Distributed Denoising Algorithm for Real-Time Ray Tracing
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Solution Overview
Problem
Existing denoising frameworks for real-time ray tracing operate on a single machine, limiting their ability to access all rendered pixels across multiple devices, which hampers the computation of a denoised image in distributed rendering systems.
Innovation Solution
A distributed denoising algorithm that collects 'ghost region' data from neighboring nodes to enable efficient denoising across multiple devices, using both AI and non-AI techniques, and continuously updates a machine learning engine during runtime with new training data to improve denoising performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rendering is distributed across multiple devices, then rendering capacity and speed are improved, but access to all rendered pixels for denoising becomes limited
Solution Approach 1:
The patent introduces a distributed denoising framework that acts as an intermediary system between multiple rendering devices. This framework collects rendered pixels from various devices through a standardized interface, aggregates them centrally, and distributes denoised results back to the original devices, thereby mediating the information access problem while maintaining distributed rendering benefits
Solution Approach 2:
The patent merges the denoising operations across multiple devices by collecting rendered pixels from different rendering nodes into a unified denoising pool. This combination allows the system to treat distributed rendered pixels as if they were from a single source, enabling effective denoising despite the physical distribution of rendering operations
2Ease of operation
If existing single-machine denoising frameworks are used, then denoising simplicity is maintained, but distributed rendering compatibility is lost
Solution Approach 1:
The patent creates a universal denoising framework that can handle both single-machine and distributed rendering scenarios. The system provides a standardized interface that works across different rendering architectures, making the denoising solution adaptable to various deployment configurations without requiring separate specialized frameworks
Data Source
AI summary
Apparatus and method including cell primitive for unstructured volume rendering. For example, one embodiment of an apparatus comprises: a ray generator to generate a plurality of rays in a first graphics scene; a hierarchical acceleration data structure generator to construct a hierarchical acceleration data structure comprising a plurality of hierarchically arranged nodes including leaf nodes and inner nodes; traversal circuitry to traverse one or more of the rays through the hierarchical acceleration data structure; unstructured volume intersection circuitry to intersect a ray with an unstructured volume primitive within a leaf node of the hierarchical acceleration data structure, the unstructured volume intersection circuitry to determine multiple intersection hits between a ray and an unstructured volume primitive.