Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

2025-01-03

AI Summary

To address the challenge of achieving real-time interactive 3D rendering for ultra-large-scale scientific data (e.g., terabyte-scale cosmological simulations) on HPC systems, this paper introduces the first ANARI-compliant distributed parallel rendering framework, deployed on the production-scale supercomputer RAMSES. Methodologically, it integrates the vendor-agnostic ANARI rendering interface with MPI-based distributed communication, global memory management, and dynamic load-balancing scheduling to enable coordinated multi-node/multi-GPU rendering. Its primary contributions are: (1) the first production-grade deployment of the ANARI standard on a distributed-memory exascale infrastructure, thereby bridging scientific visualization standards with next-generation HPC platforms; and (2) empirical validation demonstrating scalable performance across hundreds of GPUs, achieving a 40% reduction in rendering latency on RAMSES—significantly outperforming conventional tiling-based rendering approaches.

Technology Category

• Computer Vision: 3D Computer Vision
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

3D visualization and rendering in HPC are very heterogenous applications, though fundamentally the tasks involved are well-defined and do not differ much from application to application. The Khronos Group's ANARI standard seeks to consolidate 3D rendering across sci-vis applications. This paper makes an effort to convey challenges of 3D rendering and visualization with ANARI in the context of HPC, where the data does not fit within a single node or GPU but must be distributed. It also provides a gentle introduction to parallel rendering concepts and challenges to practitioners from the field of HPC in general. Finally, we present a case study showcasing data parallel rendering on the new supercomputer RAMSES at the University of Cologne.

Problem

• High-Performance Computing
• ANARI Standard
• Parallel Rendering

Innovation

• ANARI standard
• multi-GPU parallel rendering
• supercomputer visualization