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Choose NVIDIA Tesla M40 or K80 accelerators for deep learning and batch compute, NVIDIA Quadro M2000 or M4000 cards for professional 3D workstations, or an AMD Radeon Pro WX 9100 for high-compute graphics work. Every configuration below pairs dual Xeon E5-2697 v4 processors with 256GB of RAM and 2TB of SSD storage, and the inventory updates in real time.
Choose the dedicated server which is right for your business.
Dublin sits strategically within the Greater Columbus Technology Corridor one of the fastest-growing data center markets in the United States.
Rather than just offering standard infrastructure, our Dublin facility leverages Ohio’s unique geographic and networking advantages for high-compute workloads:
Dublin is positioned directly on the major transcontinental terrestrial fiber routes connecting Chicago (350 E. Cermak) to East Coast hubs like Ashburn, VA (Data Center Alley) and New York. This guarantees ultra-low latency routing without the congestion of coastal networks.
Central Ohio is home to massive infrastructure investments from AWS, Google, and Meta. Hosting your dedicated GPUs in Dublin places your workloads in the exact same low-latency region, making it perfect for hybrid-cloud architectures and multi-cloud data exchanges.
GPU rendering and AI training require massive, stable power. Ohio’s highly regulated, highly redundant industrial power grid ensures that your multi-GPU clusters run 24/7 without the power instability or premium costs often found in coastal data centers.
Each Dublin configuration includes a 1Gbps unmetered port, so training datasets, model checkpoints, and render assets move without overage charges. If your pipeline needs more throughput, the sales team can advise on higher-speed options.
Tesla-class GPUs such as the M40 (12GB) and K80 (24GB) handle model training, batch inference, and experimentation in TensorFlow, PyTorch, and other CUDA-based environments. Match your framework and CUDA versions to the GPU generation before deployment, since Maxwell- and Kepler-era cards run best on the toolchains built for them.
Quadro M2000 and M4000 cards, along with the Radeon Pro WX 9100, shorten render and viewport turnaround for Blender, Maya, and Cinema 4D projects. Moving a render queue to a dedicated server frees local workstations, and 256GB of RAM leaves room for heavy scene files and simulation caches.
Two Intel Xeon E5-2697 v4 processors supply 36 cores and 72 threads for parallel ETL jobs, feature engineering, and analytical queries. GPU acceleration takes over where a workload maps well to CUDA. The 256GB of RAM keeps working sets in memory, and 2TB of SSD storage holds the datasets themselves.
