Bitcoin and Cryptocurrency Technologies

Disadvantages of GPU mining. ​GPU mining has some disadvantages. GPUs have a lot of hardware
built into them for doing video processing that can’t be utilized for mining. Specifically, they have a
large number of floating point units that aren’t used at all in SHA‐256. GPUs also don't have the
greatest cooling characteristics when you put a lot of them next to one another. They’re not designed
to run side by side as they are in the picture; they're designed to be in a single box doing graphics for
one computer.
Miners vs. Gamers.​According to folklore, by 2011 Bitcoin miners were purchasing enough GPUs to
upset the normal market. This caused friction with the gaming community who found it increasingly
difficult to find certain popular GPUs in local electronics stores. Interestingly, however, it may have
increased interest in Bitcoin mining as many of these frustrated gamers learned about the currency
to understand where all the GPUs were going, with some of gamers becoming miners themselves!
GPUs can also draw a fairly large amount of power, so a lot of electricity is used relative to a
computer. Another disadvantage initially was that you had to either build your own board or buy
expensive boards to house multiple graphics cards.
On a really high‐end graphics card with aggressive tuning you might get as high as 200 MH/s ​ , or 200
million hashes per second, an order of magnitude better than you would be doing with a CPU. But
even with that improved performance, and even if you're really enterprising and used one hundred
GPUs together, it would still take you over 300 years on average to find a block at the early‐2015
difficulty level. As a result, GPU mining is basically dead for Bitcoin today, though it still shows up
sometimes in early‐stage altcoins.
FPGA mining. ​Around 2011 some miners started switching from GPUs to FPGAs, or Field
Programmable Gate Arrays, after the first implementation of Bitcoin mining came out in Verilog, a
hardware design language that’s used to program FPGAs. The general rationale behind FPGAs is to try
to get close as possible to the performance of custom hardware while also allowing the owner of the
card to customize it or reconfigure it “in the field.” By contrast, custom hardware chips are designed
in a factory and do the same thing forever.
FPGAs offer better performance than graphics cards, particularly on “bit fiddling” operations which
are trivial to specify on an FPGA. Cooling is also easier with FPGAs and, unlike GPUs, you can
theoretically use nearly all of the transistors on the card for mining. Like with GPUs, you can pack
many FPGAs together and drive them from one central unit, which is exactly what people began to do
(see Figure 5.8). Overall, it was possible to build a big array of FPGAs more neatly and cleanly than you
could with graphics cards.
Using an FPGA with a careful implementation, you might get up to a GH/s, or one billion hashes per
second. This is certainly a large performance gain over CPUs and GPUs, but even if you had a hundred
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