What does a GPU server do?

A lot of people have actually heard ofserver (computer)The server belongs to the IT infrastructure, very important facilities, the need to carry different numbers of people traffic access, which has strict requirements for the server, to be able to fast throughput, stability and the ability to run for a long time. And today we are talking about GPU servers, but we should be a little confused, GPU servers are a class of servers, is more suitable for business use of a server, cost-effective, the following take you to understand what GPU servers.

GPU serverIt is GPU based application for video codec,deep learningThe GPU has excellent graphics processing capabilities, and also has the ability of high-performance computing, in the same server products, the efficiency of computing processing is more competitive. Enterprises generally choose servers most of the choice of GPU servers, if the use of the demand is not so high, the choice of ordinary servers is also possible, generally in the purchase of the time will be based on their own needs to choose the configuration.
GPU servers have very powerful computing power, is able to become a deep training platform for machines, GPU servers are models with the ability to help machines from simple training to deep training. So a lot of machine learning will use GPU servers.
GPU servers have gas pedal instructions that allow thousands of cores to be used by the user, which can help the user to speed up the rendering speed of graphic images in the workplace. Compared to normal servers, theGPU serverPerformance is more able to meet the needs of users, and in terms of stability is not ordinary servers can be compared.
GPU servers are capable of handling a lot of work scenarios. If the enterprise uses the server more frequently and has higher configuration requirements, then it is more recommended to choose GPU servers. Because of the processing power of the work, GPU servers are fully capable of.

Let's talk about GPU server categorization below

To be honest, the classification of things, phenomena and other targets is a very complex issue that requires a deeper understanding of the target to achieve a comprehensive classification. The purpose of classification, in turn, is to better and more comprehensively recognize and understand the object of our classification - theGPU serverThe
Let's start with a small example: how to categorize people
You could say it's divided into: male, female (actually it's divided by gender)
It can also be said to be divided into: Chinese, American, Japanese (by country)
It can also be said to be divided into: whites, yellows, etc. (this is by skin color)

It follows that to categorize GPU servers, it is first necessary to identify a perspective (dimension) to make a categorization of GPU servers
1, we are divided by the shape of the GPU server: tower GPU servers, rack-mounted GPU servers
2, we are divided by CPU brand type: Intel processor GPU server, AMD processor GPU server or ARM chip GPU server and so on.
3, we can be divided by server platform: Lenovo GPU servers, Huawei GPU servers, Wave GPU servers, Huasan GPU servers, HP GPU servers, DELL GPU servers and so on.
4, we are divided by application scenarios: graphics acceleration GPU server (such as video codec), AI training GPU server, AI reasoning GPU server, scientific computing GPU server
5, we can also be divided by industry: fluid dynamics GPU acceleration server, protein analysis GPU server, medical impact analysis GPU server and so on.
Therefore, we don't have to care about how the GPU servers are categorized. What do you think?