ASUS IoT, the global AIoT solutions provider, announced the PE8000G model at the Embedded World 2024 event. This powerful AI edge computing computer supports multiple GPU cards for high performance. The PE8000G has been expertly engineered to withstand extreme temperatures, vibration and fluctuating voltage. PE8000G is powered by impressive Intel Core processors (13th and 12th generation) and Intel R680E chipset, thus offering superior processing power and efficiency.
Thanks to its advanced architecture, PE8000G manages to operate multiple neural network modules in real time, making it an ideal solution in the edge computing field. is taking an important step . With its robust design, exceptional performance and wide range of features, the PE8000G series is ready to revolutionize AI-powered applications across multiple sectors. The model enables organizations to take on critical tasks with confidence and achieve unprecedented levels of productivity and innovation.
Dual GPU power and industrial durability for seamless AI inferences
PE8000G supports two graphics cards, each consuming up to 450 watts of power. Thus, endpoint redundancy, high-efficiency computation, seamless real-time artificial intelligence inference and accelerated computation become possible. Additionally, the PE8000G can operate in the 8 to 48 V DC input range and has built-in ignition power control and monitoring for flexible power options in a variety of installation scenarios. offers opportunities . In addition, the product was designed in accordance with MIL-STD-810H military standards against vibration and shaking. The secure mechanism supported by dual GPU helps provide accurate inference results even in challenging conditions and provides confidence in artificial intelligence-supported decision-making.
Optimized for computer vision and perception and ready to go
PE8000G is optimized for in-car environments. The model has integrated ignition power control and power monitoring capabilities. The product also excels in challenging environments such as AI-powered factory automation, intelligent video analytics (IVA), roadside units (RSUs), and autonomous driving. Data is ready. Efficient pre-processing and detection capabilities that can optimize the density can increase the accuracy of artificial intelligence inference.
