- Get in Touch with Us
Last Updated: Apr 25, 2025 | Study Period: 2024-2030
The graphics processing unit (GPU) had already progressed from its own modest beginning as a display device adapter in arcade machines to a computer processing frontrunner that powers artificial intelligence technology, gaining speed parallel computing workflows in sectors ranging from oil and gas exploration to natural language processing.
GPUs, in particular, are becoming increasingly important in the rapidly expanding innovations of autonomous vehicles and enhanced driver-assistance technologies (ADAS).
Imaginary Technologies provides a GPU product portfolio exclusively for transportation components, incorporating safety and reliability all across the development to reduce the need for system-level safety involvement while achieving ISO 26262 regulations.
Imagination relies heavily on the automobile sector. It detects both transient and persistent errors in every block of the GPU. These include mechanical systems which incorporate hardware methods that conduct safety-critical operations across computation and graphics while optimising speed to preserve data presented on electronic dashboard screens.
A normal CPU, on the other hand, consists of a few cores with plenty of cache memory and is typically intended to handle only a few software threads at a time.
CPUs are designed for sequential serial processing, which is adequate for the majority of basic computing operations. However, when it comes to processing large volumes of data at the same time, the GPU tends to do the work as needed.
The processing needs of autonomous cars and ADAS technologies are entirely within the capabilities of GPUs, particularly in image analysis and parallel signal processing. Image processing is a natural problem area for a GPU designed for gaming.
| S No | Overview of Development | Development Detailing | Region of Development | Possible Future Outcomes |
| 1 | AMD, Intel, And NVIDIA, Announce New CPU, GPU And Automotive Processors At CES 2022 | Many new products were announced by Intel AMD and NVIDIA that cover next-generation CPUs, next-generation and all-new GPUs, and next-generation automotive processors. | Global Scale | This would enhance better Technologies and production |
Additional mechanism underlying the GPU industry is the increasing use of processors to enable graphics applications and 3D content in many industries worldwide such as automotive and related industries.
CAD and simulation tools, for example, use GPUs to produce lifelike graphics or animations to help production and design applications in the automobile sector.
Due to the widespread use of hardware components such as integrated and dedicated processors in devices such as computers, game consoles, and smartphones to enable graphics-intensive workloads, GPU technology accounted for a significant percentage of the industry.
In the equipment sector, the hybrid GPU market will rise rapidly because hybrid processors offer the capabilities of both integrated and dedicated GPUs, making them a popular choice amongst computer programmers for enhancing the productivity of graphical fidelity applications.
Companies are quickly embracing cloud-based solutions to benefit from the related scalability and performance, therefore the usage of a cloud â based deployment strategy will grow.
The main cloud platform companies, such as Microsoft, Amazon Web Services, and IBM, are forming alliances with graphics chip vendors to enable on-demand GPU cloud computing.
The primary drivers driving market expansion include increased expenditures in research and development of AI and VR automotive platforms, as well as continued developments in graphics processing units.
Furthermore, the developing electronics industry, increased use of portable devices, and emphasis on better visual content are offering profitable potential for market growth.
Along with this, government investment for virtual reality and the advent of multiple machine learning firms are expected to boost the industryâs growth.
This same transportation industry is likely to make a significant contribution to development, owing to a continuous trend in which vehicle manufacturers continue improving their various intelligent and healthier vehicles on the roadway.
The Global Automotive Graphic Processor Unit Market can be segmented into following categories for further analysis.
Graphics Processing Units (GPUs) have been widely employed to boost the performance of many deep learning applications. GPUs can deliver high computational power and throughput attributable to hundreds or even thousands of operating threads and a vast quantity of hardware compute units.
The calculations of deep neural networks are ideally suited to GPU architecture. Because deep neural network training might span weeks or months, processing speed and efficiency. Indeed, several of profound learningâs breakthroughs would not have been found if GPUs had not been widely available.
Deep learning requires a large number of matrix multiplications and other operations, which may be massively parallelized and hence accelerated on GPUs. AI is being used in IoT applications for algorithms such as image perception and speech synthesis.
GPUs have been employed for AI amplification in embedding SoCs and participate in the training process of AI on mainframe computers within those scenarios.
It is also popularly referred to that one of the key AI applications powered by GPUs is driverless mobility. Various phases for autonomous driving are routed through GPU systems for a variety of reasons.
