South Korean cloud infrastructure firm Innogrid has successfully deployed a GPU-based AI and Big Data analytics environment for the Korea SMEs and Startups Agency, marking a significant milestone in the domestic transition toward integrated AI infrastructure. The project, which utilizes Innogrid’s proprietary private cloud platform “Openstackit” and cloud management platform “TabCloudit,” signals a departure from traditional, siloed IT structures toward a unified, high-performance computing model.
The core of the initiative involved migrating the SME Big Data Platform (SIMS) from a rigid, on-premises, physical PC-centric architecture to a flexible cloud-based resource system. By integrating the agency’s existing virtualization assets with high-performance GPUs, Innogrid has established a framework that allows the Korea SMEs and Startups Agency to handle complex tasks, such as policy impact analysis and forecasting simulations, with greater efficiency.
A key innovation in this deployment is the virtualization of GPU resources. Unlike traditional setups where hardware is locked to specific physical machines, Innogrid’s solution allows GPUs to be allocated at the virtual machine (VM) level. This configuration enables administrators to distribute computing power dynamically based on the scale and requirements of specific analytical tasks. Users can leverage development VMs equipped with multiple GPUs for intensive processing, while the system’s integrated monitoring tools provide real-time visibility into resource status. Features such as snapshots, replication, and dynamic scaling further enhance the flexibility and utilization of these resources, allowing for predictive management of future expansion needs.
From a strategic standpoint, this project addresses a growing shift in the global AI infrastructure market. As organizations increasingly prioritize the efficient utilization of secured GPU resources over mere hardware acquisition, Innogrid’s approach focuses on bridging the gap between legacy IT infrastructure and modern AI workloads. By operating virtualization and AI computing environments within a single management framework, the company aims to reduce the complexities and operational redundancies that often accompany the integration of new AI technologies.
Innogrid’s broader vision, termed “From xPU to AI Platform,” seeks to centralize the control of diverse processing units—including GPUs, neural processing units (NPUs), central processing units (CPUs), and quantum processing units (QPUs)—under a single control plane. This strategy is designed to support the full lifecycle of AI, from initial development and training to deployment and operations.
The significance of this deployment extends to the broader public sector, particularly as institutions navigate the complexities of replacing foreign virtualization software. The project confirms that South Korean-made virtualization software, which meets rigorous National Intelligence Service security standards, can successfully serve as the bedrock for high-performance AI environments. For public and policy research institutions, this serves as a viable reference model for modernizing aging infrastructure while simultaneously establishing the capabilities required for the AI era.
“Virtualization transition and GPU adoption must be addressed within a single framework, not as separate tasks, to efficiently scale AI infrastructure,” said Kim Myung-jin, CEO of Innogrid. “We are moving beyond simply replacing foreign products toward a model where existing infrastructure is modernized to support AI and high-performance computing seamlessly.”
As concerns regarding the rising license costs of foreign virtualization platforms and global supply chain uncertainties persist, Innogrid’s strategy offers a compelling alternative for organizations seeking to modernize their digital foundations. By enabling customers to layer AI infrastructure onto their existing systems—rather than undergoing costly and disruptive “rip-and-replace” transitions—Innogrid is positioning its domestic cloud platform as a primary driver for the public sector’s digital transformation. Looking ahead, the company intends to use this success as a springboard to support a diverse range of customers in incrementally expanding their multi-cloud and hybrid cloud AI capabilities.
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