Application of VPU and future development trends

I. The Meaning of VPU

VPU stands for Video Processing Unit. It is a processor specifically designed for processing video signals and is also known as a video accelerator or video low-level processor. The VPU is independent of the CPU and can execute various efficient video processing tasks, such as video encoding and decoding, image processing, video analysis, etc., thereby improving the visual experience and video processing efficiency of devices.

II. Differences between VPU and GPU

Both VPU (Video Processing Unit) and GPU (Graphics Processing Unit) are processors used for processing visual information, but they differ in design and application. The following are their main differences:

As can be seen from the above table, VPU and GPU are different in terms of functions, application scenarios, advantages, and disadvantages. The VPU is more focused on video processing, features high efficiency and low power consumption, and is suitable for mobile devices and applications with extremely high requirements for video processing. On the other hand, the GPU has powerful parallel processing ability and high throughput and is applicable in fields such as games, graphic design, scientific visualization, and machine learning. When choosing between VPU and GPU, it is necessary to measure which processor is more suitable according to the requirements of specific application scenarios. For example, in scenarios of real-time video processing and analysis, the VPU may be a better choice; while in scenarios requiring complex graphics rendering and general-purpose computing, the GPU is more appropriate.

III. Applications of VPU

As a chip specifically designed for video processing, VPU (Video Processing Unit) has a wide range of applications in multiple fields. The following are the main application areas of VPU:

1. Video Encoding and Decoding

The VPU can efficiently handle video encoding and decoding tasks and supports high-definition video encoding and decoding of 4K or even 8K. This is crucial for meeting the growing demand for high-definition videos and is widely used in both consumer-level applications such as video conferencing, live streaming, and short-video apps, as well as in industrial-level surveillance systems and video editing software.

2. Computer Vision

The VPU also has extensive applications in the field of computer vision, including but not limited to:

• Object Detection: In intelligent surveillance systems, the VPU can analyze video streams in real time to detect and identify specific objects, such as pedestrians and vehicles.
• Image Segmentation: In medical image processing, the VPU can help doctors more accurately segment diseased areas to assist in diagnosis.
• Pose Estimation: In sports analysis, motion capture, and other fields, the VPU can analyze human postures in real time to provide data support for training and evaluation.

3. AI Acceleration

The application of VPU in the field of artificial intelligence is mainly reflected in accelerating AI models. For example, Intel's VPU can efficiently handle matrix operations and is particularly good at sparsification processing, which is very helpful for accelerating the inference process of deep learning models. In generative AI applications, such as Stable Diffusion, the VPU can work in collaboration with the CPU and GPU to lower the threshold for using generative AI, enabling ordinary thin and light notebooks to run complex AI models.

4. Video Conferencing and Live Streaming

In video conferencing and live streaming applications, the VPU can provide high-definition, low-latency video processing capabilities to ensure the smoothness and clarity of conferences and live broadcasts. Meanwhile, the VPU can also implement functions such as video background blurring and intelligent noise reduction to enhance the user experience.

5. Industrial Vision

In the fields of industrial automation and quality inspection, the VPU can be used to analyze and process image and video data captured by industrial cameras to achieve functions such as defect detection, dimension measurement, and assembly verification, thereby improving production efficiency and product quality.

6. Autonomous Driving

In autonomous driving systems, the VPU can process video data from cameras to identify roads, pedestrians, vehicles, etc., providing support for autonomous driving decisions.

7. Virtual Reality (VR) and Augmented Reality (AR)

In VR and AR devices, the VPU can process high-resolution video streams to provide an immersive visual experience. Meanwhile, the VPU can also implement real-time video analysis to provide users with a more realistic interactive experience.

8. Video Editing and Special Effects Processing

In video editing software, the VPU can accelerate video rendering and special effects processing to improve editing efficiency. For example, Adobe's video editing software can utilize the VPU to accelerate functions such as filters, automated processing, and intelligent matting.

