Chinese IT manufacturer Inspur´s NF5568M4 server has been selected by Internet giant Baidu to provide hardware support for the deep learning platform of Baidu´s driverless car.
Deep learning is one of the core areas of driverless technology.
In December 2015, Baidu´s driverless car passed the road test starting from the Baidu Tower in Zhongguancun High-tech Park in Beijing, driving onto the G7 Beijing-Xinjiang Expressway, through the Fifth Ring Road and reaching Olympic Forest Park, and back.
The driverless technology adopted throughout the course included decelerating, lane switching, overtaking, going on and off ramps and turning around. The car passed each of these testing criteria and reached a top speed of 100 kilometers per hour.
Another core technology in driverless cars is image sensing and recognition and Baidu´s car is able to accurately sense objects and pedestrians, even effectively following traffic lights and avoiding accidents.
Image recognition is a super large computing project, which requires hundreds of thousands — in some cases even billions — of learning samples to train a model. A GPU made up of thousands of smaller and more energy-saving cores has therefore become the main force for the application of image recognition training.
Inspur provides an artificial intelligence application and has strategic partnerships with NVIDIA (the largest vision computing company in the world) in the field of GPU heterogeneous computing. To produce the high-performance computing application, Inspur has launched the NF5568M4 co-processing acceleration server, carrying two Intel E5-2600v3 processors and four Nvidia Tesla K40 GPUs. The highest single computing capacity of a single GPU server reaches 17 teraflops.
Presently, in the KITTI test for common vehicles, Baidu has reached a recognition accuracy of 90 percent — thanks to a big contribution by Inspur´s GPU co-processing acceleration server NF5568M4, which guarantees greater safety in the operation of driverless cars.
Baidu plans to set up demonstration regions in 10 cities within China and officially put commercial-purposed driverless cars to use. Large scale production is projected in five years, and within 15 years it is estimated that 80% of newly manufactured cars will be equipped with the driverless function.
Inspur possesses 100,000-core-and-above CPU+GPU/MIC/FPGA large-scale paralleling algorithms, program development and software optimization abilities. Additionally, through research and development, Inspur´s open-source Caffe-MPI and ClusterEngine high-performance computing management platform focus on artificial intelligence and deep learning to build a professional heterogeneous acceleration platform. This platform facilitates the launch of deep learning applications such as driverless cars, and other innovative applications.