Googling for "conway's game of life" gives a simulation in the results page

Glad you liked it. I'm glad people are finding out about this and think it's as cool as I do.

Meeeeee, too. Me, too. Believe me, I tried.

I figured caching the results of common patterns appearing in blocks of 2x2, 3x3, 4x4, etc. pixels which are surrounded by all 'off' pixels, you can easily skip many repetitive calculations.

  ----    ----
  -oo- =\ -oo-
  -oo- =/ -oo-
  ----    ----

  -----    -----    -----
  --o--    -----    --o--
  --o-- =\ -ooo- =\ --o--
  --o-- =/ ----- =/ --o--
  -----    -----    -----

  ------    ------    ------
  -oo---    -oo---    -oo---
  -oo--- =\ -o---- =\ -oo---
  ---oo- =/ ----o- =/ ---oo-
  ---oo-    ---oo-    ---oo-
  ------    ------    ------

Since repeating patterns tend to turn up a lot on their own in CGoL they would end up cached, and large blocks of n cells could be computed in 1 move rather than requiring o(8n) time. That seems to be how Hashlife works: http://en.wikipedia.org/wiki/Hashlife

I've seen a detailed explanation of a very sophisticated implementation of GOL in java (using caching, cycle detection and similar things), but I can't find it right now. Damn.

Edit: found it http://www.ibiblio.org/lifepatterns/lifeapplet.html

I tend to think of cellular automata optimization as being related to data compression. This is also a simple concept with no simple solution, and what solutions are best depends on the type of data being processed. In Conway's Life, patterns tend to be blobby.

For blobby universes, one should probably consider dividing the universe up into blocks approximately the size of the blobs. For Life, 4x4 to 8x8 seem reasonable. I chose the upper bound, 8x8, for reasons of convenience: There happen to be 8 bits in a byte. I strongly considered 4x4, but it didn't work out as nice....

You should put the blocks in some kind of list, so that you waste zero time in the empty parts of the universe.

Already, note a complication: New elements in the list must be introduced if the pattern grows over a block's boundaries, but we have to know if the block's neighbor already exists. You can either do a simple linear search of the list, or binary search, or keep some kind of map. I chose to make a hash table. This is solely used for finding the neighbors of a new block; each existing block already keeps a pointer to its neighbors, as they will be referenced often.

There must also be an efficient algorithm within the blocks. I chose to primarily blaze straight thru each block. There are no inner loops until all cells in a block are processed. Also, fast-lookup tables are employed. I look up 4x4 blocks to determine the inner 2x2.

Note: CA programs typically consist of 2 main loops (plus a display loop), because CA rules operate on the cells in parallel, while the microprocessor is conceptually serial. This means that there must be two copies of the universe, effectively, so that no important info is destroyed in the process of creating the next generation. Often these 2 copies are not symmetrical. It was a great struggle for me, since almost every time I took something out of one loop to make it faster, I had to add something else to the other loop! Almost every time, that is; the exceptions to that rule lead to the best optimizations. In particular, there are good tradeoffs to be considered in bit-manipulations: shifting, masking, recombining to form an address in the lookup table....

It can also be considered that sometimes the contents of a block may stabilize, requiring no further processing. You could take the block out of the list, putting it in a "hibernation" state, only to be re-activated if a neighboring block has some activity spilling into it. These blocks would take zero processing time, just like a blank region of the universe.

Period-2 oscillators might also not be very difficult to detect, and remove from the processing time. This might be worthwhile in Life, because the blinker is the most common kind of random debris. Higher period oscillators are much more rare. It is also possible that gliders could be detected and simulated. You will get diminishing returns from this kind of optimization, unless you take it to an extreme (cf. HashLife).

Also, a block of cells that's completely empty might not be worth deallocating and removing from the hash table for a while. That takes some processing time, which could be significant in the case of an oscillator moving in and out of its space repeatedly. Only when memory gets low should the oldest blocks from the "morgue" be recycled.

When the program is fast enough, it should be considered that it isn't worth displaying generations any faster than the eye can see, or at least not much faster than the refresh rate of the monitor. Especially in windowed environments, display time can be a real bottleneck.

I think listlife is a simple and efficient algorithm: http://dotat.at/prog/life/life.html

Some years ago I implementend something similiar in javascript: http://pmav.eu/stuff/javascript-game-of-life-v3.1.1/

The benchmark can be really slow in some steps.

Hehehe

It's possible that not all of the co-workers he showed were engineers.

I find it interesting that your metric of smart is whether or not someone has knowledge of the Game of Life.

As a small counterpoint, when I interviewed at Google, one of the interviewers asked me how I might design an app to play the Game of Life, starting with simple cases and scaling up to boards with millions and millions of cells (so it was secretly about designing a distributed computation system, I think).

I would bet that 95% of Google SWEs have heard of the Game of Life, but you can be an exceptionally good software engineer without that knowledge. It's usually considered recreational mathematics, which is a small or non-existent part of most core university CS curriculums, and not everyone in the field explores such topics outside of their formal work or studies.

Also, their interview process is usually not 3 months. Most engineers have a 45-minute phone interview or two, followed by a day of onsite interviews lasting 4-5 hours.

The only reason I've heard of it is that they had the Martin Gardner essay collections at my library growing up.

'Knowing' algorithms is hardly great.

Most of them who cleared it might be kind of guys who read interview questions on programming forums every day and master the art of gaming interviews.

Found it and beautified is as much as I could. Really tough to read still: http://cl.ly/K74W

I guess, in the same sense that the implementation of any local binary executable is "all there" because you could theoretically figure out what all the machine code does. (But granted, I'm sure that reverse-engineering obfuscated JS is generally much easier than reverse-engineering a binary.)

Was under the impression the whole thing was - just didn't notice it at first and had a bit of a woah moment :)

It appears that there is some sort of spawning behavior near the darkened "Google" tiles. I paused, turned off all the cells in the region (taking into account wrapping from the other side) and let it go. Cells started activating near the 'e'.

Same for binary & hexadecimal. Man, those guys are engineers indeed. Always going the full mile...

It's basically an alias for 1.

https://www.google.com/search?q=number+of+horns+on+a+unicorn...

I know there are a ton more phrases that work as calculator aliases, but I can't think of any off the top of my head.

And the rebuttal, "Yes, I want to be writing Game of Life easter eggs"

A Game of Life type visualization of this algorithm would be interesting. It might go something like:

  The seed of the system is a random cluster of N stories (cells)
  that represent the "front page".

  Each cell has votes and topics (Erlang, Apple, X in CSS, etc.).

  1. Any cell with fewer than N votes, 
     and fewer than two neighbors dies 
     (due to lack of interest and/or promotion).

  2. Any cell with two or three live neighbors,
     lives on to the next generation
     (riding along the front page wave).

  3. Any cell with more than three live neighbors,
     that share the same topic dies
     (due to overexposure of the topic).

  4. Any dead cell with exactly three live neighbors,
     becomes a live cell with a topic shared by one of the neighbors
     (the spread of interest of a topic).

  After any generation, votes and stories can be added. 

  The low threshold of votes (N), is determined to be
  some percentage of all votes in the system.

Tempted to make this for fun now...

Every time you do a query on W|A you see a brief animation of the game of life while the result is loading. I was referring to that.

(and my comment was meant tongue in cheek)

Hehe, yeah, I tried explaining too, with all my passion, she just stared at me and said: "I have a nerdy husband" -_-'

I'll give it another shot with that link, perhaps tomorrow :)

Very, very subtle. I had to adjust the angle of the screen

And set an inconspicuous user agent!

working in FF for me:)