HPC-Accelerated Simulation
High-performance computing turns fusion simulations that would take months on a workstation into results available in hours.
Why fusion is compute-heavy
Fusion couples plasma physics, electromagnetics, neutron transport, heat transfer, and structural mechanics, each across a wide range of scales. Resolving them faithfully requires large meshes, many time steps, and many particles. A single high-fidelity run can be enormous, and design work needs many runs.
How HPC helps
- Domain decomposition splits a large problem across many processors.
- GPU acceleration speeds the dense numerical kernels.
- Ensemble runs explore uncertainty and parameter space in parallel.
- Fast storage and networks keep the processors fed with data.
Strong and weak scaling
Two scaling questions matter. Strong scaling asks whether a fixed problem finishes faster on more processors; weak scaling asks whether a bigger problem stays affordable as you add processors. Well-built codes are measured against both, because a code that does not scale wastes the hardware.
Applied to Kronos
HPC runs the neutron transport, plasma, and multiphysics models behind the Hyperion breeder and the tandem-mirror burner. It also generates the training data for the surrogates that make real-time and optimization work possible.
Efficiency as a goal
Faster runs mean more of the configuration space examined and more uncertainty quantified within the same time. Computational efficiency is therefore not a convenience; it directly sets how much of the design can be understood.
Reproducibility
Large runs are pinned to specific code versions, inputs, and environments so their results can be reproduced later, part of the reproducibility discipline.