Calculation power measurement

1.

You can refer to the following, according to some commonly used graphics cards in the Internet bar market, sort out the price and calculation power of a related graphics card, as well as the expected return to the current period, It can be used as a reference:

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power consumption: 243w
computing power: 22.4m
price of graphics card: 1999 yuan
quantity of eth g every 24 hours: 0.015
revenue generated every 24 hours: 24.48 yuan
expected payback time: 81.66 days

power consumption: 159w
computing power: 24.3m
price of graphics card: 1599 yuan Yuan
number of eth g every 24 hours: 0.017
revenue generated every 24 hours: 27.9 yuan
estimated payback time: 57.31 days

total power consumption: 171w
computing power: 24.4m
price: 1999 yuan
number of eth g every 24 hours: 0.017
revenue generated every 24 hours: 27.87 yuan
estimated payback time: 71.73 days

< H2 > extended data:

Video card (graphics card) full name display interface card, also known as display adapter, is the most basic configuration of computer, one of the most important accessories. As an important part of the computer host, the graphics card is the equipment of digital to analog signal conversion, and it undertakes the task of output display graphics

the graphics card is connected to the main board of the computer, which converts the digital signal of the computer into an analog signal for the display. At the same time, the graphics card still has the ability of image processing, which can help the CPU work and improve the overall running speed. For those engaged in professional graphic design, graphics card is very important. Civil and military graphics chip suppliers mainly include amd (ultra micro semiconctor) and NVIDIA (NVIDIA). Today's TOP500 computer, including graphics card computing core. In scientific computing, graphics card is called display accelerator

2. The computing power of CPU is related to the number of CPU cores, the frequency of core and the ability of single clock cycle of core
the ability of double precision floating-point computing is commonly used to measure the scientific computing ability of CPU, that is, the ability to process 64 bit floating-point data

the processor supporting avx2 can perform 16 floating-point operations in one core and one clock cycle, Also known as 16flops
CPU power = number of cores x frequency of cores x 16flops
processors supporting avx512 can perform 32 floating-point operations in one core and one clock cycle, also known as 32flops
CPU power = number of cores x frequency of cores x 32flops

3. There must be such a subject as black hole simulation. I heard a report in 2009, that's what I did. I have other classmates doing it. Except for the celestial bodies; High energy physics. My friends are doing or have done scientific research requiring large-scale calculation, including: behavior of biological macromolecules, gene sequence analysis, gene expression pattern analysis, energy bands of various catalysts, finance, liquid properties, superconctors and other materials, geological activities, meteorology... Er... Such a list of discoveries should give me a scientific calculation that doesn't require a lot of computing power. I feel that many teachers are very greedy. The more computing resources, the better
hope to adopt

4. Computing power (also known as hash rate) is a measure of bitcoin network processing power. That is, the speed of computing hash function output for computer (CPU). Bitcoin networks must perform intensive mathematical and encryption related operations for security purposes. For example, when the network reaches a hash rate of 10th / s, it can perform 10 trillion calculations per second

in the process of getting bitcoin through "mining", we need to find its corresponding solution M. for any 64 bit hash value, there is no fixed algorithm to find its solution M. we can only rely on the computer's random hash collisions. How many hash collisions can a mining machine do per second is the representative of its "computing power", and the unit is written as hash / s, This is the so-called proof of work mechanism (POW)

recently, bitcoin's network computing power has entered the era of P computing power (1P = 1024t, 1t = 1024g, 1g = 1024m, 1m = 1024k). In the ever-increasing computing power environment, the arrival of P era means that bitcoin has entered a new stage of arms race

computing power is a measure of the total computing power of the unit that generates new blocks under certain network consumption. The single blockchain of each coin varies with the time required to generate a new transaction block.

5. Day trading is the day to buy the day you can sell
day trading is a way of foreign exchange trading. Usually, day trading refers to setting up and clearing positions on the same trading day. You can make several or even hundreds of such transactions in one day. It's up to you. There are four main steps for day trading through HPC: deciding to conct a foreign exchange transaction; Determine the currency and amount of the transaction and establish a position in your online account; Monitor your position; Close the position
If a friend wants to obtain additional income through foreign exchange,
it is suggested that a friend apply to become an HPC agent
so that his own transaction can not only rece the cost
but also obtain a high amount of additional income
becoming an agent can enjoy a high rebate of 40% to 50%
please contact me for the specific application process
I can help you strive for the highest standard
I wish you a happy transaction!

6. Computing power is a measure of the total computing power of generating new fast units under certain network consumption. If the computing power of the blockchain is insufficient, it is suggested to take a look at the tenth power computing power platform, which provides computing power leasing services.

7. (1) Computing speed is an important index to measure the performance of computer< (2) word length< (3) the capacity of internal storage< (4) the capacity of external memory.

8. As the main CPU, the main operations are as close as possible to the approximate value within the allowable range, FPU is mainly engaged in floating-point operation, formerly known as coprocessor. 486 was not included in CPU before (8086 ~ 808780286 ~ 8028780386 ~ 80387 = 80386DX, 80486sx ~ 80487 = 80486dx, 586 = 586 + 587...) floating-point operation is a high-precision operation mode, which is mainly used in science and multi-media. It can be understood as the operation mode of movable decimal point. Current speed amd & gt& gt; Inter

integers refer to positive integers, negative integers and zeros, such as - 6, 0, 32, etc
floating point numbers refer to rational numbers with finite decimal places, such as -10.8, 0.00, 25.01, etc
integers can be either integers or floating-point numbers. For example, 255 is an integer and 255.0 is a floating-point number
integer operation, the result is an integer, and the decimal part of the result will be ignored. For example: when using integer operation, 100 ÷ 3＝33
the result of floating-point operation is a floating-point number, and the decimal part of the result will be retained
for example, when floating point operation is used, 100.0 ÷ 3.0=33.33333333

for example, when a bullet hits the wall, a piece of soil falls. If the floating-point operation is strong, it may also be able to show the st< So AMD CPU is better than Intel. It's good to play games

9. GPU is mainly used for graphics rendering. Some people say that the performance of GPU is 40 times that of CPU, which is not comprehensive. If we just say that GPU is 40 times that of CPU in parallel and intensive floating-point operations, it may be feasible (I don't think it's such an exaggeration. It's amazing that the best GPU can be 10 times that of the best CPU. Moreover, now CPU has multi-core, This greatly improves the operation of CPU, and GPGPU seems to be limited to single core, but it is groundless to say so in terms of full operation. In fact, it is still very difficult to use GPU as a general processor, and the most important thing is that GPU is specially designed to process graphics, so its programming language architecture and programming environment are difficult to be universal. When GPU runs non graphic programs, it often needs to rely on extremely complex algorithms and more tortuous processes. The powerful computing potential of GPU is often exhausted in such a circuitous process. In addition, e to the lack of unified API and driver support, GPU developers have to develop the corresponding version for each GPU architecture, which makes it more difficult to promote the project of GPU as a common processor.