Graphics & Vision IP Cores for UMC

Graphics and Vision IP cores provide the hardware acceleration engines required for image processing, video analytics, visual computing, and display management in advanced SoC and ASIC designs.

This category includes GPU, ISP (Image Signal Processor), Video Processing, Display Controller, Image Conversion, and Vision Subsystem IP cores. These solutions enable functions such as graphics rendering, image enhancement, video encoding and decoding, color space conversion, display management, camera processing pipelines, and real-time computer vision acceleration.

This catalog allows semiconductor engineers to evaluate and compare Graphics and Vision IP solutions from multiple vendors based on supported video standards, image quality, AI vision capabilities, throughput, latency, power consumption, silicon area, and process node compatibility.

Whether developing automotive ADAS platforms, AI-enabled edge devices, smart cameras, industrial vision systems, AR/VR applications, mobile processors, or multimedia SoCs, engineers can identify the Graphics and Vision IP cores best suited to their performance, power, and integration requirements.

 
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What are graphics and vision IP cores?

Graphics and vision IP cores are reusable hardware blocks used to process, analyze, and render visual data in SoCs and ASICs. They enable efficient handling of images, video streams, and graphical interfaces.

These IP cores are optimized for high-throughput visual workloads and are essential for modern applications involving display systems, camera processing, and AI-based vision.

Main types of graphics and vision IP

GPU IP cores

GPU IP accelerates graphics rendering and parallel processing, supporting applications such as user interfaces, gaming, and compute workloads.

Image Signal Processor (ISP) IP

ISP IP processes raw data from image sensors, performing tasks such as noise reduction, color correction, and image enhancement.

Video codec IP

Video codec IP handles video encoding and decoding, supporting standards such as H.264, H.265/HEVC, and AV1.

Computer vision and AI vision IP

Vision processing IP accelerates tasks such as object detection, image recognition, and video analytics, often in combination with AI accelerators.

Key features of graphics and vision IP cores

  • High-throughput image and video processing
  • Support for high resolutions (HD, 4K, 8K)
  • Energy-efficient processing for embedded systems
  • Integration with display and camera pipelines
  • Compatibility with AI and compute acceleration

How to choose graphics and vision IP

Selecting the right IP depends on your application and performance requirements:

  • Type of workload (graphics rendering, video, vision processing)
  • Resolution and frame rate requirements
  • Power and area constraints
  • Software and API support
  • Integration with other system components

Applications of graphics and vision IP

  • Mobile and consumer electronics
  • Automotive systems (ADAS, digital cockpit)
  • Surveillance and security systems
  • Industrial vision and robotics
  • AR/VR and multimedia applications

Compare graphics and vision IP cores from leading vendors

This catalog provides access to a wide range of graphics and vision IP cores from leading providers.

Use filters to compare solutions based on performance, power efficiency, resolution support, and integration requirements.

Frequently asked questions about graphics and vision IP cores

What is a graphics IP core?

A graphics IP core is a hardware block used to render images and visual interfaces in SoCs and ASICs.

What is vision IP?

Vision IP refers to hardware blocks that process and analyze image and video data, often used in computer vision and AI applications.

What is an ISP IP?

An Image Signal Processor (ISP) IP processes raw sensor data to produce high-quality images.

Where are graphics and vision IP cores used?

They are used in mobile devices, automotive systems, surveillance, industrial applications, and multimedia systems.

How do I choose graphics and vision IP?

You should consider workload type, performance requirements, power constraints, and integration needs.

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