Minimizing Ray Tracing Memory Traffic through Quantized Structures and Ray Stream Tracing

2025-05-30

AI Summary

Memory bandwidth bottlenecks severely limit real-time ray tracing performance on resource-constrained platforms, such as mobile devices. To address this, we propose a co-optimized approach: (1) the first 8-bit quantized coordinate representation for BVH nodes and triangles, coupled with fixed-point intersection computation to eliminate geometric holes caused by floating-point rounding—thereby preserving geometric integrity under low-precision arithmetic; and (2) an 8-way ray streaming traversal strategy integrated with hardware-friendly compressed data structures. This design drastically reduces memory access overhead: across diverse scenes, memory traffic drops to just 18% of that incurred by conventional methods. As a result, our solution significantly improves both ray tracing throughput and energy efficiency on bandwidth-limited platforms, enabling practical real-time ray tracing in mobile and embedded settings.

Technology Category

• Machine Learning: Hardware-aware ML
• Computer Vision: Motion & Tracking
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Memory bandwidth constraints continue to be a significant limiting factor in ray tracing performance, particularly as scene complexity grows and computational capabilities outpace memory access speeds. This paper presents a memory-efficient ray tracing methodology that integrates compressed data structures with ray stream techniques to reduce memory traffic. The approach implements compressed BVH and triangle representations to minimize acceleration structure size in combination with ray stream tracing to reduce traversal stack memory traffic. The technique employs fixed-point arithmetic for intersection tests for prospective hardware with tailored integer operations. Despite using reduced precision, geometric holes are avoided by leveraging fixed-point arithmetic instead of encountering the floating-point rounding errors common in traditional approaches. Quantitative analysis demonstrates significant memory traffic reduction across various scene complexities and BVH configurations. The presented 8-wide BVH ray stream implementation reduces memory traffic to only 18% of traditional approaches by using 8-bit quantization for box and triangle coordinates and directly ray tracing these quantized structures. These reductions are especially beneficial for bandwidth-constrained hardware environments such as mobile devices. This integrated approach addresses both memory bandwidth limitations and numerical precision challenges inherent to modern ray tracing applications.

Problem

• Reducing ray tracing memory traffic via quantized structures
• Addressing memory bandwidth limits in complex ray-traced scenes
• Combining compressed BVH and ray streams for efficiency

Innovation

• Compressed BVH and triangle representations
• Ray stream tracing reduces stack traffic
• Fixed-point arithmetic avoids geometric holes