AI (artificial intelligence) is taking the world of IoT by storm. While many aspects of AI are computing- and resource-intensive, others rely on small and swift devices that can quickly deliver results. Innodisk’s new AI accelerator cards provide exponential performance gains for AI inference on the edge.
They use Intel’s third-generation Movidius Myriad X Vision Processing Unit (VPU), which is designed for deep neural network inference. As such, the VPU enhances all vision inference applications such as facial recognition, vehicle registration plate recognition and many other machine vision applications. The results enable an up to a 30-fold boost in performance depending on the edge device’s CPU.
Embedded devices typically found on the edge are ill-equipped for image recognition. The CPU is normally chosen for its low power consumption and thermal efficiency, making it particularly unsuited for AI inference. Much like a video card takes the load off the CPU for graphics rendering in PCs, the VPU assists edge devices in picking out objects and patterns in images and videos. Innodisk’s new AI accelerator cards achieve all this while leaving a small thermal footprint and maintaining low power consumption.
Innodisk’s AI accelerator cards have no minimum order quantity and come in two form factors: mPCIe with one Myriad X (EMPA-I101); and M.2 2280 with two Myriad X (EGPA-I201) inside. Windows and Linux are supported and deep learning frameworks such as Caffe, TensorFlow, Apache MXNet, and Open Neural Network Exchange (ONNX) are also supported through the Intel OpenVINO™ toolkit.
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