What is a GPU server? | |
For people who enjoy gaming, the term "GPU" is quite familiar. Typically, the CPU is responsible for the core tasks of a computer, such as running the operating system, browsing the web, and handling day-to-day applications. Although the CPU has powerful computing capabilities, it is limited in parallel processing and struggles to efficiently handle many tasks simultaneously. The GPU, on the other hand, while perhaps not as fast as the CPU in handling individual tasks, can process thousands of tasks simultaneously. Initially, GPUs were widely used in video games due to their powerful graphics rendering capabilities. However, with the rapid development of artificial intelligence and blockchain technology, the use of GPUs has significantly expanded to more computationally intensive scenarios. The core advantage of the GPU lies in its multi-core architecture. Modern GPUs often use a multi-core design, such as NVIDIA's Pascal architecture, which can handle various workloads. Depending on their functionality, GPU cores can be categorized as follows: - **CUDA Cores**: General-purpose computing cores that can execute multiple tasks simultaneously. These are mainly found in NVIDIA GPUs, while AMD's stream processors perform similar functions. - **Tensor Cores**: Specialized processing units in NVIDIA GPUs designed for AI and deep learning, used to accelerate model training. - **RT Cores and Ray-Tracing Accelerators**: Specifically designed to handle complex ray calculations, widely used in 3D rendering and ray tracing, such as in virtual reality projects and high-intensity graphical rendering tasks. With its powerful computing capability, efficiency in processing large datasets, and exceptional performance in AI and deep learning, GPU servers offer significant advantages over traditional CPU configurations in specific computing scenarios. The GPU's ability to perform parallel processing with thousands of cores allows it to excel in tasks such as matrix operations and graphics rendering, far surpassing the CPU in those areas. | |
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