Renesas Electronics Corporation has introduced processor technologies for automotive systems-on-chip (SoCs) used in applications such as advanced driver assistance systems (ADAS) and autonomous driving (AD) systems that aim to optimize both performance and power efficiency while supporting a high level of functional safety.
Renesas’ successful development announced includes:
1) A convolutional neural network (CNN) hardware accelerator core that delivers 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
2) Sophisticated safety mechanisms for fast detection of and response to random hardware failures. This makes it possible to create a highly power-efficient detection mechanism with a high failure detection rate
3) A mechanism that allows software tasks with different safety levels to operate in parallel on the SoC without interfering with each other, thereby bolstering functional safety for ASIL D control. These technologies have been applied in the company’s latest R-Car V3U automotive SoC.
Renesas presented these achievements at the International Solid-State Circuits Conference 2021 (ISSCC 2021), which took place from February 13 to 22, 2021.
Applications such as next-generation ADAS and AD systems require outstanding deep learning performance of 60 TOPS or even 120 TOPS alongside power efficiency.
Also, 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.
Renesas has developed new technologies to meet these needs, including a hardware accelerator that delivers outstanding CNN processing performance with superior power efficiency.