We offer services:
Deep Learning on FPGA
Training Data Collection
Hardware Acceleration of Machine Learning Algorithms
Feasibility Studies and Consultation
As the hardware capabilities have grown, so has the size of the neural networks. But in recent years there has been a shift in focus to make the networks as small as possible. This means that the power of Deep Learning has become available for mobile phones, IoT devices and other embedded systems.
Synective has developed a demo system to showcase the power of embedded FPGA Deep Learning. It was able to classify hand-written digits using nothing but a tiny, low-end FPGA and a camera.
Synective has designed a CNN that is optimized with respect to memory footprint and inference speed. The network is implemented and runs on the ARM processor of the Raspberry Pi.
Synective continually take on thesis workers that improve our embedded Deep Learning system.