Developer Kits with Intel® Core™ Ultra 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
Build AI-focused solutions for retail, industrial, healthcare, and other applications at the edge using developer kits with Intel® Core™ Ultra processors. These developer kits are pretested and prevalidated with edge software packages to deliver compute performance in parallel with accelerated AI inferencing and computer vision for your solution.
- Provides multiple integrated compute engines for AI: P-cores, E-cores, Intel® Arc™ GPU, and Intel® AI Boost, a built-in neural processing unit (NPU) for increased edge AI capabilities at low power.
- Speeds up media-intensive workloads at the edge and supports up to four concurrent 4K displays with the integrated Intel Arc GPU, enabling smaller form-factor systems and lower power consumption.
- Balances power and performance tailored for your edge applications, from efficient fanless designs to performant compact designs.
Who Needs This Product
System integrators, independent software vendors (ISV), and IoT developers who create vision-based inferencing applications at the edge that demand:
- High-performance AI inferencing algorithms across a mix of Intel hardware and environments.
- Ability to offload multiple workloads to an Intel processor, GPU, or NPU.
- Support for four independent 4K displays or two independent 8K displays.
To determine the features and capabilities implemented by our ecosystem collaborators, see Hardware.
Reference Implementations
Prebuilt and validated reference implementations are available for developers to test and deploy industrial, retail, and healthcare applications enabled for computer vision.
Your experience may vary depending on the configuration of your developer kit. For details, see the target system requirements in the reference implementation.
Hardware
AAEON* UP Xtreme i14
- Enabled MIPI-CSI2 interface.
- Enables flexible deployment in a slim and compact chassis with ample I/Os for expansion options.
ASRock Industrial* NUC BOX-155H
- 2 x 262-pin SO-DIMM DDR5 5600 MHz up to 96 GB (48 GB per DIMM)
Asus* NUC 14 Pro
- Uses Intel vPro® Enterprise for exceptional security, manageability, and stability.
Innodisk* APEX-E100
- Built-in Intel® Arc™ GPU
- Intel® AI Boost integrated neural processing unit (NPU)
- Enabled MIPI CSI-2* and Gigabit Multimedia Serial Link (GMSL) interface
- Supports Innodisk MIPI fixed-focus camera modules: EV2M-OOM1, EV2M-GOM1, and EVDM-OOM1
Seavo* PIR-1014A AIoT Developer Kit
- Provides interface support for HDMI in.
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