Renesas Electronics and Fixstars Corporation have planned to collaborate in the automotive deep learning field.
In April 2022, the two companies will establish an Automotive SW Platform Lab tasked with the development of software and operating environments for Renesas automotive devices.
“Fixstars possesses both advanced software technology for deep learning and optimization technology that allows more efficient utilization of hardware,” said Takeshi Kataoka, Senior Vice President, General Manager of the Automotive Solution Business Unit at Renesas. “I am confident that our collaboration will enable us to provide strong support for software development optimized for automotive applications and allow our customers to fully leverage the superior performance of Renesas’ automotive devices.”
“After developing a deep learning application, it is not possible to maintain high recognition accuracy and performance without constantly updating it with the latest learning data,” said Satoshi Miki, CEO of Fixstars.“Fixstars plans to focus on these machine learning operations (MLOps) for the automotive field, as we work together with Renesas to develop a deep learning development platform optimized for Renesas devices.”
The new Lab will support the early development and ongoing operation of advanced driver-assistance systems (ADAS) and autonomous driving (AD) systems.
The two companies will develop technologies aimed at software development for deep learning and building operating environments that can continuously update learned network models to maintain and enhance recognition accuracy and performance.
As part of their collaboration, today Renesas and Fixstars are launching GENESIS for R-Car, a cloud-based evaluation environment for R-Car that supports the early development of ADAS and AD systems. The new environment facilitates instant initial evaluations when selecting devices. It utilizes the GENESIS cloud-based device evaluation environment from Fixstars as its platform.
The new GENESIS for R-Car cloud-based evaluation environment does not require specialized technical expertise.
GENESIS for R-Car lets engineers confirm the processing execution time in frames per second (fps) and recognition accuracy percentage of R-Car V3H’s CNN accelerators on sample images using generic CNN models, such as ResNet or MobileNet. It also allows engineers to select the device and network they wish to evaluate and perform operations remotely on an actual board.
Plans include the rollout of a service that will allow customers to use their own CNN models for evaluations.