GPU cloud computing power

1.

GPU server is a fast, stable and flexible computing service based on GPU, which is used in video codec, deep learning, scientific computing and other scenarios

the function is: excellent graphics processing ability and high-performance computing ability, providing extreme computing performance, effectively liberating the computing pressure, and improving the computing processing efficiency and competitiveness of procts

2. The 2400g Vega has no video memory, but many mining tools can't run directly with such integrated graphics cards, and even if they can, it's useless. People can connect at least six pieces with a rx560 machine, but 2400g can't be used together at all. A 2400g must correspond to a motherboard, which is much higher than the cost of graphics card.

3. computing power is a concept put forward by NVIDIA when it released CUDA (Compute Unified Device Architecture, a programming language for GPU, similar to C programming for CPU). Because the graphics card itself is a floating-point computing chip, it can be used as a computing card, so the graphics card has computing power. Different graphics cards have different computing power. In order to show the difference, NVIDIA put forward the corresponding version of computing power x.x on the procts of different periods. Computing power 1.0 appeared on early graphics cards, such as the original 8800 ultra and many 8000 Series cards, as well as Tesla C / D / s870s cards. Cuda1.0 was released corresponding to these graphics cards. Today, computing power 1.0 has been eliminated from the market. Then there was computing power 1.1, which appeared on many 9000 Series graphics cards. Computing power 1.2 appears together with GT200 Series graphics card, while computing power 1.3 is proposed when upgrading from GT200 to GT200 A / b revision. In the future, there will be computing power 2.0, 2.1, 3.0 and other versions. The latest released version is computing power 6.1, which is supported by the latest Pascal architecture graphics card. At the same time, CUDA version is also updated to cuda8.0

ordinary users do not need to care about the computing power of the graphics card, only GPU programmers care about this problem when they write CUDA programs to develop GPU computing. As long as you know the model of your computer's graphics card, you can find the corresponding computing power https://developer.nvidia.com/cuda-gpus .

4. These two are for different areas, GPU cloud server is usually used to do floating-point or graphics computing. Even machine learning

FPGA is more used in instry
GPU cloud computing is a computing service based on GPU applications. It has real-time, high-speed parallel computing and floating-point computing capabilities, and is suitable for 3D graphics applications, video decoding, deep learning, scientific computing and other application scenarios
FPGA cloud computing is a computing service based on FPGA (field programmable gate array). You can easily obtain and deploy your FPGA computing instance in a few minutes with just a few clicks. You can program on FPGA instances to create custom hardware accelerations for your applications.

5. Tencent cloud GPU cloud computing is a fast, stable and flexible computing service based on GPU, which is applied to deep learning, scientific computing and other GPU computing scenarios. GPU cloud server provides the same management mode as standard cloud server, which is convenient and fast. At the same time, GPU cloud server also provides excellent graphics processing ability and high-performance computing ability, with extreme computing performance, effectively liberating the computing pressure of users, and improving the computing processing efficiency and competitiveness of procts. There are two kinds of billing methods. They are always paid according to the quantity and monthly package. It's better to find Tencent cloud blue route to get to know them. They are very professional and have the lowest discount. But the disadvantage is that they are too enthusiastic.

6. The emphasis is different. The virtualization of GPU is more inclined to scenes that require certain 3D performance, such as desktop virtualization. Many banking and insurance companies have this kind of virtualization. Everyone has a computer to access the virtual cloud desktop, and all the data is in the virtual machine. The good thing is to prevent data leakage. This kind of application scene requires certain 3D performance, Two common manufacturers, ctrix and VMware, the former has its own set of things, without the help of GPU, while the latter has a set of hardware based GPU virtualization in cooperation with NVIDIA. CPU virtualization focuses more on computing. At present, the most common kinds of cloud servers belong to this kind
cloud computing is a concept that has been hyped in recent years. Many companies publicize that they have used cloud computing. In fact, they only use the lowest level IAAs, infrastructure as a service, which is just a virtual machine.

7. It's like this: Tencent cloud GPU cloud computing is a fast, stable and flexible computing service based on GPU, which is applied to deep learning, scientific computing and other GPU computing scenarios. GPU cloud server provides the same management mode as standard cloud server, which is convenient and fast. At the same time, GPU cloud server also provides excellent graphics processing ability and high-performance computing ability, with extreme computing performance, effectively liberating the computing pressure of users, and improving the computing processing efficiency and competitiveness of procts. There are two kinds of billing methods. They are always paid according to the quantity and monthly package. It's better to find Tencent cloud blue route to get to know them. They are especially professional and have the lowest price. But the disadvantage is that they are too enthusiastic.

8. Well, Tencent cloud GPU cloud computing is a fast, stable and flexible computing service based on GPU, which is applied to deep learning, scientific computing and other GPU computing scenarios. GPU cloud server provides the same management mode as standard cloud server, which is convenient and fast. At the same time, GPU cloud server also provides excellent graphics processing ability and high-performance computing ability, with extreme computing performance, effectively liberating the computing pressure of users, and improving the computing processing efficiency and competitiveness of procts. There are two kinds of billing methods. They are always on a monthly basis. It's better to find Tencent's cloud blue route. They are very good. But the disadvantage is that they are too enthusiastic.

9. High performance computing, or parallel computing, is to break through the resource limitation of single machine and let more machines complete a task together. Cloud computing, in general, allows a single physical machine with excess resources to complete multiple tasks independently and in isolation through virtualization technology. Their starting point is different, or even the opposite. However, the scope of cloud computing is very wide now, so there will be some overlaps. For example, the cloud servers can be clustered again, which is a bit like parallel computing. However, the cluster of cloud servers is generally used to provide network services rather than computing services
the more important progress in cloud computing is to provide storage and network virtualization, so that the cloud server is really equivalent to a physical server with moderate performance, so as to realize the on-demand allocation of resources, high utilization and high availability. It provides a very loose structure from the bottom, so that a variety of tasks can be freely combined and do not interfere with each other; It is contrary to the highly organized structure of parallel computing.

10. Dazzle cloud rendering GPU rendering, equivalent to two gtx1080 graphics cards, C4d, Maya only 5 yuan per hour, single card only 2.5 yuan, 3dsmax8.75 yuan, hope to help you