Image recognition SoC reduces power consumption and chip area

Fabless semiconductor company, Optimum Semiconductor Technologies, announces the GP8300 SoC. According to the company, the GP8300 dramatically reduces chip cost, area, and power consumption for image recognition and object detection in a range of products such as self-driving cars, autonomous vehicles, smart cameras and other IoT edge devices.

​Created using 28nm technology, the GP8300 includes four 2GHz ‘Unity’ CPU cores from General Processor Technologies (GPT) interconnected with a cache coherent memory supporting heterogeneous systems architecture (HSA) processing for a common programming framework.

The GP8300 also integrates four of GPT’s 2.0GHz variable length vector (VLVm1) digital signal processing (DSP) cores for signal processing applications. Within the chip, the out-of-order CPUs execute control code while very long vectors process data. Alongside these generalised compute units, the chip also integrates two 1.0GHz artificial intelligence (AI) accelerators from GPT.

​”The GP8300 brings together several of GPT’s innovative IP cores with underlying embedded artificial intelligence (eAI) algorithms in a highly-integrated design targeting a wide range of exciting applications,” said Gary Nacer, president and COO of Optimum.

​Building on the success of its SB3500 multi-threaded heterogeneous computing platform for low-power software defined radio (SDR), the GP8300 achieves deep integration of eAI, edge computing, and communications on a single chip, says Optimum. The company provides support for CaffeNet-based training and tools for automatic fixed-point conversion and compression for inference.

The GP8300 will be generally available in Q4 2018.

Optimum Semiconductor Technologies (OST) is a fabless semiconductor company providing highly-integrated systems on chips (SoCs), Products are designed for applications across communications, autonomous vehicles and intelligent transportation, smart cities, industrial automation, robotics, and machine vision.

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