Random Chitchat 2012-2016
Oh no, I meant, before even installing the powersupply into the computerTongue
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Use a multimeter? idkTongue
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I wonder if this thing would run MCServer acceptably Smile
http://www.tinydeal.com/mk808-16ghz-rk30...70725.html
[Image: 117940_882367_TTH-117940.jpg]

I've just given away my MK802, since its wifi was gone, it was of no use to me; brother-in-law seemed interested so maybe he can play with it Smile
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I'm currently fighting through the cNoise optimization, trying to figure the best way to attack it. At first I want to implement a 2D-only case, as a testbed for performance comparison. If it's found worth it, I'll expand it into 3D.
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Initial tests look very promising:
Code:
[0ef0|21:11:23] cCubicNoise generating 100 * 256x256 values took 1029 ticks (1.03 sec)
[0ef0|21:11:31] cNoise generating 100 * 256x256 values took 8198 ticks (8.20 sec)
So we get an 8-fold increase in the noise generator. But I still believe I can make that 10-fold, at least, there's a few tricks left up my sleeve Smile
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wow 8 times faster :O
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Well, it does NOT mean that generating will be that much faster; noise generation is only a part of the whole thing.
2D noise generation is about 10 % of the whole generating time, 3D noise generation is about 16 %. So if the noise speedup stayed at 8-fold, whole generating will speed up about 22 %.

But more importantly, it will allow us to make overhangs Smile
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:D overhangsBig Grin
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Silly me, I've been comparing performance in Debug mode again. Of course it needs to be done in Release.
So here's a Release mode comparison of the same algorithms:
Code:
[21:40:01] cCubicNoise generating 500 * 256x256 values took 670 ticks (0.67 sec)
[21:40:05] cNoise generating 500 * 256x256 values took 3678 ticks (3.68 sec)
So the speedup is "only" 5.5x.

However, after two more rounds of code optimizing, I was able to squeeze out some more:
Code:
[21:52:49] cCubicNoise generating 1000 * 256x256 values took 1138 ticks (1.14 sec)
[21:52:56] cNoise generating 1000 * 256x256 values took 7403 ticks (7.40 sec)
[21:52:56] New method is 6.51x faster

Oh yeah! Wink
Code:
[22:31:47] cCubicNoise generating 1000 * 256x256 values took 701 ticks (0.70 sec)
[22:31:54] cNoise generating 1000 * 256x256 values took 7404 ticks (7.40 sec)
[22:31:54] New method is 10.56x faster
(Just changed datatype from double to float)

I think I've hit the sweet spot now:
Code:
[22:38:19] cCubicNoise generating 1000 * 256x256 values took 686 ticks (0.69 sec)
[22:38:27] cNoise generating 1000 * 256x256 values took 7403 ticks (7.40 sec)
[22:38:27] New method is 10.79x faster
Changed datatype back to doubles, but re-implemented the CubicInterpolate() method for doubles, thus eliminating the conversion back and forth between doubles and floats.
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Impressive :O
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