Silician Sketchbook

Ninja edit: I could have sworn that I tried treating the data as an image before, but I suppose I had the dimensions reversed because it didn’t work out. On my way to figuring this level out. Details later.

Been hitting my head against level 30 of the Python Challenge. The hint forum seems quite dead — it has been a couple years since a new puzzle came out — and a lot of sites external to the solutions wiki fall short of level 30, so I figured that asking here is about as good as asking anywhere else.

Anyway, many of the puzzles don’t require specific use of Python, and this one of those, I think. Check out the CSV file. It’s not quite a perfect CSV because there’s a number missing from the last row, but treat it more as a list of floating point numbers. From the available hints, the starting point is to find the length of the list (7367) and obtain its factors (53 and 139, which are prime).

Now, we are supposed to be look at the data in a “different way” with the factors obtained. “Formula” is a term that’s thrown around a lot, and I just can’t see one. I mean, how might 0.82207, 0.91181, etc. be related to 53 and 139? One thing to consider is that the decimal is misleading, in which case how might 82207, 91181, etc. be related to 53 and 139?

I’d be interested in any thoughts on this.

Yeah, I’m one of them.

Usually if you’re coming into error correcting codes with no prior background (and parity bits doesn’t cut it), it’s best to just get a book on the topic. There aren’t that many references on the web that just tell you how to do it. A lot say what to do, but fail to provide details. To some extent, most times the details are boxed up in intellectual property cores or libraries so you don’t have to worry about them, but I was looking for at once a somewhat leaner and more specific implementation, plus a bit of education.

I found one that does a good job at both. Searching around eventually led me to a BBC white paper on Reed-Solomon coding that amounted to a gentle overview of the theory plus implementation.

Along with a couple references for multiplication over GF(256), I first wrote a multiplier function, and then used that to construct a 64 KB multiplication table. To all you veterans who frown at this seemingly inefficient approach, 64KB in memory is nothing when you have 2 GB it.

Now I’ve just got to write the rest of the forward error correction stack, and the subsequent decoder for it all.

Since getting my Inspiron last year, Dell has released a grand total of two driver updates for the NVIDIA 8600M GT. I was actually running a higher non-OEM version of ForceWare that had a fix for the lock-ups I experienced with Source engine games like Portal and TF2, and subsequently downgraded in the misguided belief that the first update would be somehow better.

Surprise, surprise, it was not. I then installed ForceWare 173.80 and have been with it ever since. I don’t know about the performance relative to other versions, but stability is what matters most at the moment, and I get the frame rates I need with an FPS config.

I installed Dell’s second update a couple days ago. It’s been a while, and it’s an OEM release, so I figured, why not.

I’m not really into benchmarks, but at least these new drivers aren’t any less stable. NVIDIA has fixed the TDR problem since late 2007, so it boggles the mind that Dell has been so slow on the uptake.

What I did notice was some potential problems with v-sync in that the frame rate gets cut in half the moment I enter into an open space, and my keyboard and mouse become really “heavy” due to the command lag. If the performance hit was that dramatic in the past, I didn’t notice it. I guess v-sync is getting disabled again.