Graphics Processing Units Statistics 2024 By Best Gaming Technology

Introduction

Graphics Processing Units Statistics: Graphics Processing Units (GPUs) have emerged as a crucial component of modern computing systems.

They play a pivotal role in various fields ranging from graphics rendering to scientific simulations and artificial intelligence.

The primary function of GPUs is to handle the massive computational requirements inherent in rendering high-resolution graphics and complex visual effects.

Originally designed to accelerate graphical computations for visual rendering. GPUs have evolved into highly parallel processors capable of handling complex mathematical computations.

This evolution has given rise to their applications in diverse domains such as gaming, machine learning, scientific research, and more.

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• The global chiplets market in 2023 was nearly USD 3.1 Billion. Over the next ten years, the chiplets industry is expected to surge at 42.5% CAGR. Concluding at a valuation of USD 107.0 Billion by 2033. It is projected to Reach USD 4.4 Billion in 2024.
• In 2022, the global GPU market was valued at 40 billion U.S. dollars, and it is projected to reach 400 billion U.S. dollars by 2032.
• With a compound annual growth rate (CAGR) of 25 percent from 2023 to 2032.
• During 2019, the primary participants in the worldwide graphics processing unit (GPU) market amassed a total revenue of 18.2 billion U.S. dollars.
• The year 1993 witnessed the entry of NVIDIA into this domain. Yet, it wasn’t until 1997 that they garnered noteworthy recognition by launching the first Graphics Processing Unit (GPU).
• Combining 3D acceleration alongside traditional 2D and video acceleration.
• The NVIDIA Titan RTX is a top-tier gaming GPU renowned for its exceptional aptitude in handling intricate deep-learning tasks. It has 4608 CUDA cores and 576 Tensor cores.
• Crafted by PNY, the NVIDIA Quadro RTX 8000 is the world’s most potent graphics card. Meticulously designed for deep learning matrix multiplications.
• Most GPUs excel at gaming on monitors with resolutions of 1440p Quad HD (QHD).
• A higher refresh rate displays and facilitates an immersive VR experience.

Graphics Processing Units Statistics by Size

• In 2022, the worldwide market for graphics processing units (GPUs) achieved a valuation of 40 billion U.S. dollars.
• Projections indicate a significant escalation to 400 billion U.S. dollars by 2032.
• Exhibiting a compound annual growth rate (CAGR) of 25 percent from 2023 to 2032.

(Source: Statista)

Graphics Processing Units Statistics by Players

• During 2019, the primary participants in the worldwide graphics processing unit (GPU) market amassed a total revenue of 18.2 billion U.S. dollars.
• Projections indicate this figure is poised to surge to 35.3 billion U.S. dollars by 2025.
• This notable growth starkly contrasts the 8.1 billion U.S. dollars in revenue generated collectively by the top three vendors in 2015.
• For the gaming sector, in June 2016, NVIDIA held a dominant market share of 56.7%. Which expanded to 63.6% by June 2017 and soared to an impressive 76.4% by July 2018.
• AMD, in contrast, held a 25.1% market share in June 2016. Which declined to 20.5% in June 2017 and decreased to 13.9% by July 2018.
• Meanwhile, Intel’s market share stood at 17.8% in June 2016, dipped to 15.5% in June 2017, and further contracted to 9.6% by July 2018.
• Other companies collectively represented a marginal market share of 0.4% in June 2016.
• Remained consistent at 0.4% in June 2017 before tapering off to 0.2% by July 2018.

(Source: Statista)

Evolution of the Graphics Processing Unit Statistics

• Before the contemporary conception of graphics cards, video display cards held prominence. IBM played a significant role in this trajectory by revealing the Monochrome Display Adapter (MDA) in 1981.
• The MDA card was designed with a distinct purpose: to display high-resolution textual content and symbols in a singular monochromatic text mode. Offering a display grid of 80 columns with 25 rows of characters.
• Harnessing this progress as a foundation, IBM continued its innovation journey by introducing the Enhanced Graphics Adapter (EGA). This inventive accomplishment brought forth the ability to present 16 concurrent colors on a screen boasting a resolution of 640 pixels by 350 pixels.
• In 1996, 3dfx Interactive introduced the Voodoo1 graphics chip, which gained initial prominence in the arcade industry and deliberately forsook 2D graphics capabilities. This avant-garde hardware initiative played a pivotal role in catalyzing the 3D revolution.