9. Smart TVs and Set-Top Boxes

In smart TVs and set-top boxes, the VPU can provide a smooth video playback experience, support decoding of multiple video formats, and can also implement real-time video processing, such as picture quality enhancement and motion compensation.

10. Drones and Robots

In drone and robot applications, the VPU can process video data from cameras to achieve functions such as obstacle avoidance, path planning, and target tracking, improving the autonomy and safety of the devices.

IV. Applications of VPU in Video Processing Technology

The Video Processing Unit (VPU) is a hardware accelerator specifically designed for video processing. It has significant advantages in improving video processing efficiency, reducing power consumption, and latency. The following explores in detail the role and technical principles of VPU in different video processing application scenarios.

1. Live Streaming and Cloud Gaming

In live streaming and cloud gaming scenarios, low latency and high compression efficiency are crucial indicators. The VPU performs excellently in these aspects by combining AI technology and dedicated hardware acceleration modules. For example, the VPU of Rongming Microelectronics has achieved low latency and high compression efficiency in live streaming and cloud gaming, significantly reducing power consumption and improving video processing efficiency.

Technical Details:

• Low Latency Technology: The VPU utilizes an efficient cache mechanism and pipeline design to reduce processing latency and ensure that video frames can be quickly transmitted and processed.
• High Compression Efficiency: By adopting advanced video compression algorithms (such as H.265/HEVC and AV1), the VPU significantly reduces the size of video files while ensuring video quality, saving bandwidth and storage resources.

2. Video Surveillance

The video surveillance industry requires long-term, high-reliability video recording and playback functions. The VPU provides high-quality, low-power solutions by optimizing the video encoding and decoding process to meet the needs of video surveillance. For example, the VPU provides stable video stream processing capabilities and efficient video analysis functions in video surveillance systems.

Technical Details:

• Video Encoding and Decoding Optimization: The VPU has been optimized for common video surveillance encoding standards (such as H.264 and H.265), improving encoding quality and speed.
• Low Power Consumption Design: Through hardware acceleration, the VPU reduces dependence on the CPU, thereby reducing the overall power consumption of the system, making it suitable for video surveillance devices that operate for long periods.

3. 5G and Mobile Video

The promotion of 5G technology has brought higher bandwidth and lower latency, providing better basic conditions for mobile video applications. The VPU enables a smoother and richer video experience on mobile devices by efficiently processing high-definition and ultra-high-definition videos. For example, the VPU has achieved efficient video transmission and playback in the 5G environment, enhancing the user's video experience.

Technical Details:

• Efficient Video Transmission: The VPU supports the latest video encoding standards (such as AV1) to provide higher-quality video transmission under limited bandwidth.
• Mobile Device Optimization: In view of the characteristics of mobile devices, the VPU adopts an energy-saving design and is compatible with multiple mobile operating systems, facilitating integration and use.

4. VR/AR and Metaverse

The development of virtual reality (VR) and augmented reality (AR) technologies has put forward higher requirements for video processing. The VPU provides technical support for VR and AR applications through its powerful video processing capabilities and AI acceleration. For example, the VPU has achieved high-quality video rendering and real-time video processing in the VR/AR environment, enhancing the user experience.

Technical Details:

• High-Quality Video Rendering: The VPU integrates AI acceleration functions and can process complex video rendering tasks in real time to provide a realistic visual effect.
• Real-Time Video Processing: In metaverse applications, the VPU can process a large amount of video data in real time to support multi-user interaction and high-quality video communication.

As a professional video processing hardware accelerator, the VPU demonstrates great potential and advantages in various video processing scenarios through its unique technology and optimized design. From live streaming, cloud gaming to video surveillance, and then to 5G mobile video and VR/AR applications, the VPU provides efficient, low-power, and low-latency solutions, promoting the development and application of video technology. With the continuous progress of technology, the VPU will play an increasingly important role in the field of video processing in the future.

