AI Workloads Are Changing What a Data Centre Needs
AI is changing what businesses expect from computing infrastructure. Training and fine-tuning AI models, running complex simulations, or designing chips can require powerful GPU servers that consume significantly more power than conventional IT systems.
The International Energy Agency (IEA) notes that AI is accelerating the deployment of high-performance servers and increasing power demand in data centres.
For businesses investing in these workloads, the question isn’t just “Which GPU server should we buy?”
It’s also: “Can our data centre support it?”
A conventional server room may not have the power, cooling, connectivity or infrastructure required to run high-density GPU systems reliably.
5 Workloads That Need High-Performance Infrastructure
The need for high-density infrastructure starts with the workload. AI and other compute-intensive applications can quickly push conventional server environments beyond their limits.
- AI and Machine Learning
AI teams may need powerful GPU infrastructure to train, fine-tune and deploy AI models. As models and datasets grow, these workloads can require multiple GPUs, increasing power, cooling and networking demands.
2. High-Performance Computing
HPC supports complex simulations, research computing, and large-scale analytics. These applications often require substantial computing resources and reliable infrastructure for sustained workloads.
3. EDA and Chip Design
Electronic Design Automation (EDA) workloads support design verification, simulation and synthesis. These compute-intensive processes make dedicated high-performance infrastructure important for semiconductor development teams.
4. Semiconductor Development
Malaysia’s growing semiconductor ecosystem may increase demand for secure, reliable environments for compute-heavy workloads. Beyond processing power, businesses need strong security, connectivity, uptime and scalability.
5. Rendering and Visualisation
3D rendering, VFX and engineering visualisation can place heavy demands on GPUs. High-density compute can support these workloads without requiring businesses to build their own specialised facility.
Why AI and HPC Workloads Need More Than a Standard Rack
These workloads have one thing in common: they demand more from the infrastructure supporting them.
AI and GPU servers can consume substantially more power than conventional servers. More power also means more heat, making cooling capacity critical.
Uptime Institute reports that rack power densities are increasing as compute-intensive workloads such as AI become more common, with more operators reporting peak rack densities of 30kW or higher.
This means businesses can’t simply place powerful GPUs into an existing rack and assume the infrastructure will cope.
The power, cooling, connectivity and facility itself need to be ready for the workload.
4 Infrastructure Requirements to Consider
High-Density Power
GPU-heavy workloads can require substantial power capacity per rack. Limited power availability can restrict deployment or require costly infrastructure upgrades.
Effective Cooling
The more power servers consume, the more heat they generate. Proper cooling is essential for stable performance during sustained workloads.
Reliable Connectivity
AI, HPC and EDA workloads can involve large datasets and frequent transfers. Reliable, high-speed connectivity is important when infrastructure communicates with cloud, storage or other systems.
Scalability
Workloads can grow quickly. A flexible environment lets businesses expand from a single rack to a larger deployment without building an entirely new facility.
Why Colocate Instead of Building Your Own AI Facility?
Building a specialised environment means taking responsibility for power, cooling, connectivity, physical security, monitoring and maintenance.
For businesses that already own or plan to purchase GPU and HPC servers, colocation provides specialised infrastructure without requiring them to build the data centre around it.
Instead, businesses place their servers in an environment designed to support high-density workloads.
Purpose-Built for AI, HPC and EDA
Exabytes HPC & AI Servers Colocation is hosted at the Exabytes T3 Data Centre in Malaysia and is designed for demanding compute workloads.
The facility supports up to 50kW per rack, with redundant power, cooling and network infrastructure and 99.9% network uptime.
It supports workloads including:
- AI model training and fine-tuning
- HPC simulations and research computing
- EDA design verification and simulation
- Semiconductor development
- 3D rendering and engineering visualisation
Businesses can scale from a single rack to a private cage, depending on their requirements.
Why Malaysia-Based AI Infrastructure Matters
For Malaysian businesses, keeping infrastructure closer to operations can offer practical advantages.
Exabytes’ T3 Data Centre is located in Penang, providing Malaysia-based infrastructure and low-latency connectivity for Malaysian and Southeast Asian workloads.
Our facility also provides direct access to DE-CIX Malaysia, supporting high-speed connectivity for AI, HPC and cloud workloads.
Exabytes manages the data-centre environment, allowing businesses to focus on their compute workloads.
AI Server Infrastructure and Colocation Explained
High-density GPU infrastructure can support demanding workloads such as AI model training and fine-tuning, HPC simulations, EDA, semiconductor development, 3D rendering, and engineering visualisation. These workloads require substantial computing power, making sufficient rack power, cooling, connectivity and scalability essential for reliable deployment.
Why AI Servers Need More Power and Cooling
AI servers often use multiple high-performance GPUs that consume significantly more power than conventional servers. Higher power consumption also generates more heat, increasing cooling requirements. A data centre designed for high-density workloads can provide the specialised power and cooling capacity needed to keep demanding GPU infrastructure running reliably.
Understanding AI Server Colocation
AI server colocation allows businesses to deploy their GPU or AI servers in a specialised data centre rather than building and maintaining their own facility. The colocation provider supplies essential infrastructure, including power, cooling, connectivity and physical security, while businesses retain control of their dedicated computing hardware.
Power Requirements for High-Density AI Server Racks
Power requirements depend on the GPU and server configuration. High-density AI deployments can require significantly more power than conventional server racks. Exabytes’ HPC and AI colocation environment supports up to 50kW per rack, providing the capacity needed for demanding GPU, AI and high-performance computing workloads.
Why Choose Malaysia for AI and HPC Server Colocation?
Malaysia-based colocation provides local infrastructure and low-latency connectivity for Malaysian and Southeast Asian workloads. For instance, Exabytes’ Penang T3 Data Centre also provides access to DE-CIX Malaysia, supports up to 50kW per rack and offers 24/7 local expert support for AI, HPC and EDA workloads.
Conclusion: Is Your Infrastructure Ready for Your AI Ambitions?
AI infrastructure isn’t simply about buying more powerful GPUs.
Whether you’re training AI models, running HPC simulations, developing semiconductors, or performing EDA and rendering workloads, the infrastructure supporting those servers matters just as much.
If your environment cannot provide enough power, remove heat effectively, deliver reliable connectivity or scale with your workloads, your computing investment may be limited by the facilities around it.
With Exabytes HPC & AI Server Colocation, businesses can deploy high-density compute at a Malaysia-based T3 data centre, with up to 50kW per rack, redundant infrastructure, low-latency connectivity and 24/7 local expert support.
Your GPUs power the workload. Exabytes powers the infrastructure behind your AI workloads.
