AI Object Recognition Accelerates Neuromorphic Computing

BrainChip’s hardware acceleration board, simply dubbed BrainChip Accelerator, is an eight-lane, PCI-Express add-in card that increases the speed and accuracy of the object recognition function of BrainChip Studio software by up to six times. It simultaneously increases video channels of the host system to 16 per card. Described as consuming very low-power, the card easily installs within existing video surveillance systems without the need to upgrade power systems or thermal management.


Tailored to law enforcement and intelligence organizations, BrainChip Studio software rapidly identifies objects in large amounts of archived or live streaming video. Processing multiple video streams simultaneously, the accelerator add-in card enables users to search increasing amounts of video faster, with a higher probability of object recognition and lower total cost of ownership. The system learns from a single low-resolution image, which can be as small as 20 x 20 pixels. The card is also said to excel in low-light, low-resolution, and noisy environments.

Sponsored by Infosys

Infosys positioned as a Leader in Gartner Magic Quadrant for IT Services for Communications Service Providers, Worldwide 2020

The Gartner Magic Quadrant evaluated 12 vendors and Infosys was recognized for its completeness of vision and ability to execute.
Infosys leverages its global partner ecosystem, CSP-dedicated studio, design tools, and 5G Living Labs to boost service delivery. Innovative solutions such as the ‘Infosys Cortex2’ are driving business value for CSPs.
BrainChip Accelerator

BrainChip Accelerator embarks as the first commercial implementation of a hardware-accelerated spiking neural network system, making significant progress in the development of neuromorphic computing, a leg of artificial intelligence that simulates neuron functions. Processing is done by six BrainChip Accelerator cores in a Xilinx Kintex Ultrascale field-programmable gate array (FPGA). Each core performs user-defined image scaling, spike generation, and spiking neural network comparison to recognize objects. In terms of power, each core consumes approximately 1W while processing up to 100 fps. In comparison to GPU-accelerated deep learning classification neural networks like GoogleNet and AlexNet, this is reported as a seven times improvement of frames/second/watt.


BrainChip Accelerator is compatible with Windows or Linux operating systems and is currently available to select law enforcement and intelligence agencies as an integrated server appliance. For further details, contact BrainChip Holdings Ltd.

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