Exploration of 3D grid caching strategies for ray-shooting

Abstract

Technology evolution gives an easy access to high performance dedicated computing machines using, for example, GPUs or FPGAS. When designing algorithms dealing with highly structured multidimensional data, the real bottleneck is often linked to memory access. The strategies implemented in standard CPU cache architectures are no longer efficient due to the parallelism level and the inherent structure of data. This article presents the so-called "n-Dimensional Adaptive and Predictive Cache" (nD-AP Cache) architecture aiming at efficient data access for grid traversal. A theoretical model of the 3D version of the cache was setup in order to predict the cache efficiency for given statistical characteristics of the access sequences and for given parameters of the cache. The practical example of ray shooting algorithms has been chosen in order to carefully explore the design space and exercise the 3D-AP cache. For this purpose, a simulation model as well as a fully functional emulation platform have been designed. Thanks to the proven efficiency of the architecture further improvement and applications of the nD-AP Cache are discussed. Comparisons with standard caches show that the nD-AP Cache allows to be two times more efficient than an "ideal" associative cache and, this, with four times less memory.