42 GPU dies across 5 nodes with InfiniBand 40 Gbps fabric and CUDA-aware MPI.
KYAMOS provides cloud-accessible GPU computing infrastructure for high-performance multiphysics simulations, AI-assisted modelling, and engineering optimization workflows. The cluster supports scalable numerical solvers, neural surrogate model training, and fast batch inference for research and industrial applications.
The telemetry below provides a live operational view of the KYAMOS self-hosted GPU cluster. It is used to monitor resource availability, GPU utilization, memory allocation, and node status for active simulation and AI workloads.
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3 nodes × 6 GPUs = 18 V100 GPUs. 16/32 GB HBM2 per GPU. Primary workhorse for deep learning training and CFD simulation.
2 nodes × 6 cards × 2 dies = 24 GPU dies. 12 GB GDDR5 per die. Used for batch processing and inference.
40 Gbps interconnect enabling low-latency GPU-to-GPU communication across nodes.
Direct GPU memory transfers between nodes without staging through CPU memory. Near-linear scaling for multi-GPU simulations.