Graphics Processing Unit (GPU) Market Size, Share, Growth, and Industry Analysis, By Type (Integrated, Discrete, and Workstation GPUs), By Application (Gaming, Automotive, AI, Data Science, and Technology), and Regional Forecast to 2034

GRAPHICS PROCESSING UNIT (GPU) MARKET OVERVIEW

The global Graphics Processing Unit (GPU) market size was USD 25.2 billion in 2025 and is projected to touch USD 65.21 billion by 2034, exhibiting a CAGR of 12.62% during the forecast period.

A Graphics Processing Unit (GPU) is a specialised digital circuit designed within the maximum vital to enhance the rendering of images and video for display on computing devices. Unlike Central Processing Units (CPUs), which may be built for preferred-reason duties, GPUs are notably parallelised processors optimised for responsibilities regarding large information devices and mathematical computations, especially those associated with statistical analysis. Modern GPUs are able to perform billions of floating-point operations consistent with second, making them essential not only in gaming and substantial programs but also in scientific research, artificial intelligence (AI), machine learning knowledge of (ML), economic modelling, and deep learning. Originally advanced to control pc images and image processing, the capability of GPUs has advanced through the years to assist greater complex workloads, particularly as needs for immoderate-basic performance computing (HPC) have grown. The middle form of a GPU includes hundreds of smaller cores that deal with duties simultaneously, thus making it tremendous for parallel processing duties. This structure differs from that of a CPU, which usually has a small number of cores optimised for serial processing. GPUs are to be had in included and discrete formats—incorporated GPUs are a part of the tool memory and are embedded interior CPUs, normally visible in cellular devices and laptops, at the same time as discrete GPUs come as standalone gambling playing cards with devoted memory and processing capabilities, generally used in pc systems and servers. With the arrival of cloud computing and virtualisation, GPUs in the meantime are also available as virtual instances, allowing corporations to leverage GPU power without making an investment in physical infrastructure.

GLOBAL CRISES IMPACTING THE GRAPHICS PROCESSING UNIT (GPU) MARKETCOVID-19 IMPACT

Demand for GPUs witnessed an surge due to several pandemic-induced behavioral shifts

The global COVID-19 pandemic has been unprecedented and staggering, with the market experiencing higher-than-anticipated demand across all regions compared to pre-pandemic levels. The sudden market growth reflected by the rise in CAGR is attributable to the market’s growth and demand returning to pre-pandemic levels.

The coronavirus chaos led to a pandemic that had a multifaceted effect on the Graphics Processing Unit (GPU) marketplace, triggering great disruptions and amazing possibilities. Initially, the worldwide deliver chain faced huge interruptions due to production facility shutdowns, labour shortages, and logistics constraints in key manufacturing hubs together including China, Taiwan, and South Korea—countries that form the spine of semiconductor production. However, at the same time as the delivery facet ended up constricted, demand for GPUs witnessed a sudden surge due to numerous pandemic-driven behavioural shifts. The transition to a long way flung artwork, digital gaining knowledge of, and extended consumption of digital leisure notably boosted the call for for laptops, computer structures, gaming consoles, and data centre capabilities—all of which depend carefully on GPU era. Esports sports sports activities, and excessive-normal regular overall performance gaming obtained traction at some point of lockdowns, raising the call for advanced GPUs capable of supporting immersive critiques. Simultaneously, the rise in cryptocurrency mining in the near future of the pandemic, although unspecified, exacerbated the demand-supply imbalance as miners snapped up high-performance GPUs in bulk. Enterprise segments additionally expert superior GPU capabilities as organisations extended their adoption of cloud computing and AI-pushed programs to cope with operationally stressful situations and data analytics needs introduced by of way of the catastrophe. These dynamics led GPU producers like NVIDIA and AMD to experience strong revenue growth, even amid constraints. However, the extended nature of the pandemic exposed vulnerabilities in the semiconductor supply chain and raised geopolitical issues, prompting calls for additional resilient manufacturing facilities and localised production.

