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Synopsys and Morpho Accelerate Deep Learning Processing for Embedded Vision Applications

By   /  August 14, 2017  /  No Comments

by Angela Guess

A recent press release states, “Synopsys, Inc. today announced a collaboration with Morpho, Inc. to optimize Morpho’s computational photography software for Synopsys’ DesignWare® EV6x Vision Processors. Morpho’s Scene Classifier™ image classification technology uses deep learning algorithms to analyze visual input and automatically apply tags for classification, searchability and organization. Morpho is optimizing their software to take advantage of the EV6x Vision Processors’ scalable hardware architecture, which includes up to four 512-bit vector DSPs and a fully programmable convolutional neural network (CNN) engine. The combined hardware-software solution enables designers to accelerate image classification and automated tagging tasks in their mobile and surveillance systems-on-chips (SoCs) while consuming significantly less power and memory resources than alternative implementations.”

The release goes on, “Morpho’s Scene Classifier uses deep learning to “recognize” essential identifying features for automated, real-time image tagging. Morpho’s portfolio of software algorithms includes high-precision scene recognition technology, motion detection, 360 VR stitching technology and other image processing technology. DesignWare EV6x Vision Processor IP is a family of fully programmable and configurable vision processors that integrate scalar, vector DSP and CNN processing units for highly accurate and fast vision processing. Supported by a comprehensive software programing environment including the ARC® MetaWare EV Toolkit, the EV6x Vision Processors offer SoC designers a flexible, power-efficient embedded vision solution that addresses a wide range of automotive, industrial and consumer applications.”

Read more at PR Newswire.

Photo credit: Synopsys

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