Based on an 8-lane, PCI-Express add-in card, the BrainChip Accelerator increases the speed and accuracy of the object recognition function of BrainChip Studio artificial intelligence softwareby up to six times, while increasing the simultaneous video channels of a system to 16 per card at more than 600 fps.
Processing is done by six cores in a Xilinx Kintex Ultrascale FPGA, each of which performs user-defined image scaling, spike generation, and spiking neural network comparison to recognize objects. Scaling images up and down, according to BrainChip, increases the probability of finding objects, and due to the low-power characteristics of spiking neural networks, each core consumes approximately one watt while processing up to 100 fps. In comparison to a GPU-accelerated deep learning classification neural networks like GoogleNet and AlexNet, this is a 7x improvement of frames/second/watt, according to the company.
The BrainChip Accelerator add-in card learns from a single low-resolution image, which can be as small as 20 x 20 pixels, and excels in recognition in low-light, low-resolution, noisy environments. BrainChip Studio, the software that is being sped up by the Accelerator, is an artificial intelligence (AI) software that is designed to aid law enforcement and intelligence organizations to rapidly search vast amount of video footage for identifying patterns or faces.
To Learn More:
Headquarters: Aliso Viejo, CA, USA
Product: BrainChip hardware accelerator
Key Features: 8-lane, PCI-Express add-in card with six core processors in a Xilinx Kintex Ultrascale FPGA, each of which performs user-defined image scaling, spike generation, and spiking neural network comparison to recognize objects.
Share new products that you think are particularly interesting or helpful by contacting James Carroll, Senior Web Editor, Vision Systems Design.