Embedded gpu

Types of Embedded GPUs

The embedded GPU market is expected to grow by 6.5% CAGR between 2023 and 2028. GPUs are essential for rendering the visual output needed in different industries, which is driving market growth. Analysts expect the market to reach $8.5 billion by 2028 from the $5.6 billion registered in 2023.

Embedded GPUs are manufactured as part of a system rather than as an independent component to create a specific system. They are built into an SoC (System on a Chip) alongside other necessary components like CPUs, memory controllers, and I/O interfaces. This helps to perform graphics and visual computing functions more efficiently. There are various types of embedded GPUs, including:

• Programmable Embedded GPUs

  This type of GPU allows users to develop and implement customized shaders and algorithms for rendering and post-processing via an open API framework. It offers flexibility to adjust graphics processing pipelines to meet specific applications and workloads.

• Ray Tracing Embedded GPUs

  Ray tracing is a rendering technique for simulating light behavior accurately to create photorealistic images. Integrated ray tracing GPUs enable real-time ray tracing capabilities in applications such as product design visualization, architectural rendering, and scientific simulations.

• Embedded Workstation GPUs

  Workstation GPUs have high computing power for professional-grade applications such as 3D modeling, CAD/CAM, and data visualization. They are used in embedded systems requiring heavy graphics processing tasks, like virtual reality development and mechanical design.

• Edge AI Embedded GPUs

  These GPUs are designed for deploying artificial intelligence (AI) and machine learning (ML) models at the edge, close to data sources. They enable real-time inference for computer vision, natural language processing, autonomous systems, and other AI-powered applications.

• Power-efficient Embedded GPUs

  These are embedded GPUs optimized for low power consumption while providing sufficient performance for battery-operated or power-constrained devices. They are suitable for mobile phones, tablets, embedded cameras, drones, and other hardware requiring efficient power utilization.

• Safety-Certified Embedded GPUs

  This type of GPU is certified for use in safety-critical applications and environments, such as avionics systems, industrial automation, and medical devices. It complies with safety standards and regulations, ensuring reliable operation in critical embedded system applications.

Features and Functions of Embedded GPUs

The embedded GPU has a wide array of functions. The following is a non-exhaustive list of key functions:

• Graphics rendering: The primary function of a GPU, whether embedded or discrete, is to render high-quality graphics for the purpose of visualization. This may be in the form of graphic rendering or creating an immersive experience while gaming. An embedded GPU is capable of rendering complex graphic-intensive applications, 3D animations, and games with minimal latency.
• Video encoding and decoding: An embedded GPU is useful in applications that require video streaming, such as media playback and video conferencing. It takes the burden off a CPU by accelerating video encoding and decoding tasks. This ensures lower power consumption and provides seamless video streaming.
• Energy efficiency: For applications such as automotive and mobile, GPU consumption is critical. An embedded GPU is useful in these applications because it is designed to provide a high level of performance per watt. This prolongs the lifespan of the battery-powered device.
• Parallel processing: The strength of an embedded GPU lies in its ability to perform parallel processing. It has a large number of cores that can work in unison to perform multiple tasks at the same time. This enhances multitasking and accelerates application loading times, which results in system responsiveness.
• Machine learning and AI functions: Modern embedded GPUs are designed with machine learning and artificial intelligence functions in mind. They can execute ML and AI workloads in real time and enhance decision-making processes in various applications, from smart surveillance systems to autonomous vehicles.

The functions are dependent on the model type and embedded system capabilities. The following are some key functions of an embedded GPU:

Applications of Embedded GPUs

Embedded GPUs provide flexible solutions across many different industries and applications, including:

• Automotive*

  Embedded GPU systems make up an important part of modern automobiles in charge of many critical driver-assist functions and vehicle monitoring systems. GPUs allow for real-time data processing from multiple sensors (cameras, LiDAR, RADAR, etc.) that are integral for advanced driver assistance systems (ADAS), self-parking features, and surrounding object detection and alerts.

• Medical Imaging*

  In medical ultrasound devices, MRI machines, and other imaging equipment, embedded GPUs enable fast processing of large imaging data sets, facilitating real-time image reconstruction, enhancement, and analysis for diagnostic applications. This helps produce quality results to aid doctors in making decisions for treating patients.

