Infineon Technologies has started a collaboration with Synopsys. Next-generation AURIX (automotive realtime integrated next generation architecture) microcontrollers from Infineon will integrate a new high-performance AI accelerator called parallel processing unit (PPU) that will employ Synopsys’ DesignWare ARC EV (embedded vision) processor IP.
“By developing the PPU together with Synopsys, we make sure that our future microcontrollers will provide the safety features, throughput, and power-efficient performance necessary to meet increasing AI computational requirements,” said Peter Schäfer, head of the microcontroller business line of Infineon’s Automotive Division. “This will prepare the AURIX for data-hungry automotive applications such as future gateways, domain and zone controllers, engine management, electro-mobility, and advanced driver-assistance systems.”
Already today, the AURIX supports certain types of neural networks. However, the PPU is expected to take its real-time and AI capabilities further. The PPU’s performance will reportedly be significantly higher than that of today’s accelerators, enabling the AURIX to process the data from advanced sensors where it is currently bounded by real-time constraints. The PPU will accelerate AI algorithms such as recurrent neural network (RNN), multi-layer perceptron (MLP), convolutional neural network (CNN), and radial basis function (RBF).
“In many AI-driven applications, safety is paramount,” said Joachim Kunkel, General Manager of the Solutions Group at Synopsys. “Combining the processing power and safety features of our ARC EV processor with the proven architecture of the AURIX will enable the development of automotive systems at the highest levels of functional safety.”
The EV processor is supported by Synopsys’ MetaWare EV Development Toolkit for Safety, which is intended to speed safety-compliant application software development for automotive designs. The resulting AURIX toolchain will support model-based designs, enabling the latest software design strategies and reducing the increasingly demanding automotive time-to-market.
Furthermore, by supporting convolutional neural networks, the companies expect the PPU will help pave the way to holistic security systems. It will enable layered security concepts supporting techniques for intrusion detection and prevention systems such as deep packet inspections or system entropy monitoring.