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Application scenarios ​

Our GPU cloud server is perfect for a variety of high-performance scenarios:

Graphics rendering ​

High quality image and video requirements, large memory, a large amount of data processing, I/O concurrent capacity. It can complete the scene of fast data processing exchange and a large number of GPU computing power. Such as graphics rendering, engineering drawing.

A GPU-accelerated elastic cloud server is recommended, which is based on NVIDIA Tesla M60 hardware virtualization technology to provide cost-effective graphics acceleration. It can support DirectX and OpenGL, and can provide graphics and image processing capabilities with a maximum memory of 1GiB and a resolution of 4096×2160.

Data Analysis ​

Processing large volume of data, requiring high I/O capabilities and fast data exchange processing capabilities. For example, MapReduce and Hadoop are computationally intensive.

Disk-enhanced elastic cloud servers are recommended for workloads that require high-performance sequential read and write access to extremely large data sets on local storage, such as Hadoop distributed computing, large-scale parallel data processing, and log processing applications. The primary data storage is an HDD-based storage instance with a default configuration of up to 10GE network capacity, which provides high PPS performance and low network latency. It supports up to 24 local disks, 48 Vcpus, and 384GiB memory.

High Performance Computing ​

High computing power, high throughput scenarios. Examples include scientific computing, genetic engineering, game animation, biopharmaceutical computing, and storage systems.

It is recommended to use high performance computing elastic cloud server, which is mainly used in applications with high performance processors that are limited by computing. It is suitable for scenes that require massive parallel computing resources and high performance infrastructure services, and need to achieve high performance computing and mass storage, and have a certain guarantee for rendering efficiency.