Neural network performance in Synopsis embedded vision processors quadrupled for machine learning applications

July 18, 2017
Synopsis Inc. has announced that it has enhanced the convolutional neural network (CNN) engine in its DesignWare EV6x vision processors to address the increasing video resolution and frame rate requirements of high-performance embedded vision applications.

Synopsis Inc. has announced that it has enhanced the convolutional neural network (CNN) engine in its DesignWare EV6x vision processors to address the increasing video resolution and frame rate requirements of high-performance embedded vision applications. DesignWare EV processors are fully programmable and configurable IP cores that are optimized for embedded vision applications that combine software and hardware, as well up to four 512-bit vector DSPs and a CNN engine.

The new CNN engine in the processors offer up to 4.5 TeraMACs per second when implemented in 16-nm FinFET process technologies under typical conditions, four times more performance than Synopsys' previous CNN engine. Additionally, a new CNN mapping tool in the MetaWare EV Development Toolkit automatically dispatches processing tasks to available hardware resources for faster execution.

To Learn More

Contact: Synopsis Inc.
Headquarters: Mountain View, CA, USA
Product: DesignWare EV6x vision processors
Key Features: 4.5 TeraMACs per second when implemented in 16-nm FinFET process technologies (four times more performance than previous CNN engine.)

What Synopsis says:
View more information on the processors.

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About the Author

James Carroll

Former VSD Editor James Carroll joined the team 2013.  Carroll covered machine vision and imaging from numerous angles, including application stories, industry news, market updates, and new products. In addition to writing and editing articles, Carroll managed the Innovators Awards program and webcasts.

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