V. Advantages of VPU in Video Encoding and Decoding

The VPU (Video Processing Unit) is an accelerator optimized for video processing. It has built-in dedicated functional modules for video encoding acceleration and features high performance, low power consumption, and low latency. Compared with traditional CPUs, the VPU has the following advantages in video encoding and decoding:

• High Efficiency: The VPU has been specifically optimized for video encoding and decoding tasks and can provide higher processing efficiency. When faced with massive video encoding and decoding requirements, the VPU can respond quickly and effectively relieve the burden on the CPU.

• Low Energy Consumption: Since the VPU is designed to process video data, its energy consumption is relatively low. This means that when processing the same amount of video data, the energy consumption of the VPU is much lower than that of traditional CPUs, helping to reduce the overall operating cost.

• Professionalism: The professionalism of the VPU in video encoding and decoding enables it to better handle high-definition videos, such as the encoding and decoding of 4K or even 8K, meeting the needs of the popularization of high-definition. This is particularly important for applications such as online conferences, industrial quality inspection, and security.

• Flexibility: The design of the VPU allows it to be flexibly deployed in different devices and environments. Whether in cloud data centers or on end-side devices, such as mobile phones, cars, security systems, drones, etc., it can provide efficient video encoding and decoding performance.

• Compatibility: The VPU supports multiple video formats, such as H.264, H.265, VP9, etc., which enables it to be widely used in different video processing scenarios and provides computing support for Internet video vendors.

• Reducing CPU Load: During the process of video transcoding, the VPU can complete tasks independently without the involvement of the CPU data plane, thereby reducing the performance consumption of the host CPU and lowering the transcoding latency.

• Supporting Multicast Mode: The VPU has also developed a multicast mode according to the characteristics of Internet video needs. It can perform derivative operations on input videos and can support operations to derive up to 4 videos from 1 input video, with each input video being able to adjust frame formats, resolutions, and other attributes separately.

In summary, the advantages of the VPU in video encoding and decoding lie in its high efficiency, low energy consumption, professionalism, flexibility, compatibility, reduction of CPU load, and support for multicast mode. These advantages make the VPU an ideal choice for handling video encoding and decoding tasks.

VI. Tasks of VPU in the Field of Autonomous Driving

The VPU (Visual Processing Unit) is a processor specifically designed for processing visual data and plays an important role in the field of autonomous driving. The following are the main tasks of the VPU in the field of autonomous driving:

• Visual Data Processing: The VPU is responsible for processing visual data from vehicle-mounted cameras, including vehicle recognition, pedestrian recognition, road sign recognition, lane line segmentation recognition, and emergency event recognition.

• Image Recognition: Image recognition is the part that consumes the most computing power in autonomous driving chips. The VPU processes relevant video graphics by combining hardware acceleration (HWA) and software acceleration (DWA), improving processing efficiency and accuracy.

• Multi-sensor Fusion: The VPU can be fused with data from other sensors (such as radar and lidar) and analyzed and comprehensively judged through artificial intelligence technology to command the actuators of the vehicle to achieve a higher level of autonomous driving.

• Real-time and Low Power Consumption: The VPU is designed with an emphasis on real-time performance and low power consumption to meet the requirements of autonomous driving for fast response and energy efficiency.

• Supporting High-level Autonomous Driving: With the development of autonomous driving technology, the performance of the VPU is constantly improving to support more advanced autonomous driving tasks, such as depth estimation and target tracking.

In summary, the tasks of the VPU in the field of autonomous driving mainly focus on visual data processing, image recognition, multi-sensor fusion, and supporting high-level autonomous driving. Together, they ensure the efficient, safe, and intelligent operation of autonomous driving systems.

VII. How Will VPU Influence Video Processing Technology in Its Future Development Trends?

1. Future Development Trends of VPU

• High-Definition Encoding and Decoding Capabilities: Future VPUs will possess powerful high-definition encoding and decoding capabilities, especially for processing 4K and 8K videos. For example, the second-generation VPU chip Quadra of Rongming Microelectronics supports the AV1 encoding format. It is the world's first data center-level hardware encoding chip that supports this format. The performance of this chip is equivalent to that of 100 high-end X86 server CPUs and, combined with a built-in artificial intelligence engine, can execute 18 trillion AI computing operations per second. It is applicable to video scenarios such as AI, VR, AR, and AIGC. Such capabilities will significantly enhance the intelligence and efficiency of video processing.

