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Powered by Xilinx: Another look at KORTIQ’s FPGA-based AIScale CNN Accelerator

Xilinx Employee
Xilinx Employee
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A previous blog at the end of last November discussed KORTIQ’s FPGA-based AIScale CNN Accelerator, which takes pre-trained CNNs (convolutional neural networks)—including industry standards such as ResNet, AlexNet, Tiny Yolo, and VGG-16—compresses them, and fits them into Xilinx’s full range of programmable logic fabrics. (See “KORTIQ’s AIScale Accelerator fits trained CNNs into large or small All Programmable devices, allowing you to pick the right price/performance ratio for your application.”) A short, new Powered by Xilinx video provides more details about Kortiq and its accelerated CNN.

 

In the video, KORTIQ CEO Harold Weiss discusses using low-end Zynq SoCs (up to the Z-7020) and Zynq UltraScale+ MPSoCs (the ZU2 and ZU3) to create low-power solutions that deliver “just enough” performance for target industrial applications such as video processing, which requires billions of operations per second. The Zynq SoCs and Zynq UltraScale+ MPSoCs consume far less power than competing GPUs and CPUs while accelerating multiple CNN layers including convolutional layers, pooling layers, fully connected layers, and adding layers.

 

Here’s the new video:

 

 

 

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