Power Generation and Transmission, Liquid Cooling, and Modular Datacenters Take Center Stage
In high-performance computing (HPC), three critical infrastructure technologies— AI factories, liquid cooling, and modular datacenters—are reshaping how organizations design and scale their IT systems. As digital transformation accelerates, AI takes a central role in business strategy, and high-density processing becomes the norm, these technologies have emerged as essential pre-requisites and are forming the new “InfraTech” area.
The AI Imperative
Organizations across industries are embracing AI to drive innovation, improve decision-making, and unlock new revenue streams. This AI imperative demands computing infrastructures that can process data-intensive workloads at unprecedented speeds and scale. However, this shift also brings significant challenges.
AI Factories: The Next Evolution in Datacenters
The concept of the “AI factory” represents a bold step forward in datacenter evolution. Unlike traditional facilities, AI factories are purpose-built to handle the unique demands of AI workloads. This includes optimized system architectures that include servers, interconnects, storage, and software that are designed for AI training, inferencing, and fine-tuning models.
The driving force behind these systems is the GPUs that accelerate the compute-intensive parts of the workload, the interconnects that “glue” the system together, and the fast storage that accelerates data management. Today, NVIDIA’s GPU, interconnect, and software technologies represent the de-facto standard for AI systems. In fact, “AI factory” is a term that was coined by NVIDIA, harkening back to the “information factory” designation of decades ago that were too early for the times.
Power Hungry, Power Density
In general, high-end systems are also high-density, and while that means higher performance and, usually, better efficiency, it also means higher power-density.
The rise of GPU-dense systems designed for AI workloads has driven power demands from 10 or 20 kW per rack just a decade ago to 100-150 kW per rack today, and moving to 500 kW per rack or even 1 MW per rack in the not too distant future.
This explains the rapid move by datacenters and public cloud providers to invest heavily in sources of electricity anywhere they can find it. Reviving an old nuclear reactor? Yes. Pursuing small modular reactors? Definitely. Building datacenters right next to a hydroelectric dam? Why not. Provisioning for electricity in mass quantities is the first and the mandatory step. Datacenters used to be measured by square feet or square meters, but they are now described by their wattage.
Power Transmission
Managing power transmission is another difficult task. First, there is the need for efficient transmission of power with minimal loss during transmission and the many conversions that occur as power moves to the data center, within the data center, and then within each rack, all the way to the CPUs and GPUs. Additionally, building power lines from the source to the datacenter adds layers of cost and complexity from securing rights of way to construction and maintenance.
Liquid Cooling: The Key to Efficiency and Density
AI systems require more electricity, generate more heat, and exceed the capabilities of traditional cooling methods, and datacenters must be prepared for them.
As power densities soar, cooling has become a critical factor in ensuring system reliability and efficiency. Traditional air-cooling methods are lower cost and easier to implement but they struggle to manage the heat generated by modern, high-performance hardware. And they certainly cannot handle a datacenter full of high-density AI racks.
Enter liquid cooling, a technology that enables more effective heat transfer and thermal management and unlocks new possibilities for component density. While it comes at a higher cost and with operational complexity, it can reduce overall costs, extend the life of systems, and provide better protection for the environment.
Liquids can absorb and move more heat than air since air is so low density. For comparison, the thermal conductivity of Air is 0.026 W/m·K while that of Water (a very good conductor of heat) is 0.6089 W/m·K, about 23 times better.
Liquid cooling works by transferring heat away from components via liquid, either via conduits that run past metal plates that touch hot components, or by immersing the circuitry directly in non-conductive (dielectric) cooling fluid, and circulating the fluid.
This not only reduces power consumption for cooling but also simplifies the reuse of heat energy, contributing to eco-friendly practices.
The benefits are clear:
- Enhanced energy efficiency: Liquid cooling systems consume less power than traditional methods.
- Sustainability alignment: Heat can be captured and reused, supporting broader green initiatives.
- Maximized performance per square foot: Denser component packaging means more computational power in the same footprint.
Modular Datacenters: Agile Solutions for Growing Demands
A quick way to address power and cooling requirements is the use of modular datacenters (MDCs). As long as there is power, these prefabricated, scalable systems allow organizations to deploy infrastructure quickly and meet the requirements of AI workloads. Whether supporting AI training clusters, fixed-edge computing, or research applications, modular datacenters offer flexibility and rapid deployment without the long lead times of traditional builds or facility upgrades.
By integrating modular designs, companies can scale capacity in weeks rather than months while ensuring consistent performance and cost predictability. Moreover, MDCs are purpose-built with energy efficiency as a core principle, offering organizations a tangible way to reduce their environmental footprint while optimizing operations—an increasingly vital advantage for those committed to achieving ambitious sustainability goals.
Meeting the Challenges of the Future
As computing power demands grow, organizations must prioritize efficiency, scalability, and sustainability. Modular datacenters, liquid cooling, and AI factories address these challenges head-on, offering solutions that reduce operational costs, minimize environmental impact, and ensure peak performance.
For those looking to embrace these solutions, SourceCode provides the Atlas AI Cluster, an integrated solution featuring technology from Eviden and VDURA designed to bring up AI factories with optimal cost and performance.
The company also specializes in co-designing and delivering customized, rack-scale solutions tailored to unique challenges, including modular datacenters for space-constrained or rapidly expanding environments that must enforce consistency across geographies and over time.
About SourceCode
As a vendor-agnostic partner, SourceCode provides the flexibility to select the best components for optimal performance. Our streamlined co-design process enhances efficiency, saving both time and cost. Additionally, SourceCode’s in-house, U.S.-based environmental testing lab ensures that your hardware meets top-quality standards and achieves the necessary certifications, providing unmatched reliability for your most critical systems.
