paper-with-me

홈 › Papers

Radiant Foam Rendering on a Graph Processor

2026-01-07 · Zulkhuu Tuya, Ignacio Alzugaray, Nicholas Fry, Andrew J. Davison arxiv

Many emerging many-core accelerators replace a single large device memory with hundreds to thousands of lightweight cores, each owning only a small local SRAM and exchanging data via explicit on-chip communication. This organization offers high aggregate bandwidth, but it breaks a key assumption behind many volumetric rendering techniques: that rays can randomly access a large, unified scene representation. Rendering efficiently on such hardware therefore requires distributing both data and computation, keeping ray traversal mostly local, and structuring communication into predictable routes. We present a fully in-SRAM, distributed renderer for the Radiant Foam Voronoi-cell volumetric representation on the Graphcore Mk2 IPU(Intelligence Processing Unit), a many-core accelerator with tile-local SRAM and explicit inter-tile communication. Our system shards the scene across tiles and forwards rays between shards through a hierarchical routing overlay, enabling ray marching entirely from on-chip SRAM with predictable communication. On Mip-NeRF~360 scenes, the system attains near-interactive throughput of approximately 1 fps at 640x480 with image and depth map quality close to the original GPU-based Radiant Foam implementation, while keeping all scene data and ray state in on-chip SRAM. Beyond demonstrating feasibility, we analyze routing, memory, and scheduling bottlenecks that inform how future distributed-memory accelerators can better support irregular, data-movement-heavy rendering workloads.

📄 PDF Abstract BibTeX arXiv:2601.04382

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

SDFoam: Signed-Distance Foam for explicit surface reconstruction

2025-12-18 · Antonella Rech, Nicola Conci, Nicola Garau arxiv

Neural radiance fields (NeRF) have driven impressive progress in view synthesis by using ray-traced volumetric rendering. Splatting-based methods such as 3D Gaussian Splatting (3DGS) provide faster rendering by rasterizi…

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition

2026-04-29 · Amr Sharafeldin, Shrisudhan Govindarajan, Thomas Walker, Aryan Mikaeili 외 arxiv

Modern scene reconstruction methods, such as 3D Gaussian Splatting, deliver photo-realistic novel view synthesis at real-time speeds, yet their adoption in interactive graphics applications has been limited. A major bott…

Novel View Synthesis

Radiant: Large-scale 3D Gaussian Rendering based on Hierarchical Framework

2024-12-07 · Haosong Peng, Tianyu Qi, Yufeng Zhan, Hao Li 외

With the advancement of computer vision, the recently emerged 3D Gaussian Splatting (3DGS) has increasingly become a popular scene reconstruction algorithm due to its outstanding performance. Distributed 3DGS can efficie…

3DGS

Neural Rendering and Its Hardware Acceleration: A Review

2024-01-06 · Xinkai Yan, Jieting Xu, Yuchi Huo, Hujun Bao

Neural rendering is a new image and video generation method based on deep learning. It combines the deep learning model with the physical knowledge of computer graphics, to obtain a controllable and realistic scene model…

3D ReconstructionDeep LearningInverse RenderingNeural Rendering+1

Power Foam: Unifying Real-Time Differentiable Ray Tracing and Rasterization

2026-04-27 · Shrisudhan Govindarajan, Daniel Rebain, Dor Verbin, Kwang Moo Yi 외 arxiv

We introduce a differentiable 3D representation that unifies the ray tracing capabilities of foam-based ray tracing with the efficiency of modern rasterization pipelines. While prior foam representations enable constant-…