Renesas Electronics Corporation has announced the development of processor technologies for automotive systems-on-chip (SoCs).
These are to be used in applications like advanced driver assistance systems (ADAS) and autonomous driving (AD) systems that aim to optimise both performance and power efficiency while supporting a high level of functional safety.
The three successful developments of Renesas that have been announced include:
A convolutional neural network (CNN) hardware accelerator core to deliver a ‘world-class’ combination of deep learning performance of 60.4 trillion operations per second (TOPS) and a power efficiency of 13.8 TOPS/W.
Sophisticated safety mechanisms for fast detection of and response to random hardware failures. Through this, a highly power efficient detection mechanism with a high failure detection rate is possible.
A mechanism that allows software tasks with different safety levels to operate in parallel on the SoC without interfering with each other, thus bolstering functional safety for ASIL D control. These technologies have been applied in the firm’s latest R-Car V3U automotive SoC.
Renesas unveiled the above at the International Solid-State Circuits Conference 2021 (ISSCC 2021), which took place February 13 to 22, 2021.
Applications like next-generation ADAS and AD systems require outstanding deep learning performance of 60 TOPS or even 120 TOPS alongside power efficiency.
Besides, since signal processing from object identification to the issuing of control instructions constitutes the bulk of the processing load in AD systems, achieving the functional safety equivalent to ASIL D – the strictest safety level defined in the ISO 26262 automotive safety standard – is a pressing issue.
The company has developed new technologies to cater to these needs, including a hardware accelerator that delivers outstanding CNN processing performance with power efficiency.
(With inputs from Automotive Lead Research Team)
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