SK Telecom Launches GPUaaS with New Gasan AI Data Center in Seoul By CIOTechOutlook Team

SK Telecom Launches GPUaaS with New Gasan AI Data Center in Seoul

CIOTechOutlook Team | Monday, 13 January 2025, 07:08 IST

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SK Telecom announced the introduction of its latest AI cloud service, SK Telecom GPUaaS (Graphics Processing Unit as a Service). To introduce the new service, a new data center has been established in Seoul, known as the Gasan AI Data Center (AIDC), which was officially inaugurated on December 30 of the previous year. This important advancement represents a crucial move in SK Telecom's plan to build a strong AI infrastructure throughout South Korea.

The Gasan AIDC is built to create an enhanced setting for high-density GPU server activities, featuring a power density of 44kW per rack. This facility is fundamental to SK Telecom's strategy for the AI Infrastructure Super Highway, which seeks to establish a nationwide network comprising AI data centers, GPUaaS, and edge AI solutions.

Working with the American firm Lambda, SK Telecom's GPUaaS offering utilizes the NVIDIA GPU H100, which is among the top-performing GPUs accessible in Korea. This service enables corporate clients to choose the quantity of GPUs and the time period of their use based on their unique AI service requirements. The adaptable pricing structure depends on the contract duration, the quantity of GPUs, and the billing approach, making it an appealing choice for companies with different AI workloads.

The GPUaaS service provides options for short-term usage, ranging from one to two months, and includes tailored package setups featuring dedicated servers, firewalls, and dedicated connections. Moreover, the service can be connected with public clouds, allowing customers to utilize SK Telecom's GPU computing capabilities while preserving their current cloud services.

An SK Telecom official highlighted the flexibility and security of the service, stating, "Customers can use their own GPUs for stable AI learning and inference, and security can be enhanced by utilizing firewalls and dedicated lines. Even if customers' AI workloads increase rapidly, they can add GPUs to dedicated servers, reducing the burden of additional facility investments."


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