IP to build high-performance embedded vision processor, from Synopsys

March 31, 2015 // By Graham Prophet
The DesignWare EV processor family delivers, its writers assert, faster object detection with significantly lower power consumption for embedded vision applications such as video surveillance, gesture recognition and object detection. The multicore architecture is optimised for vision applications and delivers over 1000 GOPS/Watt with 5x better power efficiency than alternatives.

Featuring a programming environment based on emerging embedded vision standards such as OpenCV and OpenVX application software development is simplified for the first products in the DesignWare EV family of vision processors. The EV52 and EV54 vision processors are fully programmable and configurable vision processor IP cores that combine the flexibility of software solutions with the low cost and low power consumption of dedicated hardware. The EV processors implement a convolutional neural network (CNN) that can operate at more than 1000 GOPS/W, enabling fast and accurate detection of a wide range of objects such as faces, pedestrians and hand gestures at a fraction of the power consumption of alterantive vision solutions, Synopsys claims. The EV processor family is supported by a software programming environment based on existing and emerging embedded vision standards including OpenCV and OpenVX, as well as Synopsys’ MetaWare Development Toolkit. The combination of hardware optimised for vision data processing and high productivity programming tools suit the EV processors for a range of embedded vision applications including video surveillance, gesture recognition and object detection.

The EV processors include multiple high performance processing cores that can operate at up to 1 GHz in typical 28-nm process technologies. The EV processors also implement a feed-forward CNN structure that supports a programmable point to point streaming interconnect for fast and accurate object detection, a critical task in vision processing. The processors’ configurable number of execution units enable developers to exploit the task and data level parallelism common in vision applications, executing complex image and video recognition algorithms with as little as one-fifth the power consumption of other vision processors available on the market.

A complete software programming environment, including OpenVX and OpenCV libraries, and Synopsys’ MetaWare Development Toolkit, simplifies the development of application software for the Synopsys EV processor family. The OpenCV source libraries available for EV processors provide more than 2500 functions for real time computer vision. The processors are