Photon mapping is a popular global illumination algorithm that can reproduce a wide range of visual effects including indirect illumination, color bleeding and caustics on complex diffuse, glossy, and specular surfaces modeled using arbitrary geometric primitives. However, the large amount of computation and tremendous amount of memory bandwidth, terabytes per second, required makes photon mapping prohibitively expensive for interactive applications. In this dissertation I present three techniques that work together to reduce the bandwidth requirements of photon mapping by over an order of magnitude. These are combined in a hardware architecture that can provide interactive performance on moderately-sized indirectly-illuminated scenes using a pre-computed photon map. 1. The computations of the naive photon map algorithm are efficiently reordered, generating exactly the same image, but with an order of magnitude less bandwidth due to an easily cacheable sequence of memory accesses. 2. The irradiance caching algorithm is modified to allow fine-grain parallel execution by removing the sequential dependency between pixels. The bandwidth requirements of scenes with diffuse surfaces and low geometric complexity is reduced by an additional 40% or more. 3. Generating final gather rays in proportion to both the incident radiance and the reflectance functions requires fewer final gather rays for images of the same quality. Combined Importance Sampling is simple to implement, cheap to compute, compatible with query reordering, and can reduce bandwidth requirements by an order of magnitude. Functional simulation of a practical and scalable hardware architecture based on these three techniques shows that an implementation that would fit within a host workstation will achieve interactive rates. This architecture is therefore a candidate for the next generation of graphics hardware
