Graphic Processing Unit Market is Anticipated to Witness High Growth Owing to Rising Demand for Enhanced Graphics Capabilities
Graphic Processing Unit Market |
The Graphic Processing Unit (GPU) market comprises graphics cards that are proficient of handling computer graphics, as well as their applications. As GPUs have vastly more transistors than general-purpose CPUs, they are extremely efficient for workloads with a lot of parallel computation and higher memory access. GPUs have become essential for 3D games, visualization and graphic designing tools, and scientific and engineering applications which require high-performance capabilities for graphic-intensive operations.
The global
GPU market is estimated to be valued at US$ 47.77 Bn in 2024 and is expected to
exhibit a CAGR of 18% over the forecast period 2024 to 2031.
Key Takeaways
Key players operating in the Graphic Processing Unit market are Salesforce.com,
Inc., LogicBay Corporation, Oracle Corporation, Allbound Inc., International
Business Machines Corp, Impartner Software, ZINFI Technologies, Inc., Zyme
Solutions, PartnerPath, Blackhawk Engagement Solutions, Inc., The Planet Group,
Allbound Inc., and Channeltivity, LLC. These players are mainly focused on
offering innovative graphics solutions and expanding their global footprint
through partnerships and collaborations.
Key opportunities in the Graphic
Processing Unit Market Growth include growing adoption of AI and
machine learning models, development of autonomous vehicles, and increasing
applications of augmented & virtual reality technologies. The GPU market
players are also focusing on global expansion to tap the growth opportunities
in developing countries of Asia Pacific, Middle East & Africa, and South
America.
Market Drivers and Restraints
Market Drivers: Rising demand for enhanced graphics capabilities from gaming
& esports industries is a key driver for the GPU market. Increasing
utilization of 3D graphics in various industrial and scientific applications is
also fueling the demand. Growing artificial intelligence workloads for deep
learning and neural networks require powerful GPU accelerators for faster
computation.
Market Restraints: High investment costs associated with GPU solutions pose a
major challenge, specifically for small enterprises. Complex programming and
development involved also acts as a restraint. Thermal management issues linked
with high-performance GPU processors can hamper their adoption in certain
applications. Dependence on semiconductor industry cycles remains a major
macroeconomic restraint for stable long-term growth.
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