Rx6000 Ethereum computing power

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. Rx470 and rx570 are the most cost-effective ones (before 1500), and their mining performance is no worse than 480 and 580, but they are much cheaper. We can also consider the lower 460 and 560, and other models are not worth considering.

3. 7x Tang Bohu's office has a task to learn proction. You can choose a place nearby to learn proction. There are four kinds: pig raising, fish raising, mining and tree planting. One can only learn one. Go to spring, summer, autumn and winter to get the seeds, go around to find the corresponding places to start proction, and finally get the core of earth and other items, and go to the refiner to refine the crystal of earth, After collecting the four crystals, you can synthesize them in the refiner. The light of miracle is OK. Other market prices are very low, so there's no need to combine them

4. I feel that DERO coin is good, it greatly improves the privacy and security, and greatly reces the operational risk of participants. If you are interested, I suggest you take a look at the coin dragon website

5. Let me give you a more reliable one for Amway, coin dragon. It is the world's leading digital asset trading. I have been trading all kinds of digital currencies on coin dragon. Of course, DERO is one of them.

6. It's not that the graphics card is too new. Every time NV releases the graphics card, there will be a corresponding driver.
in your case, it's either the quality of the graphics card or the old version of the driver you downloaded.
try the driver wizard

7. About CUDA:

CUDA (Compute Unified Device Architecture) is a new infrastructure, which can use GPU to solve complex computing problems in business, instry and science. It is a complete GPGPU solution, which provides direct access interface to hardware instead of relying on graphical API interface to achieve GPU access. In the architecture, a new computing architecture is adopted to use the hardware resources provided by GPU, which provides a more powerful computing power than CPU for large-scale data computing applications. CUDA uses C language as programming language to provide a large number of high-performance computing instruction development capabilities, which enables developers to build a more efficient data intensive computing solution based on the powerful computing power of GPU<

about NVIDIA CUDA technology
NVIDIA CUDA technology is the only C language environment for NVIDIA GPU (graphics processor) in the world, which brings infinite graphics processing performance to NVIDIA GPU (graphics processor) supporting CUDA technology. With NVIDIA CUDA technology, developers can use NVIDIA GPU (graphics processor) to overcome extremely complex and intensive computing problems, and apply it to such fields as oil and gas development, financial risk management, proct design, media image and scientific research< br />CUDA™ Toolkit is a C language development environment for GPU (graphics processor) supporting CUDA function. CUDA development environment includes:

nvcc C language compiler
CUDA FFT and Blas library for GPU
analyzer
GDB debugger for GPU (alpha version launched in March 2008)
CUDA runtime driver (currently available in standard NVIDIA GPU driver)
CUDA Programming Manual
the CUDA developer's software development kit (SDK) provides some examples (with source code) to help users start CUDA Programming. These examples include:

parallel bimodal sorting
matrix multiplication
matrix transpose
performance evaluation with timer
prefix and (scan) of parallel large array
image convolution
one dimensional DWT using Haar wavelet
examples of OpenGL and Direct3D graphics interoperability
examples of CUDA Blas and FFT library
CPU-GPU C - and C + + - codes Integrated
binomial option pricing model
Black Scholes option pricing model
Monte Carlo option pricing model
parallel Mersenne twister (random number generation)
parallel histogram
Image Denoising
Sobel edge detection filter
MathWorks matlab & reg; Plug in (click here to download)
the new SDK paradigm based on CUDA version 1.1 has now been released. To view the complete list and download the code, please click here<

technical functions
provide standard C programming language on GPU
provide a unified software and hardware solution for parallel computing on NVIDIA GPU supporting CUDA
CUDA compatible GPU (graphics processor) includes many: from low-power notebook GPU to high-performance, multi GPU system< The GPU (graphics processor) supporting CUDA supports parallel data cache and thread execution manager
standard FFT (fast Fourier transform) and Blas (Basic Linear Algebra Subroutine) numerical library
Special CUDA driver for computing
optimized direct upload from central processor (CPU) to GPU (graphics processor) supporting CUDA Download channel
CUDA driver can interoperate with OpenGL and DirectX graphics driver
support Linux 32-bit / 64 bit and windows xp 32-bit / 64 bit operating system
for the purpose of research and development language, CUDA provides direct access to driver and assembly language level access.

8. In terms of hardware, NVIDIA started to support CUDA technology from geforce9xxx Series graphics card, namely G92 / G94 / G96 core. The former g80 core series can also partly support CUDA technology, but the performance efficiency and software compatibility are not perfect
however, through the optimization of the driver level, NVIDIA enables all the procts starting from geforce8xxx series to support CUDA general computing technology. That is to say, starting from the core of g80 / g84 / g86, future procts support CUDA technology.

9.

CUDA core. Theoretically, the abbreviation of stream processor is sp. But NVIDIA itself calls their SP CUDA core

CUDA core is just an n-card stream processor, just a stream processor term

CUDA is a unified computing architecture, which belongs to software + hardware architecture. It's not a piece of software, it's not a piece of hardware. It's a combination of software and hardware

you can understand that CUDA is a special computing system customized by NV based on NVIDIA GPU platform. It's an algorithm invented by NV itself, which can play the most efficient role in NV platform and software support. CUDA is defined as a kind of C language in NVIDIA, which is compatible with C language. Although CUDA is an independent language to provide development learning, the gap between CUDA and C is not very huge. Many experienced developers can learn it quickly

CUDA belongs to NVIDIA private ecological zone in the world, and its influence is no less than IOS. Even in high-end computing and graphics. CUDA is an authoritative standard. Quadro and Tesla, two famous computing platforms that dominate the world, rely on CUDA ecological zone to provide integrated customer services. Otherwise, if everyone only sells a high floating-point physical node like AMD, then Lao Huang doesn't dare to call himself a visual computing company. Isn't that authorized by ordinary semiconctor companies

CUDA is a computing structure and an idea. It's a hard and soft platform, and it's something that NV provides comprehensive services. It's not a graphics card license, it's not a cluster. It's not a driver