Papers for

supercomputing visualization teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

In situ HPC data streams directly into Unreal Engine for visualization

Bridging In-Situ Visualization to Game Engines: From ParaView Catalyst via ANARI to Unreal Engine

Abstract: In-situ high-performance computing (HPC) simulations produce massive datasets that remain difficult to stream into game engines for interactive visualization. We present an in-situ, disk-free pipeline that couples simulation data to Unreal Engine 5 through ParaView's ANARI rendering API. A modified ANARI-USD device captures Universal Scene Description (USD) scene graphs in memory at the ANARI layer and streams the engine-agnostic USD format through an embedded ZeroMQ broker to visualization clients, where JuSync, middleware with a companion Unreal Engine 5 plugin, parses the geometry as it arrives and routes it to engine rendering components at runtime, producing scenes that are camera-navigable once received. The decoupled design keeps simulation execution independent of visualization load, and clients may connect or disconnect at any time. The pipeline is demonstrated on the JURECA-DC supercomputer at Forschungszentrum Jülich, streaming Free Electron Laser (FEL) simulation data with point clouds of tens of millions of particles.

Mon 19 OctDistributed, Parallel, and Cluster Computing
The gist
High-performance computer simulations create huge amounts of data that are hard to visualize in real time using game engines. The authors developed a way to send simulation data directly, without saving it to disk, into Unreal Engine 5 for interactive viewing. They convert simulation outputs into a common scene format and use a messaging system so the engine can show up-to-date scenes as the simulation runs. This system lets users navigate the simulation visuals smoothly while not slowing down the computation. They demonstrated this approach with simulations involving tens of millions of particles on a supercomputer.
Open → 2610.26247v1