LATEST TREND

Integration of AI-centric architecture through the development of tensor cores

One of the most transformative and ongoing developments within the GPU market is the integration of AI-centric structures into subsequent-generation graphics processors, especially through the development and deployment of tensor cores, neural engines, and dedicated AI acceleration modules. As artificial intelligence and devices get to know workloads that turn out to be increasingly more complex and large, conventional GPU architectures are being reimagined to address AI inference and education greater effectively than ever in advance than. This fashion is high-quality exemplified via NVIDIA’s Ampere and Hopper architectures, which embed specialised AI cores to boost matrix math operations applicable to deep learning. These upgrades significantly improve throughput, reduce latency, and enhance the overall performance of AI models running on GPUs. Similarly, AMD and Intel have delivered AI-extra abilities into their GPU roadmaps to guide workloads in element computing, self systems, and data analytics. The synergy between AI and GPUs isn't always limited to investigation labs or hyperscale information facilities—it's rapidly permeating into consumer electronics, smartphones, gaming consoles, or even domestic automation systems. AI-centric GPUs now require manual skills together with real-time facial recognition, adaptive photograph rendering, automated video upscaling, and realistic workload control. Moreover, cloud employer carriers are providing GPU-as-a-Service with protected AI frameworks, permitting small and medium-sized institutions (SMEs) to get admission to scalable, excessive-preferred standard performance AI talents without huge capital funding. This democratisation of AI through GPU upgrades is reshaping innovation cycles for the duration of industries which encompass healthcare, vehicle, finance, and cybersecurity.

GRAPHICS PROCESSING UNIT (GPU) MARKET SEGMENTATION

BY TYPE

Based on Type, the global market can be categorized into Integrated, Discrete, and Workstation GPUs.

• Integrated: Integrated GPUs are embedded right away into the same chip because of the fact that the Central Processing Unit (CPU) and GPU are generally found in charge range computer systems, laptops, tablets, and cellular gadgets. These GPUs percent tool reminiscent of the CPU and provide strength-efficient picture processing suitable for everyday obligations, alongside video playback, internet browsing, and primary gaming. While they lack the overall performance of standalone GPUs, they may be first-class for light-weight computing eventualities, thin-and-slight laptops, and devices where space and power consumption are critical. Leading examples encompass Intel’s UHD and Iris Xe graphics and AMD’s Radeon Vega covered GPUs.
• Discrete: Discrete GPUs, instead, are standalone devices with committed memory and processing cores, offering considerably better graphical and computational performance overall. These are commonly used in gaming pc structures, widely fashionable modern standard performance laptops, and professional environments that require expanded rendering or parallel processing. Discrete GPUs dominate the client gaming and immoderate-surrender seen computing segments, with marketplace leaders like NVIDIA’s GeForce RTX and AMD’s Radeon RX collection setting trendy overall performance benchmarks. They guide real-time ray tracing, better body prices, and complicated three-D rendering, making them vital for immersive gaming, 3-D layout, or even cryptocurrency mining.
• Workstation GPUs: Workstation GPUs represent a specialised elegance optimised for professional programs which encompass laptop-aided design (CAD), digital content material cloth advent, scientific visualisation, simulation, and AI model training. These GPUs are engineered for stability, prolonged driving force manual, and compatibility with professional software program software utility software program suites. They are commonly positioned in commercial enterprise corporation-grade workstations and servers used by engineers, researchers, and animators. NVIDIA’s Quadro and RTX A-series, similarly to AMD’s Radeon Pro collection, are prominent in this phase. Workstation GPUs provide capabilities like ECC memory, better floating-factor precision, and massive frame buffers, which might be vital for undertaking important responsibilities.

BY APPLICATION

Based on application, the global market can be categorized into Gaming, Automotive, AI, Data Science, and Technology.