First, because of the vast size of resources required, the AI training stage for automated vehicles takes place in a server-scale environment; server systems often expedite AI instruction using multi-GPU processors.
Whenever a driverless car is driving, the induction step of AI runs, and also many businesses create specific embedded circuits for particular automobiles to speed up the inference process. GPUs are used on multi-processor boards.
The expanding sign and graphics business, as well as increasing preference for digital applications, are likely to drive economic growth. Furthermore, the modernisation of consumer lifestyles, along with increased desire for automotive personalisation, is expected to have a beneficial influence on market growth.
Improving living standards, along with rising disposable income levels, particularly in developing countries such as China as well as India, have a vital influence in raising product performance. To improve their product portfolios, key players in the market are pursuing methods such as strategic partnerships, mergers & acquisitions, through introduction of new products.
NVIDIA is one of the leading developers of the current market of operations focusing on the GPU Automotive integrations over the global scale of operability. NVIDIA DRIVE Hyperion 8 is a computational framework and sensing suite designed for fully autonomous systems.
This cutting-edge technology is developed for the greatest degree of cognitive reliability as well as security, and it has been backed by detectors from a diverse range of high â quality manufacturers, including Continental, Hella, Luminar, Sony, and Valeo. DRIVE Hyperion is now available for makes and models from 2024.
DRIVE Hyperion, including its fundamentally safe AI computation architecture at its heart, provides a safe foundation for automated vehicle innovation. Dual NVIDIA DRIVE Orin systems-on-a-chip provides resilience and fail-over security, including plenty of computational power for level 4 self-driving and intelligent cockpit functionalities.
NVIDIA Ampere architecture GPUs are also included in the DRIVE Hyperion 8 development kit. This high-performance computation provides plenty of room for developers to test and check their code.
Imagination Technologies has been developing new operational automated driving systems focused GPUs in the global market. The PowerVR technologyâs virtualization technology features allow it to run several software packages (OS) on a single GPU core with minimal performance consequence.
The PowerVR architecture also includes a full basic functioning for troubleshooting and tweaking, as well as a wide range of automotive ecosystem relationships. Imaginationâs most current GPU family, the PowerVR Series9XTP, is based on the Furian architecture.
Its high-performance density is appropriate for the automotive industry due to considerable power/performance/area (PPA) optimizations. This has also brought Hyperlane technologies to the industry.
Hyperlane is a type of hardware virtualization that contains a hypervisor software in hardware multiple virtual environments may be switched in and out of the Graphics processing units without the need for external interference.
| Sl no | Topic |
| 1 | Market Segmentation |
| 2 | Scope of the report |
| 3 | Abbreviations |
| 4 | Research Methodology |
| 5 | Executive Summary |
| 6 | Introduction |
| 7 | Insights from Industry stakeholders |
| 8 | Cost breakdown of Product by sub-components and average profit margin |
| 9 | Disruptive innovation in the Industry |
| 10 | Technology trends in the Industry |
| 11 | Consumer trends in the industry |
| 12 | Recent Production Milestones |
| 13 | Component Manufacturing in US, EU and China |
| 14 | COVID-19 impact on overall market |
| 15 | COVID-19 impact on Production of components |
| 16 | COVID-19 impact on Point of sale |
| 17 | Market Segmentation, Dynamics and Forecast by Geography, 2024-2030 |
| 18 | Market Segmentation, Dynamics and Forecast by Product Type, 2024-2030 |
| 19 | Market Segmentation, Dynamics and Forecast by Application, 2024-2030 |
| 20 | Market Segmentation, Dynamics and Forecast by End use, 2024-2030 |
| 21 | Product installation rate by OEM, 2023 |
| 22 | Incline/Decline in Average B-2-B selling price in past 5 years |
| 23 | Competition from substitute products |
| 24 | Gross margin and average profitability of suppliers |
| 25 | New product development in past 12 months |
| 26 | M&A in past 12 months |
| 27 | Growth strategy of leading players |
| 28 | Market share of vendors, 2023 |
| 29 | Company Profiles |
| 30 | Unmet needs and opportunity for new suppliers |
| 31 | Conclusion |
| 32 | Appendix |
© 2017-2025 Mobility Foresights Pvt Ltd. All rights reserved.