Developer Kits with Intel® Core™ Processors
Preinstalled Software
Get the most out of your hardware performance with the Intel® Distribution of OpenVINO™ toolkit, Ubuntu* Desktop LTS, and libraries.
Pretrained Models for Acceleration
Choose from a variety of optimized detection and recognition models for developing deep learning applications.
Training Extensions for Deep Learning
Modify, customize, train, and extend computer vision models for deep learning and inference optimization.
Overview
Develop and deploy solutions on Intel's latest high-performance platforms.
- Increase single-thread performance by up to 23% and multithread performance by up to 19%¹
- Gain 2.95x the graphics performance over the 8th generation Intel® Core™ processors¹
- Enable inference workloads to run across all four CPU cores or up to 96 graphics execution units (EU)
- Offload multiple workloads to optional Intel® Vision Accelerator products
Who Needs This Product
System integrators, independent software vendors (ISV), and IoT developers who create solutions using the following processes and applications:
- High-performance AI inferencing algorithms across Intel® Vision products and platforms
- Real-time workloads
- Ingestion of up to 40 simultaneous 1080p video streams at 30 FPS with output support of up to four channels of 4K video (or two channels of 8K)
- Ability to offload multiple workloads
Reference Implementations
These solutions have been prebuilt and validated for developers to test and deploy industrial, retail, and digital security applications enabled for computer vision.
Hardware
Prevalidated developer kits with an optional vision accelerator.
11th Generation Intel® Core™ Processors and Intel® Xeon® E Processors
UP Xtreme i11 Edge Compute Enabling Kit
Optional: UP AI Core XM2280 with Intel® Vision Accelerator Design
IEI* DRPC AIoT Developer Kit
Optional: IEI* Mustang-V100-MX8 with eight Intel® Movidius™ Myriad™ X VPUs
Intel® Vision Accelerator Design
This option enables the following capabilities:
- Delivers high-performance machine vision at ultra-low power.
- Offloads workloads to increase available processing efficiency.
- Is engineered for performance and inferencing at the edge.
Review the supported pretrained models for the Intel Distribution of OpenVINO toolkit.
Learn More
Software
Intel® Distribution of OpenVINO™ Toolkit
- Enable convolutional neural network-based deep learning inference on the edge.
- Support heterogeneous running across various accelerators—CPUs, GPUs, Intel® Movidius™ Neural Compute Sticks (NCS), and Intel Vision Accelerator Design products—using a common API.
- Speed up time to market via a library of functions and preoptimized kernels.
Overview | Training | Documentation | Get Started | Forum
Intel® Developer Cloud
Explore this cloud-hosted AI development platform with access to Intel hardware to find a solution that meets your needs.
- Try a variety of hosted hardware including Intel Atom®, Intel Core, and Intel® Xeon® processors or the Intel® Movidius™ VPU.
- Upload your own AI model or choose from a library of prebuilt sample applications.
- Benchmark hardware solutions to optimize for your performance needs.
Intel® Edge Software Hub
- Download the latest software packages for edge solutions (including computer vision and deep learning applications) for Intel architecture.
- Develop, test, deploy, and maintain solutions at the edge with software packages and tools.
- Optimize your computer vision and deep learning applications for Intel architecture with the Intel Distribution of OpenVINO toolkit.
- Maintain and manage your applications with containerized architecture and regular updates.
- Get started quickly with reference implementations, tutorials, and samples.
Intel® oneAPI Base & IoT Toolkit
The combination of Intel® oneAPI Base Toolkit and Intel® oneAPI IoT Toolkit provides what you need to implement efficient, reliable, cross-architecture IoT solutions that run at the network edge. It delivers a core set of high-performance build tools and libraries and analysis tools to simplify IoT system design, development, and deployment across CPUs, GPUs, FPGAs, and other accelerator architectures.