Palo Alto, CA 94303

?           ?                  ?

Tuition unknown

Rocky Valley Aikido
Heery Sensei
Tuazon Sensei

1211 Arbor Road
Menlo Park, CA 94025

Tuesday     19:00-20:00        St. Raymond School
Wednesday   17:30-18:30        Mitchell Park
Thursday    19:00-20:00        St. Raymond School

$60/month

Sierra Aikido
Levenbach Sensei
Bennett Sensei

2134 Old Middlefield Way, Suite A
Mountain View, CA 94043

Monday      19:00-20:00        weapons
Tuesday     12:00-13:00
Wednesday   19:00-20:00
Thursday    12:00-13:00
Friday      19:00-20:00
Saturday    11:00-12:00        weapons

$100/month

Stanford Aikido
Doran Sensei

Arillaga Family Sports Center
Wrestling Room
641 Campus Drive
Stanford, CA 94305

Monday      12:00-13:00
Tuesday     12:00-13:00
Wednesday   12:00-13:00
Thursday    12:00-13:00
Friday      12:00-13:00

$ 50/quarter  Student
 105/quarter  Stanford Faculty/Staff
 225/quarter  Non-Stanford Affiliated
  15/quarter  Anyone paying dues at Aikido West

I don’t know how long it takes to assemble the movie from source assets into a shipping product but I’ll venture it is quite a compute intensive process. I got the idea for this benchmark while reading on the sintel.org home page that the project is re-rendering the film for 4K and that it should be ready later this year (still a few months away). I didn’t know what 4K was so I looked it up. That lead me to compile a table of film formats and supported Frames per Second (FPS). I also appended three rows for HDTV of which only 720p and 1080p are real. 4320p is something bandied about as future but I couldn’t find material online that would lead me to believe it’s anything but a concept. I included it to define the upper envelope edge. (Note: different formats support different levels of FPS.)

Fomat   Width    Height    Frames per Second (FPS)
------- ------   ------  ----------------------------
2k 16:9 (2,048 × 1,152)  24, 25, 30, 50, 60, 100, 120
2K 2:1  (2,048 × 1,024)  24, 25, 30, 50, 60, 100, 120
2K ANA  (1,408 × 1,152)  24, 25, 30, 50, 60, 100, 120

3k 16:9 (3,072 × 1,728)  24, 25, 30, 50, 60
3K 2:1  (3,072 × 1,536)  24, 25, 30, 50, 60
3K ANA  (2,112 × 1,728)  24, 25, 30, 50, 60

4k 16:9 (4,096 × 2,304)  24, 25, 30
4K 2:1  (4,096 × 2,048)  24, 25, 30
4K HD   (3,840 × 2,160)  24, 25, 30
4K ANA  (2,816 × 2,304)  24, 25, 30

4.5k WS (4,480 × 1,920)  24, 25, 30

720p    (1,280 ×   720)  24, 25, 30, 50, 60
1080p   (1,920 × 1,080)  24, 25, 30, 50, 60
4320p   (7,680 × 4,320)  24, 25, 30, 50, 60

From this, I build a spreadsheet table of “Gigabytes per Second” of uncompressed data and converted the table into a set of data files compatible with gnuplot. Below are plots for 24 and 60 FPS for three formats.

I chose 24 FPS since it is a standard film frame rate. I excluded 25 and 30 FPS since they were so close to 24 FPS that they didn’t add any additional insight into designing the test. (25 and 30 FPS happen to be half of 50 and 60 FPS, which I discuss next). One datapoint to consider is that Blu-Ray supports 1080p at no greater than 24 FPS.

Just as the world is split between driving on the left or right hand side of the road, the world’s electrical power is split between 50 and 60 Hz. Neither is right or wrong but they are different and the two don’t mix well (like people driving on both the left and right side of the same road don’t mix well). I currently live in a 60Hz world so I biasedly chose the familiar but I could have easily chosen 50Hz. They are so close to each other in context of this exercise that the differences are negligible.

I chose two HD formats (4320p and 1080p) plus one film format (4K 16:9). The film format file size falls between the two HD formats. Note that 4K doesn’t support a frame rate obove 30 FPS and isn’t included in the 60 FPS graph.

Note that I haven’t included compression in this test as I believe it to be a different strain on the system.

My thoughts for the blender test was to establish a benchmark that would be inherently obvious and understandable to anyone, especially to those without any previous knowledge of video rendering or video formats. It’s more intuitive to say, “This system renders the video 1000 times slower than real time.” It also makes for a nice roadmap chart. Consider time on a linear x-axis and rendering ratio on a logrithmic y-axis.

A second roadmap milestone map could be what format/fps combination(s) achieve real time rendering status for a specific system on a specific date.

It would be interesting to see the performance of an ad hoc office cluster vs. a 40 foot shipping container of specialized hardware. If this sounds crazy, juxtapose any of the recent systems from Tom’s Hardware System Builder Marathon against the original IBM PC. (Or the ENIAC ;^)

In the conclusions section, I’d want to see analysis/conjecture about the test results regarding system bottlenecks. In an attempt to compare the systems, I’d also want to see the individual system price divided by the performance ratio. For example,

System A
Cost         $1200 USD
Ratio        0.0005245  (1830:1)
Cost/Ratio   2,196,000

System B
Cost         $1153 USD
Ratio        0.0005736  (1735:1)
Cost/Ratio   2,021,209

Cost Comparison
System A  : System B
    1,200 : 1,153
    1.040 : 1  (A is 4% more expensive than B)

Ratio Comparison
System A  : System B
    1,830 : 1,735
    1.055 : 1  (A is 5.5% slower than B)

Cost/Ratio Comparison
System A  : System B
2,196,000 : 2,021,209
    1.086 : 1  (A is 8.6% more expensive to
                to finish the same job as B)

If one starts to compare operating environments (Windows 7, OS X, Ubuntu, Fedora) on the same system and then repeats those tests across various systems (Dell, Apple, Whitebox), we start to get an apples to apples comparison in price, performance and price/performance ratios.

Note: the spreadsheet (numbers, exported to excel), data files, gnuplot scripts and images are available for download.

[update 2010-10-05: I just read at thenextweb.com that rendering Avatar requires 1 petabyte of drive space. That's in 3D but it still makes me wonder why there's a wide gap between my calculations of a hypothetical 2 hour movie and that of Avatar. The article at information-management.com gives a reference of 17.28 gigabyte/minute. At 166 minutes, this is 2.8 terabytes (a long way off from a petabyte). Perhaps there are a lot of intermediate stages for each frame which must be saved? Nevertheless, I believe the test is still interesting.]