Yotta Challenges Hyperscalers with India’s First AI-Centric GPU Cloud
The global datacentre market is projected to reach $325.90 billion in 2023, with an annual growth rate of 6.12%, pushing the market volume to $438.70 billion by 2028. The United States is expected to lead with 5,375 datacentres, clocking a revenue of $95.58 billion in 2023. Meanwhile, the Indian datacentre market, with 151 datacentres currently, is forecasted to experience a surge in business from $6.12 billion in 2023 to $10.89 billion by 2028, showing an impressive 12.22% CAGR. Generative AI is poised to revolutionise the datacentre sector and is projected to create a demand wave comparable to the cloud. India aims to capitalise on this opportunity and strengthen its datacentre capacity. As part of this initiative, several leading datacentres, including Yotta, a Mumbai-based datacentre giant, anticipate acquiring NVIDIA GPUs and expanding their infrastructure accordingly. While Yotta currently has about 700 GPUs, in an exclusive interview with AIM, managing director Sunil Gupta revealed they are slated to launch their Yantra and Shakti Clouds in early 2024. Yantra will be a hyperscale cloud targeting government, enterprise, and startup sectors. Shakti Clouds is slated to be India’s first AI-centric GPU-based cloud, consisting of 16,384 NVIDIA GPUs. “It will be a mixed bag of H100s and the recently launched L40S. I would say that about 1,000 of the 1,600 ordered are L40S; however, the majority are H100s,” Gupta detailed the GPU specifications. The roadmap includes an ambitious plan to operationalise 4096 GPUs by January 2024, expanding to a staggering 16,384 GPUs by June 2024. Furthermore, Gupta explained that Yotta is poised to elevate its GPU infrastructure to an unprecedented scale of 32,768 by the end of 2025. “I’ve been told by NVIDIA themselves that for the capacity that we’re building, Yotta might become one of the ten largest supercomputers in the world,” Gupta remarked. As India looks to bolster its capacity from 800 megawatts to a staggering 3,000 megawatts by 2030, Gupta’s vision encapsulates building raw datacentres and establishing India’s sovereign AI and cloud infrastructure. He articulated, “Capacity building is crucial, but equally important is constructing our own AI and cloud ecosystem for the country’s benefit.” “There’s a lot of support and encouragement from the government because this is something which we feel India needs—because India will need its own LLM and a model on Indian data.” Infrastructure Overhaul The surge in Generative AI presents significant challenges in adapting datacentres for AI applications, not just from the infrastructural aspect but also from the software end. Gupta highlighted the challenges, noting the estimated seven to eight times increase in power and cooling density required for GPU integration: “The underlying infrastructure required to support these GPUs is just crazy… instead of some 678 kilowatts per array, you’re talking about 40 to 60 kilowatts per rack.” He outlined plans for improvements in cooling infrastructure, aiming to reduce PUE(Power usage effectiveness) with technologies like immersion cooling and direct liquid cooling to reduce PUE further to sub 1.1.” A comprehensive software layer is also being developed to streamline GPU access for startups, providing an orchestration layer akin to regular cloud services. This involves a user-friendly interface for startups to subscribe to plans, access pre-trained models, integrate their data, and create them seamlessly. “So, the startups come, create the accounts, subscribe to some plans, subscribe to some capacity, get the capacity, I give them the tools, you know, the pre-trained models, they can take those trained models, put their data, and then make their model,” said Gupta. Distinctiveness From Hyperscalers Gupta discussed the unique aspects of Shakti Cloud compared to providers like AWS, Google Cloud, and Azure, noting the scarcity of GPUs and how hyperscalers are turning to companies like theirs due to allocation trends. He expressed ambitions to rival top cloud operators, promising to provide services others might not attempt, starting with the latest H100 Tensor Core GPUs for their AI cloud. “I will be as good as Amazon, Azure, Google… while being a sovereign cloud operator,” Gupta said, outlining his ambition regionally, including other unexplored markets. Additionally, he highlighted a unique marketplace with foundational models for startups to leverage: “I’m building my AI cloud,  beginning directly with H100 GPUs… including all those foundational models.” Furthermore, Gupta emphasised Shakti Cloud’s distinctive multi-cloud architecture, enabling seamless management of various cloud resources. “By default, we are doing something that you come to my orchestration layer to register, you not only can see the catalogue of and consume my cloud services, but you can also see the catalogue of and consume AWS or Azure services as well right from my orchestration.” Demand and Expansion Plans When it comes to hyperscalers’ interest in India, Gupta highlighted their move into emerging markets not just for cost-effectiveness but to serve India’s growing economy better. He explained that these companies initially prefer partnering with providers like Yotta to navigate regulations and construction challenges but hinted at future infrastructure plans as they mature in the market. While the primary usage of Yotta’s GPUs previously was for graphics workstations by studios, mainly for tools like Maya, VFX effects, and online game creation—Gupta pointed out the diverse stakeholders in need of GPU capacities now include entities like ONGC and FTS, amongst other startups, enterprises etc. However, this infrastructure is not solely for India; Gupta’s expansive vision encompasses serving underserved markets in Southeast Asia, the Middle East, Africa, and beyond, leveraging the potential demand for GPU cloud services globally. “My fundamental thought was to go to underserved markets, where demand exceeds the local supply in the local market,” Gupta said, highlighting specific regions targeted for expansion, including Southeast Asian countries like Thailand, Philippines, Vietnam, Indonesia, and Malaysia. Moreover, their GPU cloud services attract global interest, indicating potential demand from unexpected markets like the UK.
The roadmap includes 4k GPU cluster, scaling up to 16,384 GPUs by June 2024. The intent is to reach an unprecedented 32,768 GPUs by late 2025.
The roadmap includes 4k GPU cluster, scaling up to 16,384 GPUs by June 2024. The intent is to reach an unprecedented 32,768 GPUs by late 2025.
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["AI", "ML", "generative AI", "Aim", "Ray", "RAG", "AWS", "Azure", "R", "Go"]
Shyam is a tech journalist with expertise in policy and politics, and exhibits a fervent interest in scrutinising the convergence of AI and analytics in society. In his leisure time, he indulges in anime binges and mountain hikes.