• Gaming: Gaming remains the most crucial and mature software segment, accounting for a notable part of GPU earnings globally. Gamers require more and more powerful GPUs to address superior rendering strategies, real-time ray tracing, high-resolution indicates, and frame-rate optimisation. The growth of competitive e-sports sports sports, virtual reality (VR), and streaming systems like Twitch and YouTube Gaming has, in addition, advanced GPU call for among both expert and casual gamers. Technologies which include NVIDIA’s DLSS (Deep Learning Super Sampling) and AMD’s FidelityFX are examples of GPU upgrades particularly targeted at the gaming market.

• Automotive: Automotive is a growing application area in which GPUs have come to be essential for allowing advanced purpose strain-help systems (ADAS), independent of the usage of algorithms, in-vehicle infotainment, and virtual dashboards. These structures depend on GPU electricity for photograph reputation, LiDAR statistics processing, and sensor fusion. Companies like NVIDIA (with its DRIVE platform) and Intel’s Mobileye are spearheading GPU integration in next-generation vehicles.
• AI: AI (Artificial Intelligence) represents one of the fastest-growing utility segments. GPUs are uniquely applicable for AI version schooling and inference due to their pretty parallel shape. They strengthen deep learning, natural language processing, computer vision, and robotics across sectors consisting including healthcare, finance, protection, and retail. AI-targeted GPUs embody NVIDIA’s A100 and AMD’s Instinct series, which are probably applied in data centres, side gadgets, and AI development labs.
• Data Science: Data Science is a different software program area in which GPUs play a pivotal function, permitting complicated data evaluation, statistical modelling, and real-time visualisation. GPU-accelerated computing dramatically reduces processing time for big datasets, making it essential in genomics, weather forecasting, financial modelling, and virtual twins. Popular frameworks like RAPIDS, TensorFlow, and PyTorch leverage GPU abilities to boost average performance.
• Technology: The Technology segment encompasses the big use of GPUs in cloud computing, virtualisation, corporate IT infrastructure, and software application improvement. GPU-as-a-Service (GPUaaS) systems supplied by using the use of AWS, Google Cloud, and Microsoft Azure cater to developers, startups, and institutions trying scalable, on-call for GPU get right of entry to for several responsibilities.

MARKET DYNAMICS

Market dynamics include driving and restraining factors, opportunities and challenges stating the market conditions.

DRIVING FACTORS

Rising demand with the explosive and sustained growth of the global gaming industry

One of the most dominant driving forces behind the Graphics Processing Unit (GPU) market growth is the explosive and sustained boom of the global gaming commercial enterprise company, which has gone through a massive evolution from informal gaming proper right into a multi-billion-dollar, high-fidelity, immersive environment. As modern video games turn out to be more and more graphically complicated—incorporating features like physics simulations, real-time ray tracing, and 4K to 8K resolutions—name for effective GPUs capable of rendering such rich content cloth fabric fabric in real-time has surged. Gamers, specifically the ones involved in competitive and e-sports activities environments, are searching for low-latency, high-frame-rate reports, which can be achieved through top-tier GPU basic standard performance. Consequently, customers are willing to make investments closely in top-tier GPUs to optimise their gaming rigs. This name is amplified with the beneficial aid of common product launches and advertising and marketing and marketing and marketing campaigns from GPU producers, which include NVIDIA’s GeForce RTX collection or AMD’s Radeon RX lineup, which emphasise gaming-unique competencies, collectively with DLSS (Deep Learning Super Sampling), FreeSync/G-Sync compatibility, and VR readiness. Moreover, the proliferation of online gaming systems and streaming offerings like Twitch and YouTube Gaming has created an environment wherein GPUs are important not only for gaming video games but also for content creation, streaming, and broadcasting, thus widening the scope of use. The rise of virtual reality (VR) and augmented reality (AR) gaming evaluations is a one-of-a-kind vector reinforcing the centrality of GPUs, as these technologies require notable processing strength to supply immersive, interactive environments.

