AI and neural networks are essential building blocks for automated driving, for example in the classification and tracking of objects or in determining the route in traffic. In addition, they help to optimize many other automotive applications, reduce the cost of ECUs, improve their performance and accelerate their market launch. For example, AI and neural networks enable optimized autocalibration of engines and reduce the number of sensors required by generating precise mathematical models of the physical reactions in a system. At the same time, AI applications require significantly more computing power than standard algorithms. Therefore, Infineon's Aurix microcontrollers will be equipped with a Parallel Processing Unit (PPU) specifically for processing AI algorithms. For the development of the PPU, the chip manufacturer uses the processor IP of the ARC EV from Sysnopsys.
The PPU is intended to ensure that the Aurix microcontrollers meet the increasing requirements for computing power in terms of security, data throughput and energy efficiency," says Peter Schäfer, head of the microcontroller business in Infineon's Automotive Division. The measure is intended to make the Aurix fit for data-intensive automotive applications such as future gateways, domain and zone controllers, engine control, electromobility and advanced driver assistance systems.