Understanding the buzz around GPUs in 2023 ?
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The server market for the near future is going to be all about GPUs, GPUs, and more GPUs. The Graphic Processing Unit (GPU) Market size was valued at USD 25.41 Billion in 2020 and is projected to reach USD 246.51 Billion by 2028, growing at a CAGR of 32.82% from 2021 to 2028.
According to the latest research report by ZMR (Zion Market Research),“According to the latest research study, the demand of global GPU As A Service Market size & share in terms of revenue was valued at USD 2.31 billion in 2022 and it is expected to surpass around USD 28.7 billion mark by 2030, growing at a compound annual growth rate (CAGR) of approximately 28.78% during the forecast period 2023 to 2030.”
The key market players are listed in the report with their sales, revenues and strategies are DigitalOcean, Amazon Web Services (AWS), Oracle Cloud, Microsoft Azure, OVHcloud, Google Cloud, Qarnot Computing, IBM Cloud, Packet, INVIDIA Cloud, Vultr, Scaleway, Igneous, HPE GreenLake, Paperspace, NetApp, Alibaba Cloud, Hetzner, Rescale, Linode, and others.
This is the reason we see a lot of buzz around the GPUs and the GPU manufacturers and vendors.
But as a layman, do we have an idea, what is GPU, how does it work, what the the different GPU components etc.
What is GPU?
A Graphics Processing Unit (GPU) is an electronic device or circuit designed primarily for rendering and processing video and image data on a computer screen. GPUs are also known as Visual Processing Units (VPUs) because they excel at handling visual data. They are optimized for parallel processing, allowing them to perform multiple tasks simultaneously, making them exceptionally fast at handling mathematical and graphical workloads. GPUs are instrumental in providing 2D and 3D graphics in computer games and various other visual applications. In recent years, GPUs have become a critical component in fields such as Artificial Intelligence (AI), machine learning, scientific research, and simulations, as they significantly reduce the time required to solve complex mathematical problems.
