Why high-performance GPUs are critical for IndiaAI Mission

This infrastructure will be critical for startups, researchers, and academia to test and deploy large language models (LLMs) and other AI solutions.
Why high-performance GPUs are critical for IndiaAI Mission
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NEW DELHI: In 2024, the government approved an investment of over Rs 10,300 crore for the IndiaAI Mission, a five-year initiative to develop India’s artificial intelligence (AI) ecosystem in the country. A major component of this mission is the establishment of a cutting-edge AI computing infrastructure, which will include the deployment of over 10,000 Graphics Processing Units (GPUs) through collaborations between the public and private sectors. Of the total mission budget, Rs 5,000 crore has been specifically earmarked for this initiative.

This infrastructure will be critical for startups, researchers, and academia to test and deploy large language models (LLMs) and other AI solutions.

What Is a GPU?

A Graphics Processing Unit (GPU) is a specialised processor designed to accelerate tasks related to graphics, such as image and video rendering. Much like Neural Processing Units (NPUs), GPUs excel at parallel processing, allowing them to handle multiple tasks simultaneously and perform trillions of operations per second.

Originally, GPUs were mainly used for gaming, video editing, and rendering 3D graphics. However, due to their immense processing power, GPUs have become essential for more complex tasks, such as large-scale data processing and cryptocurrency mining.

Today, GPUs are also indispensable for training large neural networks. For example, leading tech companies use Nvidia’s H-100 GPUs to train large language models (LLMs).

How are GPUs used?

Twenty years ago, GPUs were primarily used to accelerate 3D graphics in applications like video games. As computing needs grew, however, scientists and engineers realised that GPUs could solve far more complex problems. This insight sparked the rise of the “general-purpose GPU” era. Today’s GPUs are far more versatile and programmable, enabling them to tackle a wide range of applications well beyond graphics rendering. They are now used in fields such as artificial intelligence, scientific research, large-scale data analysis, and even cryptocurrency mining.

The status of India’s GPU infrastructure

Several major companies, including Yotta (backed by Hiranandani), Tata Communications, Jio, CtrlS, and E2E Networks, recently presented their proposals to the Ministry of Electronics and Information Technology to help build AI computing infrastructure under the IndiaAI Mission. These companies are competing for a portion of the Rs 10,000 crore allocated to provide GPUs and cloud services to startups, academic institutions, and researchers.

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