HYPERPC AMPERE X ULTRA workstation: 4x RTX 6000 Blackwell for computing and neural networks

Client task

The client required a local computing node to train neural network models and work with large datasets. The main problem with existing solutions was the limited amount of video memory and overheating under prolonged loads.
  • Scope of activity: Machine Learning (ML) and Data Science.
  • Software used: Python library stack (PyTorch, TensorFlow), NVIDIA CUDA.

Key requirement: The possibility of parallel operation of four flagship GPUs in a single circuit and the availability of RAM with a capacity of 2 TB or more for processing data in RAM.

Configuration

  • CPU:
    AMD Ryzen Threadripper PRO 7995WX (96 cores, 192 threads).
  • Graphics cards:
    4 x NVIDIA RTX PRO 6000 Blackwell Server Edition (96GB VRAM per card).
  • Motherboard:
    ASUS PRO WS WRX90E-SAGE SE.
  • RAM:
    2048GB (8x256GB) Samsung ECC DDR5 4800MHz.
  • Drives:
    4 x 4TB Samsung 9100 PRO (read speed up to 14.8 GB/s).
  • Case:
    CORSAIR 9000D RGB AIRFLOW White.
  • Cooling:
    Individual air cooler circuit, 18 Thermalright TL-B12-EXTREM fans.

Selection process and decision

When designing the system, the main emphasis was placed on balancing throughput and efficient heat dissipation.

  • Platform: Processor selected Threadripper PRO 7995WX based on the WRX90 chipset. 96 cores allow you to effectively parallelize data preprocessing tasks before feeding them to the GPU.
  • Graphics cards: Installation of four RTX 6000 Blackwell required the use of a specialized motherboard with a sufficient number of PCIe 5.0 lanes operating in x16/x16/x16/x16 mode.
  • Cooling: Standard air cooling for four server cards in one case is ineffective due to the dense packaging. We implemented a custom liquid cooling system covering the CPU and all GPUs. This made it possible to maintain operating temperatures within 55–60°C under full load.
  • Power: The peak power consumption of the system exceeds 2 kW. Power supply installed 3000W, providing the necessary margin on 12V lines and Platinum certification to reduce heat loss.

Result

The designed system allowed the customer to abandon the rental of cloud capacity in favor of local computing. The station operates stably 24/7, providing a total of 384 GB of video memory for the most resource-intensive tasks.

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