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Edge Computing

Edge Computing for Real-Time Industrial Systems

Industrial systems increasingly rely on edge computing to process data closer to machines, sensors, and control systems. By moving compute and intelligence to the edge, manufacturers can reduce latency, improve reliability, and enable real-time decision making on the factory floor. Altera FPGAs provide the flexibility, deterministic performance, and hardware acceleration needed to run AI inference, signal processing, and industrial protocols efficiently in demanding edge environments.

Why Altera FPGAs

Real-Time Performance

Altera edge computing solutions process data locally, enabling ultra-low latency responses for time-sensitive applications like industrial automation, robotics, and smart infrastructure.

Flexible and Scalable Architecture

With FPGA-based acceleration, Altera platforms can be reconfigured and optimized for evolving workloads, giving businesses the flexibility to adapt without replacing hardware.

Efficient AI at the Edge

Altera enables AI inference directly at the edge, reducing bandwidth costs and cloud dependency while improving privacy, reliability, and operational efficiency.

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Solutions

Video, Imaging IP and Connectivity Solutions

Altera provides a comprehensive portfolio of video imaging and machine vision IP solutions for high-performance industrial vision systems. These solutions include video processing pipelines, image enhancement, and high-speed interface connectivity supporting standards such as MIPI, CoaXPress, GigE Vision, USB3 Vision, and SLVS-EC. With ready-to-use IP cores and reference designs, Altera FPGAs enable scalable architectures for smart cameras, frame grabbers, and AI-enabled inspection systems requiring reliable, high-bandwidth image processing.

Altera Video Solutions Stack
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FPGA AI Suite

FPGA AI Suite

The FPGA AI Suite enables developers to deploy AI inference on Altera FPGAs using a streamlined software flow. It allows machine learning models from common frameworks to be converted into optimized FPGA inference IP using tools such as OpenVINO and Quartus. With automated model conversion, design-space optimization, and software emulation for early validation, the suite accelerates development of efficient FPGA-based AI solutions for edge and embedded applications. 

  • Convert trained AI models into optimized FPGA inference IP using automated development flows.
  • Accelerate AI deployment with push-button optimization and seamless integration with Quartus design tools.
  • Support popular AI frameworks and Open Model Zoo for rapid AI inference deployment.
FPGA AI Suite
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