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Kneron Delivers Efficient AI

February 25, 2020

Author: Linley Gwennap

New companies continue to jump into the hot edge-AI market, but Kneron stands out in a few ways. While many competitors are still showing PoC (proof of concept) demos, the startup already has its first chip in production. It has more than 140 employees and big customers such as Acer and Gree, one of the world’s largest appliance vendors. It recently announced a $40 million funding round, bringing total investment to $73 million. Despite that success, Kneron has been nearly as silent as the first letter of its name.

Founded in 2015, Kneron initially developed face-recognition algorithms. By 2017, it began licensing its first deep-learning accelerator (DLA) design so customers could integrate it into their own SoCs; Gree, for example, integrates the DLA into an ASIC. After instantiating the DLA in a 65nm test chip, Kneron developed its first chip, the KL520, which is similar to many other Cortex-M4 microcontrollers but includes the company’s DLA. The chip can serve as the main processor in camera-based edge devices, connecting directly to image sensors, a display, an audio codec, LEDs, and motors along with DRAM and flash memory. It entered production in late 2019 and costs less than $5. Applications include security cameras and smart-home devices.

The central element of the Kneron DLA is a convolution unit (CU) optimized for 3x3 convolutions. Each clock cycle, the CU performs the equivalent of nine INT8 MAC operations, producing a partial sum. This approach takes advantage of data reuse: the CU requires only six inputs for the nine two-input multiply operations, the results of which are then summed. The KL520 employs a set of 64 convolution units to achieve 350 billion operations per second (GOPS) for 8-bit integer (INT8) calculations. Even at this peak speed, the chip typically requires less than 500mW.

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