Market growth with the proliferation of AI and ML

Another massive and increasingly more influential pressure on the GPU marketplace is the proliferation of artificial intelligence (AI), tool getting to know (ML), and data centre packages that require high computational capabilities. Unlike conventional workloads that CPUs can address, AI and ML algorithms require large parallel processing and matrix manipulation abilities, which are probably the middle strengths of GPU architectures. Training deep neural networks, as an example, includes processing petabytes of information and project tens of loads of billions of matrix multiplications—a task that could be prohibitively time-consuming with CPUs by itself. As a give up end result, GPUs have become the hardware spine of AI studies, powering the whole lot from natural language processing (NLP) models like ChatGPT to autonomous systems and fraud detection algorithms in finance. Large-scale cloud agencies together with Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) have cautiously invested in GPU-based totally completely without a doubt infrastructure to guide excessive-ordinary performance computing (HPC) and AI-as-a-Service offerings, permitting organisations of all sizes to train and installation AI models at scale. Beyond cloud, on-premise records centres are also embracing GPU acceleration to boost productivity in sectors like genomics, weather modelling, oil exploration, and digital twin simulations. Moreover, agencies which embody Tesla use GPUs for training self-the usage of vehicle algorithms, at the same time as pharmaceutical organisations rely on GPU-improved simulations for drug discovery and molecular modelling. AI frameworks, collectively with TensorFlow, PyTorch, and MXNet, are optimised for GPU usage, further cementing their relevance in modern-day computing. The growing need for real-time analytics, aspect AI, and federated learning has brought about extended adoption of GPUs in cellular gadgets, corporate IoT gateways, and embedded systems.

RESTRAINING FACTOR

Persistent volatility and bottlenecks in supply chain resulted in unpredictable availability

A large restraining factor for the Graphics Processing Unit (GPU) market is the persistent volatility and bottlenecks within the international semiconductor delivery chain, which have led to unpredictable availability, elevated production prices, and prolonged lead times. The production of GPUs is cautiously dependent on superior semiconductor fabrication strategies that require particularly specialised tools, expert hard work, and get right of get entry to uncommon materials, which include silicon wafers and rare earth elements. Most of this excessive-give-up production is centred in a handful of nations—which include Taiwan, South Korea, and the us—developing a slender manufacturing funnel that is highly prone to geopolitical tensions, natural disasters, or health crises. The COVID-19 pandemic magnified the one vulnerability, with lockdowns and tough artwork shortages extensively curbing semiconductor output. Even though the agency tried to get higher, similarly geopolitical frictions, especially between China and the U.S., in the facet of trade context, created uncertainty concerning technology exports and access to foundries. Compounding the problem is the surge in demand from multiple immoderate-growth sectors like electric vehicles, 5G infrastructure, and cloud computing, which all compete for the same fabrication capacities. The shortage of substrates, packaging materials, or probable devices like lithography machines has had a cascading effect on the production of GPUs.

OPPORTUNITY

Scope of growth with its expanding role within the rapidly evolving edge computing

A promising possibility for the GPU market lies in its growing characteristics in the abruptly evolving factor computing and Internet of Things (IoT) panorama. As the need for real-time information processing grows in sectors alongside self-driving automobiles, business automation, smart cities, and far-off healthcare, traditional centralised cloud-based architectures are often insufficient due to latency and bandwidth constraints. This creates an urgent demand for effective, compact, and strength-inexperienced processing devices that can deliver the information deliver—properly at the threshold. GPUs, historically perceived as components for computer structures and data centres, in the interim are being miniaturised and tailor-made for deployment in edge environments. Companies like NVIDIA with its Jetson collection, and AMD with embedded Radeon processors, are already capitalising in this fashion via a manner of way of supplying GPUs tailor-made for aspect AI and real-time analytics. These issue GPUs are increasingly incorporated into robotics systems, drones, surveillance cameras, and scientific devices to perform duties which embody image popularity, speech processing, and predictive upkeep without relying on non-save you cloud connectivity. Moreover, the deployment of 5G networks complements the viability of these side use cases through providing the high-tempo connectivity needed to aid GPU-powered devices at some stage in allocated environments. This convergence of GPUs with edge and IoT opens new verticals in retail, agriculture, strength, and transportation, in which on-tool intelligence is vital. As AI applications proliferate and additional IoT endpoints are associated, the decision for detailed AI accelerators like GPUs will rise dramatically, growing a large market, even though during a largely untapped market. With similar enhancements in thermal normal performance, electricity optimisation, and AI version compatibility, GPUs are properly-positioned to become the processing heart of issue-based intelligence, supplying the GPU commercial enterprise organisation a significant growth avenue beyond its traditional strongholds in gaming and data centres.

