Renesas Provide the Advanced AI Tool to Assist the Development of Autonomous Driving Technology
AI complier Renesas is developing is the software which can generate high-performance executable code for Renesas’s R-Car device from pre-trained deep neural network.
Background
Performing CNN inference in real time is very challenging work because embedded hardware faces severe restrictions in the hardware resources of computation and power consumption. In order to performing CNN inference effectively on R-Car V series device, Renesas designed the heterogeneous architecture, which is divided into a programmable processor (CPU) and the accelerators dedicated for computing each layer of the network.
As for AI complier, the common software architecture contains two parts: the compiler “Front end” and the complier “Back end” as shown in the figure. Deep neural networks are translated into multi-level IRs in AI compiler. The complier front end is responsible for hardware-independent transformations (graph IR) and graph optimizations while the complier back end is responsible for hardware-specific optimizations, code generation.
Renesas is mainly developing the hardware-dependent optimization algorithm, by making maximum use of the heterogeneous architecture of R-Car V series.
Deep neural network is one of the technology field which has been extensively studied in recent years and continues to evolve. Renesas will provide the advanced AI tool to assist the development of autonomous driving technology.
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