Accelerator topology
Consider device count, interconnect, memory capacity, precision, and supported software as one compute topology.
Accelerate work that thrives on parallel compute.
GPU servers combine high-density acceleration with the host resources and data paths needed to sustain demanding parallel workloads.
From compact multi-GPU nodes to dense rack platforms, the design must keep accelerators supplied with data without creating avoidable thermal or network bottlenecks.
Consider device count, interconnect, memory capacity, precision, and supported software as one compute topology.
Match CPU, system memory, local storage, and network bandwidth to the rate at which the workload consumes data.
Translate rack density and operating duty into practical power, airflow, and facility requirements.
Tell us about the models, render jobs, datasets, and software stack you expect to run. We can translate them into a practical accelerator topology.
Discuss GPU infrastructure