CHALLENGE

Issue of power consumption and thermal management results in elevated heat output

One of the maximum urgent traumatic conditions dealing with the GPU marketplace in recent times is the problem of power consumption and thermal manipulate, in particular as GPUs become increasingly powerful and are tasked with dealing with particularly complex computational workloads. High-basic overall performance GPUs, especially those used in gaming rigs, AI model education, and statistics centre environments, require a large amount of electrical power, regularly exceeding several hundred watts steady with unit. This surge in power name for outcomes in extended warm temperature output, necessitating extremely cutting-edge and steeply priced cooling systems to keep operational balance and save your hardware from degradation. The mission is mainly acute in data facilities, wherein masses of GPUs are deployed in dense configurations, multiplying the thermal load and power footprint. Effective cooling solutions which incorporate liquid cooling, specialised airflow designs, and superior warm temperature sinks power up the rate of infrastructure and strength intake, hence affecting well-known running expenditure. Furthermore, cellular and embedded gadgets that use GPUs face stricter constraints in electricity budgets, limiting the general popular standard performance thresholds that GPUs can benefit from without draining battery life or overheating. These thermal troubles moreover limit the portability and integration of GPUs in smaller form-factor devices, hindering market penetration in certain software utility regions.

GRAPHICS PROCESSING UNIT (GPU) MARKET REGIONAL INSIGHTS

• NORTH AMERICA

North America, mainly the United States Graphics Processing Unit (GPU) market, represents one of the most influential regions within the international Graphics Processing Unit (GPU) market, in desired due to its characteristics as a technological powerhouse and its function due to the reality the headquarters to several key GPU business enterprise leaders, which include NVIDIA, AMD, and Intel. The U.S. is a worldwide hub for immoderate-average performance computing, advanced semiconductor design, AI research, and gaming innovation, all of which are probably cautiously reliant on GPU technology. The area is blessed with a strong ecosystem of Research and Development institutions, number one universities, and generation groups that continuously push the envelope of GPU skills. The wonderful use of GPUs across industries—from gaming and enjoyment to car, protection, aerospace, and healthcare—has made the U.S. an early and fast adopter of advanced GPU solutions. North America’s gaming enterprise, especially its console and PC gaming segments, has fueled a huge GPU demand. E-sports leagues, online streaming systems, and VR-based in-reality entertainment stories have further contributed to the recent boom in GPU intake. Moreover, North America is likewise home to some of the largest hyperscale cloud issuer carriers, which include Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, all of which extensively use GPUs in their AI, ML, and deep learning services. This large deployment has not handiest boosted the income of mainstream common performance GPUs but also fostered improvements in GPU-as-a-Service (GPUaaS) organisation models. Furthermore, the American Department of Defence and National Laboratories actively put money into GPU-extended computing for country-wide safety, simulation modelling, and weather era programs. The u . S . A .’s dedication to keeping semiconductor independence and decreasing reliance on Asian foundries has furthermore introduced approximately duties, such as the CHIPS and Science Act, which is driving domestic GPU and chip manufacturing. Additionally, U.S. Startups and AI-targeted companies are developing proprietary GPU-based completely totally in truth structures tailor-made for facet computing and vertical-precise packages, ensuring that innovation is not simply centralised but also numerous across sectors. Despite supply chain disruptions and regulatory troubles regarding exports of excessive-stop GPU technology, the U.S. continues to dominate in terms of innovation, adoption, and production fee. Its integration of GPUs into purchaser tech, organisation solutions, and national infrastructure cements its management within the worldwide marketplace.

