You have special order items in your shopping cart, please note that item descriptions with “*” denotes a “Special Order Item” which cannot be returned for refund, nor cancelled once ordered.
If your organisation is pushing the boundaries in AI, research, or high-performance computing (HPC), you know not every workload fits the public cloud. Sometimes, your data is too sensitive, too large, or just needs to be processed now—without waiting for uploads, downloads, or unpredictable costs.
On-premises GPU servers can unlock real speed and savings for teams working on AI training, scientific simulations, complex analytics, or 3D rendering. And if you need to comply with local data privacy laws or keep things running close to home in Australia, New Zealand, or the Pacific Islands, building locally makes even more sense.
Cloud vs On-Prem: What’s Right for You?
Think of on-prem as owning your office, and cloud as renting by the hour.
Cloud is brilliant for bursty, unpredictable workloads, or when you’re getting started and want zero upfront cost.
On-premises shines when you want full control, predictable costs, and the ability to customise everything—especially for consistent or long-term heavy usage.
Key Differences (At a Glance):
Decision Factor
On-Premises GPU
Cloud GPU
Cost Model
One-off investment, no recurring rental; better ROI if you’re always busy.
Pay-as-you-go; costs add up fast for ongoing or big workloads.
Performance
Dedicated, always-on, ultra-low latency.
Dependent on network; some overhead and traffic delays.
Scalability
Limited by physical space and budget.
Virtually unlimited—spin up what you need, when you need it.
Data Security
100% under your control, local and compliant.
Relies on provider security and offshore data laws.
Customisation
Total flexibility: pick hardware, OS, software, cooling.
Predefined, limited by the cloud provider’s catalog.
Ongoing Management
Your IT, your rules—more work, more control.
Outsourced; easy, but less say in when and how.
Energy Efficiency
Optimise for your site, use green energy, run jobs off-peak.
No direct control; you pay for what’s used.
Don’t Have a Data Centre? No Problem.
You don’t need a massive facility to run world-class workloads on-site. At DiGiCOR, we’ve deployed powerful GPU servers everywhere from small labs and branch offices to university closets and regional data rooms. The trick is in planning:
Power: Multi-GPU servers need real power—think dedicated 20A+ circuits, not standard office outlets.
Space: Whether it’s a server rack, a closet, or a custom cabinet, ensure there’s enough airflow and access.
Cooling: Heat is the enemy. Make sure you have AC, ventilation, or, if needed, DiGiCOR’s liquid-cooled systems for ultra-dense deployments.
Noise: These are not office desktops—plan for sound insulation if servers are near people.
Safety: Use surge protection, quality cabling, and don’t overload circuits.
With the right approach, even small sites can enjoy enterprise-grade performance.
What Hardware Should You Choose?
This is where DiGiCOR’s local expertise pays off:
Form Factor: From compact towers to dense rackmounts, we help you fit world-class performance into your real-world environment.
GPUs: Get what your workload needs—anything from power-efficient cards for analytics to the latest NVIDIA H100/H200s or AMD MI-series for deep learning and simulation.
CPU, Memory, Storage: Balance is everything. We help you avoid bottlenecks and future-proof your investment.
Networking: Scale from one server to a cluster with 10GbE, 40GbE, or 100GbE—whatever your data needs.
Redundancy & Support: Minimise downtime and keep working, with the backing of DiGiCOR’s engineering team across ANZPI.
Power & Cooling: Often Overlooked, Always Critical
Don’t skimp here. The best hardware in the world is useless if it’s starved for electricity or gets too hot:
Use PDUs and UPS for safe distribution and backup.
Ventilate the room or add smart cooling—DiGiCOR’s experts can help you size and install everything you need.
Answers to Common Questions
Can I run GPU servers in a small room? Yes, with good planning! DiGiCOR helps you make it work safely and efficiently—even in non-traditional IT spaces.
What power setup do I need? Ideally, a dedicated 208–240V circuit with the right amperage. Don’t just “plug and pray”—talk to us or your electrician.
Can I just use regular wall sockets? Not for multi-GPU systems. It’s risky and will almost always trip breakers or worse.
How do I choose the right GPU? Let us profile your workloads. We’ll recommend a mix that maximises performance and minimises waste.
Do I need to manage everything myself? No. DiGiCOR can pre-configure management tools and provide ongoing support. Treat your on-prem setup like your own private cloud—with us on call.
Ready to Take Action? Build the GPU System That Fits Your Needs
As the trusted local leader in HPC, AI, and enterprise IT, DiGiCOR supports you from design through delivery and beyond. We build, configure, and support GPU servers to fit your needs—whether it’s a single box for a researcher or a multi-node cluster for enterprise-scale AI. Our team is based in Australia and New Zealand, with reach into the Pacific Islands and a legacy of building reliable, high-performance systems since 1997.
Ready to bring the power back in-house? Talk to DiGiCOR. We’ll help you build smarter, run faster, and stay in control.
