Quote from: DeathAndTaxes on March 16, 2012, 07:08:39 PM

1) 58.2 TFlop is pathetically weak for a super computer. A 5970 graphics card has about 4.6 TFLOPs. So it is roughly equal to the floating point math calculations of ~12 5970 GPUs (4x that if it is double precision).

3) The largest super computers in the world is 11,280 TFLOPs. http://i.top500.org/system/177232

That seems to be an explanation, although it seems weird that you can already create a more powerful (in terms of flops) machine with a number of GPUs that is affordable for a hobbyist. Maybe raw processing speed is not the most expensive factor in supercomputers anymore? That weather forecast thing also has a huge amount of RAM, and probably some high-speed inter-computer connections as well.

Quote from: kjj on March 16, 2012, 07:13:15 PM

Comparisons between integer and floating point operations are meaningless. Not just inaccurate, or merely approximate, but not even in the same universe.

I disagree with that. You can always emulate floating point operations on top of integer operations, or integer operations on top of floating point operations. This places an upper and lower bound on the speed ratio between floating point and integer operations, which is basically independent of the hardware you are using. I don't really know how big the gap is between the upper and lower bound, but at least I can say from experience that emulated floating point can be relatively fast(*).

Quote from: kjj on March 16, 2012, 07:13:15 PM

Just the Xeon CPUs in that Dutch thing are capable of finding a block every 30 hours or so, or about 40 BTC per day. Presumably, that is more than 12 euros.

I used an exchange rate of about 4EUR/BTC, so your value would correspond to about 160 EUR/day.

If you are correct, then how is that possible? Wouldn't they be able to have more FLOPs than they report even by doing emulated floating points on the Xeons?

Or does bitcoinwatch.com use an unrealistic estimation of the FLOPS / hashes ratio? I see in an earlier post that they use 1 INTOP = 2 FLOP. So it assumes integer is actually slower than floating point? But even if it is 4 INTOP = 1 FLOP for floating point emulation, you'd still only lose a factor 8, which is less than needed to explain the ratio between 12 EUR/day and 160 EUR/day.

(*) I did some speed measurements on an ARM 7 without floating point unit and a Pentium 3 or 4 with floating point unit. On the ARM, emulated floating point operations (addition and multiplication) were actually faster w.r.t. integer operations than the hardware-accelerated floating point w.r.t. integer on the Pentium (TfloatARM / TintARM < TfloatIntel / TintIntel). I did not use things like SSE on the Pentium.