The?OpenVINO? toolkit offers software developers a single toolkit to accelerate their solutions across multiple hardware platforms including FPGAs. Intel? FPGAs offer fast to market, scalable, and customizable solutions.
OpenVINO? toolkit with the Deep Learning Deployment Toolkit (DLDT) enables you to go from Caffe* or TensorFlow* to hardware with no FPGA experience.
We have developed Intel? FPGA Deep Learning Acceleration Suite (Intel? FPGA DL Acceleration Suite) to scale to a wide array of networks.
The unique architecture of FPGAs provides the flexibility needed to support custom primitives.
The IEI Mustang-F100-A10 is an Intel? Vision Accelerator Design with Intel? Arria? 10 FPGA GX in a small form factor, PCI Express* (PCIe*) acceleration card that is supported natively by the OpenVINO? toolkit to deliver low-latency video inference for edge and, cloud deployment. It has been designed to add acceleration capabilities to PCIe* host platforms and has been validated on the IEI TANK-870AI compact IPC for those with space and power constraints.
Intel? FPGA-based acceleration platforms include PCIe*-based programmable acceleration cards, socket-based server platforms with integrated FPGAs, and others that are supported by the Acceleration Stack for Intel? Xeon? CPU with FPGAs. Intel platforms are qualified and validated for several leading original equipment manufacturers (OEM) server providers to support large scale FPGA deployment.
The OpenVINO? toolkit was awarded Best Developer Tool by the Embedded Vision Alliance at the Embedded Vision Summit (EVS) 2019.
"We thank the Embedded Vision Alliance for recognizing the OpenVINO? toolkit as its Developer Tool of the Year. Edge solutions require diverse hardware options to meet stringent performance, power, latency and cost requirements. This award reinforces the value of a high-performance, unified software environment across diverse hardware to enable developers to deploy AI solutions," said Adam Burns, vice president, Internet of Things Group, Intel Edge Inference Products.
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