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• In just one year, the Voodoo2 emerged, heralding its arrival as one of the pioneering video cards capable of supporting parallel processing by two cards within a single personal computer.
• The year 1993 witnessed the entry of NVIDIA into this domain. Yet, it wasn’t until 1997 that they garnered noteworthy recognition by launching the first Graphics Processing Unit (GPU). Combining 3D acceleration alongside traditional 2D and video acceleration.
• The inception of the term “GPU” owes its existence to NVIDIA’s significant contributions. NVIDIA assumed a pivotal and influential role in shaping the trajectory of contemporary graphics processing, a role highlighted by the unveiling of the GeForce 256.
• NVIDIA’s definition characterized the graphics processor as a “singular chip processor that integrates functions such as lighting, triangle setup/clipping, transformation, and rendering engines, possessing the capability of processing a minimum of 10 million polygons per second.”
• The debut of the GeForce 256 represented a leap beyond the capabilities of its forerunners. The RIVA processors mark a substantial advancement in the realm of 3D gaming performance.
• NVIDIA’s drive remained robust, as evidenced by the introduction of the GeForce 8800 GTX. Which showcased an impressive texture-fill rate of 36.8 billion per second.
• 2009 ATI introduced the impactful Radeon HD 5970 dual-GPU card before its acquisition by AMD.

(Source: Codinghero.ai)

Graphics Processing Units Architecture Statistics

Memory Hierarchy of Different Graphics Processing Units Statistics

• A substantial and unified register file stands at the architecture’s core, encompassing 32,768 registers.
• This intricate architecture spans 16 Streaming Multiprocessors (SMs), each with a 128KB register file.
• With an allocation of 32 cores per SM. This configuration yields a collective 2MB spread seamlessly throughout the chip.
• Complementing this arrangement, totaling 48 warps, equating to 1,536 threads per SM, seamlessly integrates into the architecture. This is further augmented by the allocation of 21 registers per thread.
• The memory component is structured with multiple banks. Ensuring efficient memory management. An exceptionally high bandwidth capability further enhances this strategic arrangement, totaling a remarkable 8,000 GB/s.
• The architecture incorporates a versatile shared and Level 1 (L1) memory configuration.
• This configurable 64KB memory allocation can be flexibly partitioned into two distinct layouts: 16KB for shared memory and 48KB for L1 cache, 48KB for shared memory and 16KB for L1 cache.
• The memory design is marked by low latency, operating within 20 to 30 cycles.

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• In tandem with this efficiency, the architecture boasts a substantial bandwidth capacity, surpassing the threshold of 1,000 GB/s.
• An integral architecture component includes specialized memory caches dedicated to texture and constants. This arrangement entails a read-only constant cache with a capacity of 64KB.
• A 12KB texture cache is also incorporated into the architecture’s design.
• This texture cache exhibits an impressive memory throughput rate, quantified at 739.63 GB/s. Accompanying this high throughput, the cache registers a noteworthy texture cache hit rate of 94.21%.
• The principal memory repository, accessible to both the GPU and CPU, is a pivotal aspect of the architecture. Functioning cohesively, this memory interface comprises six 64-bit DRAM channels.
• This architecture accommodates up to 6GB of GDDR5 memory, facilitating substantial data handling capabilities.
• However, it’s notable that this main memory component is associated with relatively higher latency, typically between 400 and 800 cycles.
• The architecture exhibits a commendable performance potential of up to 177 GB/s in terms of throughput.

(Source: Carnegie Mellon University, Virginia Tech)

Parallels Between CPU and Graphics Processing Units Statistics

• In a comparative analysis of render times, several GPU and CPU combinations are crucial. The rendering performance of the GE Force RTX 3070 was showcased with a time of 64.72 seconds. While the Intel Core i9-12900K exhibited a contrasting render time of 233.59 seconds.
• Similarly, the Quadro RTX 8000 recorded a render time of 84.4 seconds, juxtaposed with 238.24 seconds for the AMD Ryzen 9 3950X 16-core processor.
• The Radeon RX 6900 XT demonstrated a render time of 93.98 seconds, in contrast to the render time of 270.93 seconds for the Intel Core i7-12700KF.
• For the Radeon Pro W6800, the render time was extended to 128.57 seconds. While the Intel Core i9-11900K @350GHz registered a render time of 357.74 seconds.
• Lastly, the Titan V displayed a render time of 169.92 seconds. Contrasting the render time of 365.97 seconds for the AMD Ryzen 7 5800X 8-core processor. This analysis illuminates the varying rendering capabilities of the evaluated GPU and CPU configurations.

