Trending
DCD Podcast – What data centers should expect from the next UK Prime Minister Karis eyes potential data center development outside Chicago, Illinois AI-Native Leaders: The Organizational Playbook for Engineering Transformation at Scale Centuria Capital Group raises AU$300m in equity for ResetData AI cloud business Hybrid quantum supercomputer Roquo installed at Japan’s Riken PLDT files to establish and float data center REIT in Philippines Digital Realty plans 600MW campus in Kansas, acquires investment firm Columbia Capital MGX could purchase APAC data center operator DayOne – report Running ComfyUI workflows on Amazon SageMaker AI processing jobs Microsoft plans 2GW data center campus in Pecos, Texas The $400 million machine powering the future of chipmaking The multi-modal advantage for quantum computing Gigawatt-scale data center campus proposed in Kansas Mitigating vendor lock-in with Sakana AI Fugu multi-agent models Building pay-per-intelligence for AI agents: How Ampersend uses Amazon Bedrock AgentCore Payments

Sponsored: Rethinking data center cooling for AI: The rise of direct-to-chip liquid cooling

As AI and high-performance computing continue to drive ever-higher levels of processing power, conventional data center cooling methods must advance accordingly. Data centers need to innovate in order to handle the massive heat produced by ever-more-powerful GPUs and CPUs. One of the most promising solutions is direct-to-chip liquid cooling, which efficiently removes heat from AI workloads, improves sustainability, and boosts overall performance.

Why traditional cooling methods are no longer sufficient for high-performance computing (HPC) infrastructure. Modern air-cooling systems are finding it increasingly difficult to manage the intense heat produced by today’s AI workloads. As GPU heat density continues to rise, air cooling is approaching its practical limits.

Even at elevated fan speeds, air’s limited thermal capacity prevents efficient heat dissipation, resulting in hotspots, thermal throttling, and heightened risk of component failure in AI and HPC systems. Moreover, air cooling consumes substantial electricity because fans must run continuously to handle the increasing heat generated by GPUs.

Data centers currently account for around 2% of global electricity usage, a proportion projected to rise with increasing AI deployment. A new strategy is required to cool HPC infrastructure. Why liquid cooling is essential for AI data centers.

Liquid cooling is a vital solution that is up to 3,000 times more effective than air cooling, allowing for greater compute density while lowering energy consumption.

 

Join the conversation

Your email address will not be published. Required fields are marked *