American engineers have come up with a way to increase the profitability of mining bitcoins by 30%

Dr. Rakesh Kumar of the University of Illinois at Urbana-Champaign in his work " Mining Bitcoins with approximation " described a mechanism by which you can increase profits from mining Bitcoins by 30% - in terms of unit processor power. The method is based on the use of approximate calculations - if we assume the appearance of a small number of errors, the resulting efficiency of calculations increases.

Approximate calculations are often used in science to simplify mathematical calculations. Dr. Kumar calculated that using iron, which counts with a certain, but not 100% accuracy, it is possible to increase the mining efficiency by 30%.
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When mining bitcoins, it is necessary to calculate hashes from some initial values . It is necessary to obtain a hash of a certain type, and since it is impossible to predict the type of hash before its calculation, it is necessary to carry out calculations, and thereby prove that the processor time has been spent.

In connection with the constant planned increase in the complexity of bitcoin calculations, miners gradually switched from CPU to GPU, FPGA or ASIC. Increasing complexity requires increasing the energy consumption of processors. Kumar and his students thought about it - is it possible to understand the technology of mining and reduce energy consumption by increasing profits?

As a result, they turned to the idea of ​​approximate calculations. According to Kumar, quite a few applications running on a computer — for example, visualization — are
can work with calculations that are not 100% accurate. Such programs are error tolerant and can safely work even on an inaccurately working hardware. Researchers found that bitcoin mining has the same properties and “forgives” some inaccuracies.

The researchers found that the processor, which is obliged to guarantee 100% accuracy of operations, in some cases consumes 2 times more energy than the processor, which should produce 99% accuracy.

Mining of bitcoins can be performed in several parallel processes, and the iron used for this purpose consists of independent modules. If any of the modules makes a mistake, it does not affect the work of others.

As Kumar explains, mining errors can be of two types - the right decision, which was mistakenly considered wrong (false-negative), and wrong, wrongly taken as correct (false-positive). Since the probability of finding the right solution is very small, then false-positive can be neglected - there will be few of them. And you can still send them to the network — they will still be checked and other miners will exclude them when updating the block chain. A false negative decision is a missed opportunity - the right decision that has not been implemented.

Dr. Kumar argues that the use of iron, which considers hashes approximately, will allow to pack more modules in the same space, as compared to ordinary iron. As a result, the time for calculating the hash is halved - the miner can generate twice as many hashes per unit of time. Due to periodic errors, actual performance increases by about 30%.

The report based on his work, Dr. Kumar will do in June 2016 at a conference on the design of electronics and automation.