For production deployment of AI, e.g. in industrial plants or mobile systems, it is often necessary to port the AI implementation to edge devices. However, available off-the-shelf systems are not always suitable: Often they do not satisfy the contradicting demands on performance, energy consumption or operating conditions.
Tool support for the selection or design of system-on-chip (SoC) platforms that are tailored to the AI implementation as well as the operating conditions.
Development environment for application-specific design of RISC-V-based SoC architectures. Building on top of a RISC-V hardware generation framework, an application-specific SoC accelerator architecture is generated.
FPGA-based SoC architectures for time series analysis prepared for synthesis.