Neural Radiance Cache Implementation on Mobile GPU

We present a Neural Radiance Cache (NRC) integrated into the global illumination and reflection passes of a hybrid renderer targeting mobile devices. Real-time Monte Carlo rendering on mobile remains challenging due to limited compute and memory bandwidth, despite the emergence of hardware-accelerated ray tracing on mobile GPUs. Ray tracing workloads often exhibit incoherent memory access patterns that can bottleneck GPU performance. In contrast, our NRC implementation shifts this cost toward predictable, compute-centric neural inference. Our design features a fused MLP architecture implemented entirely in compute shaders, along with an efficient path-traced training pipeline decoupled from inference. While introducing more overhead than traditional radiance cache techniques, our mobile-optimized NRC achieves higher perceptual quality while maintaining real-time frame rates across a range of scenes on modern mobile hardware.