• Surveillance Cameras

  Embedded GPUs process high-definition video streams from security cameras for real-time monitoring, recording, and analytics, including motion detection, facial recognition, and license plate recognition.

• Consumer Electronics

  Today's consumer electronics, such as smart TVs, gaming consoles, and tablets, rely on embedded GPUs for rendering high-resolution graphics and video playback, enabling rich multimedia experiences and interactive applications.

• Robotics

  GPU-embedded systems are integral to robot control, perception, and manipulation. GPUs allow for real-time processing of sensor data (cameras, LiDAR, IMUs) for localization, mapping, path planning, and object recognition to facilitate autonomous operating in complex environments.

• Aerospace and Defense

  embedded GPU technologies are used in avionics, missile guidance, surveillance drones, and various other military applications. High-performance GPUs offer capabilities for real-time processing of radar, sensor fusion, target tracking, and high-resolution imaging in critical aerospace and defense situations.

• Industrial Automation

  Embedded GPUs can be employed in factory automation systems for machine vision, quality control, predictive maintenance, and other automated tasks that require real-time data processing and analysis to optimize production efficiency.

• Gaming and AR/VR

  Built-in GPUs provide the graphical power and performance required to render complex game graphics and immersive environments in augmented and virtual reality applications. High-performance GPU capabilities enable realistic simulation and interaction for enriched gaming and AR/VR experiences.

How to Choose Embedded GPUs

There are a few important factors to consider when choosing an embedded GPU that suits a particular application's needs. They include;

• Performance: When looking for an embedded GPU, one of the most important things to know is the workload it will handle. It's imperative to take into account the embedded system's processing capacity and memory needs because these qualities will have a big influence on performance.
• Form factor: Size, weight, and power consumption restrictions are imposed on embedded systems; thus, selecting a GPU with the appropriate form factor is crucial. It is best to choose a GPU with a small size if space is at a premium.
• Power consumption: A vital part of embedded system design is power management. It is important to choose a GPU with higher energy efficiency and low power consumption. Such a GPU will provide great performance while extending battery life.
• Thermal performance: The GPU embedded in the system's design can affect its cooling requirements. Ensuring that the embedded GPU has good thermal performance will prevent overheating and maintain reliability.
• Scalability: With scalability, the GPU can adapt to different workload demands. It is beneficial to select a GPU that offers consistent performance.
• Cost: It is crucial to consider the entire cost embedded system design will incur. Although choosing a less expensive embedded GPU may be tempting, it is beneficial to evaluate long-term performance and reliability.
• Connectivity: Consideration should be given to the GPU's connectivity options, such as ports and interfaces, which can impact system compatibility and peripherals support. Additionally, verifying that the embedded GPU can meet the requirements of the intended application is crucial.
• Compatibility: A thoroughly evaluated and compatible embedded GPU will work harmoniously with the targeted CPU, memory, and other system components. This will help prevent embedded system performance, stability, and functionality issues.
• Support and resources: It is imperative to select an embedded GPU that provides adequate support and resources. Such a GPU will have documentation, drivers, and software development kits, which are essential for developers in order to optimize performance and program embedded systems.

Q&A

Q1. What is the difference between a CPU and an embedded GPU?

A1. The CPU handles the general processes of the computer and contributes to rendering basic graphics, while the main duty of an embedded GPU is to render graphics and handle video processing. An embedded GPU is more powerful than a CPU with integrated graphics, but both work together to ensure the system functions properly.

Q2. Can a GPU be embedded into a motherboard?

A2. Yes, some motherboards come with an embedded GPU, which might be in the form of a chip known as a video output connector that can include a VGA, HDMI, or DVI port. This type of GPU is known as a graphics card that's integrated into the motherboard and shares memory with the CPU.

Q3. How are GPUs used in embedded systems?

A3. An embedded GPU processes and calculates all the data that's related to graphics and displays it on the screen, delivering an excellent visual experience. The designer of the embedded system determines the type of GPU and how it will be used in the application and system/project.

Q4. What benefits does an embedded GPU deliver?

A4. Better performance is delivered by parallel processing that increases the speed of an application. It offers excellent graphics and visual experiences while freeing the CPU to handle general tasks, resulting in decreased power consumption.