(Source: Blender Stats)

Graphics Processing Units Statistics by Applications

Gaming Using Graphics Processing Units Statistics

• Contemporary games heavily rely on the GPU’s capabilities, often surpassing the demands placed on the CPU. The intricate tasks of processing intricate 2D and 3D graphics, rendering complex polygons, and efficiently mapping textures necessitate a potent and swift GPU. The efficiency with which your graphics/video card (GPU) processes data directly correlates with the number of frames displayed per second, resulting in smoother gameplay.
• For instance, the recommended graphics specifications for Call of Duty: Black Ops 4 include mid-range options like the NVIDIA GeForce GTX 970 4GB, GTX 1060 6GB, or Radeon R9 390/AMD RX 580.
• These GPUs are apt for 1080p gaming and can adeptly manage games at medium to high settings, even at elevated resolutions.
• “1080p” denotes the resolution of 1920 x 1080 pixels, also known as Full HD.
• Competitive players are advised to opt for even more potent options, such as the GeForce GTX 1080 or Radeon RX Vega 64 graphics cards, categorized as high-end.

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• These GPUs excel at gaming on monitors with 1440p Quad HD (QHD) resolutions or higher refresh rate displays and facilitate immersive VR experiences. However, ensuring your monitor aligns with these specifications is imperative, as investing in a higher-end graphics card wouldn’t yield the desired results without a compatible display.
• Conversely, a monitor with a maximum refresh rate of 60 Hz would fail to leverage the capabilities of a more powerful graphics card.
• Turning to World of Warcraft, the recommended GPU options include the NVIDIA GeForce GTX 960 4GB or the AMD Radeon R9 280 or superior variants.
• The GTX 960 is commendable, delivering dependable 1080p performance while maintaining power efficiency and lower temperatures.
• The AMD R9 280 boasts additional video memory, making both GPUs proficient at running demanding games at elevated settings.
• The expansive sandbox action-adventure title Grand Theft Auto V, alongside the popular battle royale phenomenon Fortnite Battle Royale, suggests an NVIDIA GeForce GTX 660 2GB or an AMD Radeon HD 7870 2GB.
• These GPUs are suitably priced and engineered to facilitate fluid 1080p gaming experiences. Catering to players seeking performance without breaking the bank.

(Source: HP)

Machine Learning and Deep Learning Using Graphics Processing Units Statistics

• The NVIDIA Titan RTX is a top-tier gaming GPU renowned for its exceptional aptitude in handling intricate deep-learning tasks. It has 4608 CUDA cores and 576 Tensor cores.
• It has a GPU memory of 24 GB GDDR6 and a Memory Bandwidth of 673GB/s.
• NVIDIA’s Tesla represents a pioneering tensor core GPU meticulously designed to accelerate an array of critical tasks encompassing artificial intelligence, high-performance computing (HPC), deep learning, and machine learning.
• Embracing the potency of the NVIDIA Volta architecture, the Tesla V100 stands as a formidable embodiment, boasting a striking 125TFLOPS of deep learning performance for both training and inference purposes.
• Its CUDA cores are 5120, while tensor cores are 640.
• Its memory bandwidth is 900 GB/s, and GPU memory is 16GB. Its clock speed is 1246 MHz.
• Crafted by PNY, the NVIDIA Quadro RTX 8000 is the world’s most potent graphics card, meticulously designed for deep learning matrix multiplications.
• Remarkably, a sole Quadro RTX 8000 card has the prowess to vividly render intricate professional models. Imbuing them with realism through precise shadows, reflections, and refractions, thereby delivering rapid insights to users.
• Engineered with the prowess of the NVIDIA TuringTM architecture and the NVIDIA RTXTM platform. The Quadro series furnishes professionals with cutting-edge hardware-accelerated features, including real-time ray tracing. Deep learning capabilities, and advanced shading techniques.
• Notably, through NVLink utilization, the memory capacity of this graphics card can be extended to an impressive 96 GB.

(Source: ProjectPro)