• Integration with AI: VPUs will be increasingly integrated with AI technology to achieve more intelligent video processing. For example, content recognition and encoding optimization in video processing can be automated and made intelligent through AI. This integration can not only improve the efficiency of encoding and decoding but also enable more complex video analysis and processing tasks, such as real-time object recognition and behavior analysis.

• Low Latency and High Efficiency: Future VPUs will continue to optimize low-latency and high-efficiency video transmission. For example, the VPU products of Rongming Microelectronics have been widely deployed among domestic and international customers and have received extensive praise in terms of stability, picture quality, performance, latency, power consumption, and cost. These VPU products have been optimized to maintain low latency while processing videos with a high compression ratio, making them particularly suitable for scenarios of real-time video transmission and processing.

• Multimodal Processing: Future VPUs will be able to handle multimodal data, combining video, audio, and inputs from other sensors to achieve richer media processing capabilities. This multimodal processing ability will make VPUs more proficient in complex application scenarios, such as in the fields of intelligent security and autonomous driving.

2. How It Will Influence Video Processing Technology

• Improve Processing Efficiency and Reduce Costs: Through its architecture specifically designed for video processing, the VPU can significantly improve the efficiency of video processing. For example, the VPU products of Rongming Microelectronics can significantly reduce the total cost of ownership (TCO) in high-computing-power scenarios such as live streaming, security monitoring, and cloud desktops. This means that when enterprises process the same amount of video data, they can greatly reduce the required traditional CPU/GPU resources, thereby reducing operating costs.

• Support High-Definition and High-Frame-Rate Videos: The powerful encoding and decoding capabilities of the VPU make it possible to process high-definition (4K/8K) and high-frame-rate videos. Future video processing technology will no longer be limited by the current resolution and frame rate constraints but will be able to smoothly process video data of higher specifications. This will greatly enhance the viewing experience of users, especially in VR and AR applications.

• Enable Real-Time Video Analysis and Processing: Combined with AI technology, the VPU will make real-time video analysis and processing the norm. For example, in video surveillance, the VPU can implement functions such as real-time face recognition and behavior analysis, thereby greatly improving the reaction speed and accuracy of security systems. This real-time processing ability can also be widely applied to other fields, such as instant replay analysis in sports events and quality control on industrial production lines.

• Promote the Development of Video-Intensive Applications: The powerful processing capabilities and low-latency characteristics of the VPU will promote the development of video-intensive applications, such as cloud gaming, video conferencing, and online education. These applications have high requirements for video quality and real-time performance. The introduction of the VPU will enable these applications to be implemented and promoted on a larger scale with high quality.

In summary, the future development trends of the VPU will profoundly influence video processing technology at multiple levels, bringing revolutionary changes from the underlying hardware architecture to the implementation of high-level applications. These changes will not only be reflected in the improvement of technical indicators but, more importantly, will open up a series of new application scenarios and business opportunities.

VIII. Future Development Trends of VPU and Their Impact on Video Processing Technology

With the rapid expansion of industries such as 5G, mobile video, cloud gaming, cloud desktops, VR/AR, and the metaverse, the market demand for dedicated video processing chips is growing explosively. Some studies predict that the VPU market scale may reach hundreds of billions of dollars in the next few years. In addition, with the progress of AI technology, the role of VPU in video processing technology will become more prominent. For example, in aspects such as video content generation and video analysis, the VPU can provide more efficient processing capabilities, promoting the development of video processing technology in an intelligent direction.

IX. Summary

In summary, in its future development trends, the VPU will continue to deepen its application in video processing technology, especially in aspects such as improving processing speed, reducing energy consumption, and enhancing intelligent processing capabilities. With the continuous progress of technology, the VPU is expected to play a more important role in the field of video processing and promote the development of the entire industry.