Powerful graphics card
21.5 * 3600 seconds * 24 hours = 1857600 M / day
1857600 / 1024 / 1024 = 1.7715 T / day
a t of computing power / day can dig bitcoin worth 4.03 yuan
1.7715 * 4.03 = 7.14 yuan / day
since 2017, bitcoin has reached new heights. Yesterday (May 23), the value of bitcoin broke through the ￥ 16000 mark, hyping virtual currency, becoming a matter that the general public can participate in, And a little bit of technical level, both fried money, but also began to have the technical content of mining
as we all know, virtual currency has a numerical peak, the more difficult it is to dig. In fact, it's hard to judge whether to lose money or not if we continue to dig. Therefore, in the end how to dig, dig what can be the fastest back to this, this paper studies the above two core issues based on the current market situation
2. Different mining softwares have different algorithms and ranking.
it is common in mining software, but the ranking will be different for different algorithms.
a card, that is to say, it depends on the frequency and SP
,
the better the a card, the stronger the mining.
high performance means that you don't need graphics effects to play, but sacrifice the graphics effects for 3D flow smoothness.
high quality means that it is just the opposite of performance, It is to sacrifice fluency for better picture effect
the default is high performance. N-card driver has been doing very well, that is, n-card common practice is to sacrifice the picture for fluency.
you are a low-end graphics card, so it is recommended that the default is good, the default is to sacrifice the picture, at least you can play, this practice is also desirable
At present, blockchain training courses in the market span a lot, and the course content and teaching form are also varied
mainly used in scientific computing, video rendering, video processing and other fields
in our daily use of computers, we seldom use the general computing power of graphics card, which has little impact.
CPU is mainly serial instruction optimization. The current multi-core CPU is suitable for a large number of parallel simple operations for instruction set parallelism and task parallelism
GPU, and for data parallelism
if it is repetitive operation with little data correlation, GPU has advantages
simple understanding:
CPU is equivalent to several professors working together
GPU is equivalent to a large group of primary and secondary school students working together