談人工智慧晶片的4種類型

談人工智慧晶片的4種類型

傳統伺服器與AI伺服器的差別在於：

1. 傳統伺服器透過CPU做為主要的運算，

2. AI伺服器除了使用CPU外，還使用GPU、FPGA、ASIC來加速運算。

一般來說，傳統伺服器價格較低，約1500~3000 美元；而AI伺服器價格較高，如AI推論伺服器落在3000~20000美元；而AI訓練伺服器約落在15~30萬美元。

以下簡介各種伺服器晶片的差別：

1. CPU (Central Processing Unit): 以執行複雜指令集為目的，處理重複性高的類神經運算。

2. GPU (Graphics Processing Unit): 擅長浮點數及平行運算，適用於AI深度學習。

3. FPGA (Field Programmable Gate Array): 可依需求調整硬體配置，具備演算法靈活性。

4. ASIC (Application Specific Integrated Circuit): 能針對特定應用最佳化算效能、降低功耗、縮小體積。

4 Types of AI Chip 

The difference between traditional servers and AI servers is:

1. Traditional servers use the CPU as the main operations.

2. Except for the CPU, AI ​​servers also use GPU, FPGA, and ASIC to accelerate operations.

Generally speaking, the price of traditional servers is lower, about 1,500 to 3,000 USD; while the price of AI servers is higher, such as AI inference servers is about 3,000 to 20,000 USD; and AI training servers is about 150,000 to 300,000 USD. 

The following is the introduction to the differences between various server chips:

1. CPU (Central Processing Unit): Aimed at executing complex instruction sets, it processes highly repetitive neural-like operations.

2. GPU (Graphics Processing Unit): Good at floating point numbers and parallel operations, suitable for AI deep learning.

3. FPGA (Field Programmable Gate Array): The hardware configuration can be adjusted according to needs and has algorithm flexibility.

4. ASIC (Application Specific Integrated Circuit): It can optimize computing performance, reduce power consumption, and reduce size for specific applications.