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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