Graphics Processing Units Cryptocurrency Mining Statistics

• During 2021, the sales of graphics cards experienced a significant surge. This surge was not attributed to a rise in the desire for enhanced gaming graphics. Rather, the driving factor was the capacity of Graphics Processing Units (GPUs) to engage in cryptocurrency mining activities.
• Positioned at the apex of the NVIDIA RTX 30 series of graphics cards, the RTX 3090 is a pinnacle performer. Built on the foundation of the Ampere architecture, this card distinguishes itself through remarkable daily profitability efficiency.
• It grants users the capability to participate in the mining of an array of cryptocurrency coins and tokens, encompassing Swap (XWP), Ravencoin (RVN), Grin (GRIN), and others. It delivers commendable gaming performance with an ample VRAM capacity of 24GB and an imposing count of 10,500 CUDA cores.
• Introduced by AMD in 2019, the RX 5700 series of GPUs employs FinFET (fin field-effect transistor) technology. This innovative approach minimizes power consumption by reducing the number of electronic components involved.
• The AMD Radeon RX 5700 XT can engage in mining cryptocurrencies such as ETH, GRIN, RVN, ZEL, XHV, ETC, and BEAM, and its power consumption is 225 watts.
• Utilizing Nvidia’s Ampere architecture as its foundation, the RTX A5000 showcases a configuration of 8192 CUDA cores.
• It is equipped with 24GB of GDDR6 memory accompanied by a 384-bit memory interface.
• Additionally, it boasts a boost clock speed reaching 1.75 GHz while maintaining a peak power consumption of 230W.

(Source: Changelly)

Recent Developments

Acquisitions and Mergers:

• Nvidia acquires Arm Holdings: Nvidia completed its $40 billion acquisition of Arm Holdings in 2024. This strategic move aims to integrate Arm’s processor designs into Nvidia’s GPU technology, enhancing performance and energy efficiency.
• AMD acquires Xilinx: AMD finalized its $35 billion acquisition of Xilinx in late 2023. This merger aims to combine AMD’s GPUs with Xilinx’s FPGA technology to deliver advanced computing solutions for AI and data centers.

New Product Launches:

• Nvidia GeForce RTX 5090: Nvidia launched its GeForce RTX 5090 in March 2024. This GPU features improved ray tracing, AI-enhanced graphics, and a significant performance boost over its predecessor, targeting gamers and professionals.
• AMD Radeon RX 7900 XT: AMD introduced the Radeon RX 7900 XT in January 2024, offering enhanced graphics performance, lower power consumption, and support for advanced gaming technologies.

Funding:

• Intel invests $3 billion in GPU R&D: Intel announced a $3 billion investment in research and development for its GPU technologies in 2023. This funding aims to accelerate the development of Intel’s Xe graphics architecture and improve competitiveness in the GPU market.
• Graphcore secures $250 million: AI chip startup Graphcore, known for its IPU (Intelligence Processing Unit) technology, raised $250 million in 2023 to expand its GPU capabilities and market presence.

Technological Advancements:

• AI-Enhanced Graphics: Nvidia and AMD are leveraging AI to enhance graphics rendering, with features like DLSS (Deep Learning Super Sampling) in Nvidia GPUs and FidelityFX Super Resolution in AMD GPUs, providing better performance and visual quality.
• Ray Tracing Improvements: The latest GPUs from Nvidia and AMD feature advanced ray tracing capabilities, providing more realistic lighting, shadows, and reflections in gaming and professional applications.

Market Dynamics:

• GPU Market Growth: The global GPU market is projected to grow at a CAGR of 21% from 2023 to 2028. Driven by increasing demand for gaming, AI, and data centers.
• Competitive Landscape: Nvidia maintains a leading position in the GPU market, followed by AMD and Intel, with each company investing heavily in R&D to innovate and capture market share.

Regulatory and Strategic Developments:

• US Export Controls: New US export controls on advanced GPUs to China are impacting global supply chains and market dynamics, with companies adapting their strategies to comply with regulations.
• EU’s Digital Strategy: The European Union’s digital strategy includes initiatives to support GPU development and adoption, emphasizing the importance of GPUs in AI and digital transformation.

Research and Development:

• Next-Generation Architectures: Ongoing R&D efforts are focused on developing next-generation GPU architectures. Such as Nvidia’s Hopper and AMD’s RDNA 4, aimed at delivering higher performance and efficiency.
• Collaboration with Academia: Leading GPU manufacturers are collaborating with academic institutions on research projects to explore new applications and improve existing technologies, driving innovation in the field.

Conclusion

Graphics Processing Units Statistics – Significant milestones have marked the evolution of graphics processing units (GPUs).

From the early days of monochrome display adapters, GPUs have evolved into powerful components capable of intricate 2D and 3D graphics rendering, deep learning, and scientific computations. NVIDIA played a pivotal role with innovations like the GeForce 256, setting the stage for modern GPUs.

The surge in GPU sales driven by cryptocurrency mining underscored their versatility beyond gaming. The introduction of powerful GPUs like the RTX 3090.

Tesla V100 demonstrated its prowess in gaming, AI, and scientific computing. As the market grows and diversifies, GPUs remain a cornerstone of technological advancement in various industries.

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