Edge AI Hardware Considerations
Whether training models, fine-tuning them, or deploying them at the edge, choosing the right AI hardware can help businesses right-size their investment and support performance requirements.
For an example, central processing units (CPUs) with built-in accelerator engines can help power many advanced edge AI workloads without the need for specialized hardware and GPU solutions can help power the most demanding workloads in the data center, at the edge, or in end user devices.
Intel® Processors & Intel® ARC GPUs for the Edge
Explore Intel® Processors and ARC GPUs for edge computing. Discover enhanced AI, graphics, and media processing capabilities. Click "Learn more" to see how these technologies boost your edge AI solutions.
Intel® Processors for the Edge
Discover Intel Edge Processors that are able to power vision, generative AI and data processing at the edge.
Intel® ARC GPUs for the Edge
Supercharge Edge AI, Graphics, and Media Processing with Intel Arc Graphics discrete GPU
Intel® AI Edge Systems Sizing
Intel AI Edge Systems offer balanced, efficient, and scalable solutions. For further sizing guidelines, see below and use the sizing tool.
Intel® AI Edge Systems sizing guide breakdown by following
- Mainstream and Entry Edge AI offers a good balance between compute, inferencing, TCO and low power.
- Efficiency Optimized Edge AI enhances AI performance with integrated CPU, GPU and NPU, ideal for low power while maximizing the potential performance.
- Scalable Performance Edge AI delivers adaptable AI performance with build-in AI accelerator and the option to add discrete GPU of your choice, including Intel GPUs
Intel® AI Edge Systems Sizing Tool
Intel® AI Edge System Sizing Tool helps solution developers to streamline hardware selection for optimized system level Edge AI performance.
Intel® AI Edge System Sizing Tool offers several benefits for solution developers:
- Optimized Resource Allocation: Helps developers choose the right balance of CPU, GPU, and NPU resources for specific AI workloads, ensuring efficient use of hardware.
- Cost Efficiency: Assists in selecting configurations that meet performance needs while minimizing total cost of ownership (TCO).
- Performance Prediction: Provides insights into expected performance outcomes, enabling developers to make informed decisions about system capabilities.
- Scalability Planning: Facilitates planning for future growth by suggesting scalable solutions that can adapt to increasing demands.
Access to sizing tool will be made available in Q2.