SUNIX AIEH2000 VS NVIDIA A4000 AI computing energy saving benefit comparison(ResNet50 model)
Uplaod date: 2023-12-29 10:50:03
Time: 3:38
Description:
As technology advances, artificial intelligence has become widely applied in various edge computing industries. With the increasing demand for computing power, energy conservation has become a significant issue. Today, I will introduce SUNIX’s AI acceleration card and demonstrate how it effectively reduces computer energy consumption while delivering exceptional performance in high-speed AI visual recognition processing.
SUNIX’s AI acceleration card, the AIEH2000, is specifically developed for the PC platform and utilizes a PCIe interface. At its core, it features the HAILO 8 AI chip. The HAILO 8 is a high-performance, low-power AI processor designed for edge computing. It offers powerful neural network inference capabilities, allowing complex AI models to run on edge devices with minimal power consumption. With up to 26 TOPS (trillions of operations per second) of computational power, the HAILO 8 excels in various AI applications and is an ideal choice for AI visual recognition tasks.
To clearly showcase the energy efficiency of the SUNIX AI acceleration card, we conducted tests on the same platform using the Nvidia RTX A4000, which also has AI model inference capabilities. We performed image recognition tests using the same ResNet50 model to compare the power consumption between the SUNIX AIEH2000 and the Nvidia A4000.
The test results clearly show that the Nvidia A4000 AI acceleration card consumes between 60W and 100W when performing image recognition tasks. In contrast, the SUNIX AIEH2000 AI acceleration card only requires 7W to 10W, significantly lower than the Nvidia A4000. This low power consumption is primarily due to the advanced design of the HAILO 8 AI chip, which delivers exceptional computational power while dramatically reducing energy usage.
The bar chart in the test results further illustrates the energy efficiency of the two AI acceleration cards. The energy consumption for image processing with the SUNIX AIEH2000 is much lower than that of the Nvidia A4000, achieving at least six times the energy savings. In terms of energy efficiency for visual recognition tasks, the SUNIX AIEH2000 achieves up to 166 FPS/W (frames per second per watt), compared to 33 FPS/W for the Nvidia A4000, highlighting its superior performance. While the Nvidia A4000 also performs well in AI computations, it comes with higher setup costs and typically consumes over 60W during model inference. In contrast, the SUNIX AIEH2000 maintains an average power consumption of less than 10W during model inference. Therefore, in large-scale applications of computer vision recognition and AI edge computing, a PC equipped with the SUNIX AI acceleration card better meets the energy-saving needs of customers.
Adopting the SUNIX AI acceleration card to expand your PC business into the AI visual application market is not only energy-efficient and economical but also helps you stand out in the edge computing market.
If you have any questions, please feel free to contact us, and we will be happy to assist you.
