Bitcoin mining difficulty (Bitcoin) Announced in China Combat mining operations, At its peak, contributed three-quarters of the world’s computing power.Newest data Data from BTC.com shows that starting from June 17, 2021, the difficulty of Bitcoin mining has continued to soar.
As miners from China slowly settled in cryptocurrency-friendly areas, the mining difficulty of the Bitcoin ecosystem rose by 13.77% for two consecutive times, exceeding 15 terahash (T) for the first time since the second week of June. It is expected that the next adjustment will begin on August 27, and it is estimated that the difficulty will soar to 15.63 terahash.
Before China cracked down on local miners, Bitcoin’s mining difficulty reached a peak of 25 terahash. The sudden decrease in the number of miners in China has reduced competition for confirmation of blocks. This allows existing miners on the network to obtain higher profits.Data from Statista show China’s contribution to Bitcoin mining has been reduced to nearly 46%, while the United States has filled the vacancy and owns nearly 17% of the global mining power.
At CNBC cover area In this matter, Quantum Economics cryptocurrency analyst Jason Deane emphasized that the network’s latest difficulty adjustment mechanism has reduced the profit of mining bitcoin by 7.3%.
At the end of the discussion, Mike Colyer, CEO of the New York-based Digital Currency Group, said:
“A large number of machines from China need to find a new home.”
Colyer also believes that the new generation of mining machines are more efficient and “double the computing power with the same amount of electricity.”
related: As the main miners are back online, the Bitcoin hash rate rebounds
Due to energy issues, China’s opposition to Bitcoin mining is considered to be Electricity consumption of mining operations. After the suppression, Canada, Kazakhstan, Russia The United States is the best choice for migrating bitcoin miners. As Cointelegraph reported, Bitcoin’s hash rate rises It will eventually translate into higher computational costs.