Computing power of AI graphics card

1.

The types of chips that provide computing power for AI include GPU, FPGA and ASIC

GPU is a kind of microprocessor specialized in image operation on personal computers, workstations, game machines and some mobile devices (such as tablet computers, smart phones, etc.). It is similar to Cu, except that GPU is designed to perform complex mathematical and geometric calculations, which are necessary for graphics rendering

FPGA can complete any digital device function chip, even high-performance CPU can be implemented with FPGA. In 2015, Intel acquired the FPGA long alter head with us $16.1 billion. One of its purposes is to focus on the development of FPGA's special computing power in the field of artificial intelligence in the future

ASIC refers to the integrated circuits designed and manufactured according to the requirements of specific users or the needs of specific electronic systems. Strictly speaking, ASIC is a special chip, which is different from the traditional general chip. It's a chip specially designed for a specific need. The TPU that Google recently exposed for AI deep learning computing is also an ASIC

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chips are also called integrated circuits. According to different functions, they can be divided into many kinds, including those responsible for power supply voltage output control, audio and video processing, and complex operation processing. The algorithm can only run with the help of chips, and because each chip has different computing power in different scenarios, the processing speed and energy consumption of the algorithm are also different. Today, with the rapid development of the artificial intelligence market, people are looking for chips that can make the deep learning algorithm perform faster and with lower energy consumption

2. Although both inside and outside the instry can feel the hot wave of artificial intelligence in recent years, in fact, artificial intelligence technology does not appear in recent years. Since the 1950s and 1960s, artificial intelligence algorithms and technologies have been hot for a time. With the development of time, they continue to evolve and evolve, and have experienced a process from heat to decay
in recent years, artificial intelligence has made everyone feel its very hot and sustainable development. Therefore, we believe that this round of rapid development of artificial intelligence benefits from the rapid development of IT technology over the years, which brings computing power and computing distance to artificial intelligence, so as to provide support for artificial intelligence algorithms
in recent years, the research and development of artificial intelligence technology and various artificial intelligence applications by enterprises have been continuously implemented, which directly promotes the rapid development of the overall artificial intelligence instry. The overall scale of the core instry of artificial intelligence is close to 100 billion yuan, which can be said to be one of the instries with huge scale. Moreover, from the perspective of future development trend, it is estimated that this year, the overall market scale will reach 160 billion yuan, so the growth rate is still very fast
What are the advantages of deep learning
in order to recognize a certain pattern, the usual way is to extract the features of the pattern in a certain way. This feature extraction method is sometimes designed or specified manually, and sometimes summed up by the computer itself under the premise of relatively more data. Deep learning puts forward a method to let the computer automatically learn the pattern features, and integrates the feature learning into the process of modeling, so as to rece the incompleteness caused by artificial design features. At present, some machine learning applications with deep learning as the core have achieved the recognition or classification performance beyond the existing algorithms in the application scenarios that meet specific conditions
if you are interested in artificial intelligence and deep learning, you can take a look at the AI deep learning courses jointly organized by China public ecation and Chinese Academy of Sciences, both of which are taught by experts of Chinese Academy of Sciences in person

3. In addition to big cloud factories at home and abroad, you can also rent physical machines. Lin Haitian has this business, which is more suitable for companies and enterprises, or for developing 5g projects, such as running data, doing experiments, or renting from big factories

4. In theory, it's perfectly possible. After all, that's how the graphics card was used to run and calculate when mining was considered. After all, these problems need to consider how to set up the software, not whether the graphics card can be used.

5. Is more intelligent deployment of graphics card performance, better play the role of graphics card

6. Public toilets that professional computer configuration requirements, this configuration requirements, you can do according to the regular manual test professional computer.

7. 1650 is still one of the mainstream graphics cards, which can easily drive this major.

8. If you pay attention to AI processing well, you can also optimize the game processing and save CPU!

9. NVIDIA AI denoiser is the exclusive RTX platform of RTX series, which integrates real-time ray tracing, artificial intelligence, programmable coloring and other technologies
the use of NVIDIA AI denoiser requires geforcertx20 Series graphics cards, which are supported as long as the graphics card model is geforcertx20xx.