It is undeniable that Artificial Intelligence (AI) technology and adoption will transform many industries, from healthcare to finance. When successfully integrated into complex IT operations, AI can revolutionize the way businesses operate by helping to make better and faster decisions through advanced automation. 

Data centers play a critical role in supporting these high-powered computing tasks as AI requirements become more common in today’s digital age. In this article, we will discuss how data centers can effectively support AI workloads and ensure the optimal operating environment.

1. High Density Racks

Data centers need to provide highly scalable IT infrastructure to support AI workloads that will require significantly higher power (>10kW per Rack) compared to conventional IT workload (<6kW per Rack). This is driven by more powerful chips, high-end GPUs (Graphics Processing Units) and High-Performance Computing (HPC) that consume higher power. Data Center will need to secure reliable Power from their utility providers and be equipped with high density breakers to support the high power AI racks. Lastly, it is also important for Data Center providers to have discussion with their customers regarding their design and expected IT Load requirements to account for periods of peak power demand.

2. Advanced Cooling

Higher power required by AI workload in a Data Center will result in higher temperature of the servers which in turn necessitate advanced cooling technology to prevent overheating. One of the technologies that is being explored for AI deployment is immersion-cooling whereby the electrical components of the device are immersed in a coolant. As liquid is more effective as a heat conductor than air, this kind of cooling system can reduce power consumption and environmental footprints. However, it is still early stages of adoption for this system due to the risk of voiding OEM warranties and downtime from cooling system leaks. Overall, Data Center should consider their cooling infrastructure to ensure that it can support higher specifications required for AI workload.

3. Regulatory Compliance

In general, AI workloads often involve processing and storing sensitive data, making security a top priority. Data centers should have stringent security protocols, including encryption, access control, and monitoring, to protect data and AI models from cyber threats. Compliance with data privacy regulations is also important, and data centers should adhere to industry-specific standards and certifications. 

More about our data center compliance here.

4. Environmental Considerations

Finally, it is important to address the environmental impact of data centers supporting high AI workloads. As a responsible enterprise, Data center operators should aim to minimize carbon footprint especially with greater usage of power and resources to support AI deployments. Sustainable data center practices, including energy-efficient cooling, renewable energy sources, and responsible waste disposal, can help minimize the carbon footprint of AI operations. Lastly, utilizing AI technology itself such as machine learning and automation can provide real-time monitoring that precisely identifies energy inefficiencies, reducing wasted power and improving overall operational performance.

Conclusion

In conclusion, optimized data centers play a crucial role in supporting complex AI workloads, involving scalable infrastructure, high-performance computing, advanced cooling, regulatory compliance, and environmental considerations. Addressing these aspects will ensure seamless integration of AI across diverse sectors while minimizing the carbon footprint of their operations. Reach out to EDGE DC for dependable data center solutions tailored to support your AI-driven business expansion in Indonesia