Why DSPs excel at embedded vision neural networks.
Neural networks are now being developed in a variety of technology segments in the embedded market, from mobile to surveillance to the automotive segment. The computational and power requirements to process this data is increasing, with new methods to approach deep learning challenges emerging every day.
Vision processing systems must be designed holistically, for all platforms, with hardware and software developed in tandem. To develop this technology, designers must use tools and IP that enable:
• Efficient algorithms, to speed training and minimize computation
• Hardware platforms that meet the target cost and power usage for each application
By designing with the entire system in mind, designers can create transformative vision-enabled products as quickly and efficiently as possible. Taking a systems-level perspective pays off with in faster and better design, shorter verification cycles, software that works with the hardware, and new product leadership.
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