• EUROPE

European Graphics Processing Unit (GPU) market share represents a frequently developing and strategically crucial region inside the global GPU marketplace, characterised via way of a strong emphasis on virtual sovereignty, high-performance general-purpose overall performance computing (HPC), and sustainable energy integration. While it lacks vital standalone GPU producers similar to the United States or countries in Asia, Europe is domestic to several critical stakeholders and customers that substantially contribute to GPU demand, specifically in fields at the side as medical studies, vehicle innovation, healthcare, and company automation. Countries which include Germany, France, the UK, and the Netherlands are the most critical adopters of the GPU era in Europe. Germany, with its advanced automobile quarter, leverages GPUs for simulation, self-sufficient use of algorithms, and automobile infotainment structures. Leading car businesses like BMW, Volkswagen, and Daimler rent GPU-powered systems for real-time information processing, pc imaginative and prescient, and motive force-help structures. Similarly, within the UK and France, the finance, healthcare, and AI research sectors extensively undertake GPUs for record analytics, scientific imaging, and drug discovery strategies. Europe's developing willpower in artificial intelligence and quantum computing is likewise a key trouble in growing the GPU market. The European Commission has launched projects alongside the European Processor Initiative (EPI) and EuroHPC JU (Joint Undertaking), which promote homegrown immoderate-usual overall performance computing skills, a lot of which are probably GPU-primarily based totally surely. These packages aim to lessen dependence on foreign chipmakers and enhance Europe’s technological autonomy. Additionally, the location’s popularity in green computing aligns nicely with the development of next-generation GPUs that provide better overall performance in keeping with watt ratios, helping both ecological desires and company-wide average performance mandates. Moreover, Europe's data privacy rules and AI ethics frameworks have endorsed the development of localised GPU-stepped forward answers tailor-made to conform with the General Data Protection Regulation (GDPR) and other prison requirements, especially in sectors like healthcare and finance. Cloud provider businesses like OVHcloud and Deutsche Telekom are also integrating GPU-powered offerings into their offerings to compete with American hyperscalers.

• ASIA

Asia-Pacific is the dominant region within the international Graphics Processing Unit (GPU) marketplace, because of its vital characteristics in every production and consumption of GPU-based technology. The region’s dominance is driven by nations alongside China, Taiwan, South Korea, and Japan, which together represent a powerful mixture of fabrication competencies, technological improvement, and great client markets. Taiwan, domestic to TSMC (Taiwan Semiconductor Manufacturing Company), is the linchpin of global GPU manufacturing, fabricating superior chips for organisations like NVIDIA, AMD, and Apple. South Korea, through company giants together with Samsung and SK Hynix, moreover contributes appreciably to the GPU environment through manufacturing memory chips and growing custom GPU solutions for cell and embedded structures. Japan, notwithstanding the fact that greater centered on specialised robotics and electronics, remains a key contributor through groups like Sony, which makes use of custom GPUs in its PlayStation consoles, and Fujitsu, which employs GPU computing for supercomputing and commercial simulations. Meanwhile, China performs a twin function as both a production hub and an increasing customer of GPU technology. Driven through the use of national strategies like “Made in China 2025” and a formidable push toward technological self-sufficiency, China is making an funding in growing domestic GPU corporations, together with Biren Technology and Moore Threads, to reduce reliance on U.S.-based companies. Chinese cloud giants like Alibaba Cloud, Tencent Cloud, and Huawei Cloud are carefully deploying GPU-powered servers for AI, records analytics, and video processing. The vicinity’s booming e-sports activities market, growing base of PC and console game enthusiasts, and growing popularity of VR/AR amusement are also developing a fertile ground for GPU names. 

