Machine vision and deep learning are being embedded in highly integrated SoCs and expanding into emerging high-volume applications such as automotive ADAS, surveillance, and augmented reality. A major challenge in enabling mass adoption of embedded vision applications is in providing the processing capability at a power and cost point low enough for embedded applications, while maintaining sufficient flexibility to cater to rapidly evolving markets.
The DesignWare® EV Processors are fully programmable and configurable IP cores that have been optimized for embedded vision applications, combining the flexibility of software solutions with the low cost and low power consumption of hardware. For fast, accurate object detection and recognition, the EV Processors integrate an optional high-performance convolutional neural network (CNN) engine.
The EV Processors are designed to integrate seamlessly into an SoC and can be used with any host processors and operate in parallel with the host. The EV Processors include support for synchronization with the host through message passing and interrupts. In addition, the EV Processor memory map is accessible to the host. These features enable the host to maintain control while allowing all vision processing to be offloaded to the EV Processor, reducing power and accelerating results. The EV Processors can access image data stored in a memory mapped area of the SoC or from off-chip sources independently from the host through the ARM® AMBA® AXI™ standard system interface, if required.
To speed application software development, the EV processors are supported by a comprehensive software programming environment based on existing and emerging embedded vision and neural network standards including OpenCV, OpenVX™, OpenCL™ C and Caffe with Synopsys' ARC MetaWare Development Toolkit.