KEY INDUSTRY PLAYERS

Key Industry Players Shaping the Market Through technological innovation

Key game enthusiasts inside the GPU market play a crucial role in shaping the business enterprise through technological innovation, strategic collaborations, and brilliant environment improvement. Companies like NVIDIA, AMD, and Intel are at the forefront, constantly pushing the bounds of GPU abilities to satisfy the growing wishes of gaming, AI, and excessive-normal standard overall performance computing (HPC). NVIDIA, as an example, has pioneered GPU-based total AI acceleration with its CUDA platform and Tensor Cores, transforming GPUs into effective AI engines applied in research labs, cloud data facilities, and self-driving systems. Through acquisitions like Mellanox and Arm (pending approval), NVIDIA is aiming to consolidate its function in the course of information delivery, chip format, and processing layers. AMD, within the intervening time, is focused on handing over immoderate-traditional overall performance, cost-effective GPUs through its RDNA and CDNA architectures, which cater to gaming as well as compute-intensive workloads. It furthermore plays a key role in powering gaming consoles similar to the PlayStation and Xbox, showcasing its functionality to influence mass-marketplace adoption. Intel, a reasonably new entrant within the discrete GPU vicinity, is investing intently in its Arc collection and integrating AI-intensive first-rate competencies into its Xe form to compete in every purchaser and company segment. Additionally, cloud corporations like Amazon, Google, and Microsoft integrate the GPUs into their infrastructure-as-a-service (IaaS) offerings, making GPU power accessible to startups and groups globally. Hardware OEMs, which include ASUS, MSI, and Gigabyte, contribute with the resources of the usage of customising GPU merchandise with advanced cooling, electricity shipping, and aesthetic improvements, in addition to tailoring GPUs to unique character dreams. Collectively, the ones game enthusiasts invest in Research and development, growth-supporting software program ecosystems, participate in developer outreach, and preserve international supply and help networks to ensure scalability.

LIST OF TOP PP WOVEN BAG COMPANIES

• NVIDIA Corporation (U.S.)
• Advanced Micro Devices (U.S.)
• Intel Corporation (U.S.)
• ASUSTeK Computer Inc (Taiwan)
• Gigabyte Technology Co., Ltd. (Taiwan)
• Micro-Star International Co., Ltd. (Taiwan)
• Qualcomm Technologies Inc. (U.S.)
• Samsung Electronics Co., Ltd. (South Korea)

KEY INDUSTRY DEVELOPMENT

March 2024: NVIDIA unveiled its subsequent-generation Blackwell GPU shape, a primary milestone within the evolution of the GPU era aimed in maximum times at accelerating artificial intelligence and deep learning workloads. This launch marked a large bounce in computational common popular common overall performance, with the Blackwell collection imparting exponential upgrades in floating-point throughput and energy performance in comparison to its predecessors. Designed for electricity AI fashions with trillions of parameters, Blackwell GPUs aid capabilities together with faster matrix operations, advanced multi-GPU scalability, and advanced guide for combined-precision computing. NVIDIA, moreover, added integration with its NVLink and Grace CPU platform to offer unified reminiscence get proper of get right of get entry to to to inside the course of big clusters, thereby reducing latency and optimising traditional average standard overall performance for organisation-diploma AI deployment. This release is seen as pivotal in strengthening NVIDIA’s dominance within the AI and facts centre GPU market and allowing the subsequent wave of generative AI packages, which incorporate language models, clinical simulations, and robotics.

REPORT COVERAGE

The study encompasses a comprehensive SWOT analysis and provides insights into future developments within the market. It examines various factors that contribute to the growth of the market, exploring a wide range of market categories and potential applications that may impact its trajectory in the coming years. The analysis takes into account both current trends and historical turning points, providing a holistic understanding of the market's components and identifying potential areas for growth.

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