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Abstract

We present an implementation approach for Marching Cubes (MC) on graphics
hardware for OpenGL 2.0 or comparable graphics APIs. It currently outperforms
all other known graphics processing units (GPU)-based iso-surface extraction
algorithms in direct rendering for sparse or large volumes, even those using
the recently introduced geometry shader (GS) capabilites. To achieve this, we
outfit the Histogram Pyramid (HP) algorithm, previously only used in GPU data
compaction, with the capability for arbitrary data expansion. After
reformulation of MC as a data compaction and expansion process, the HP
algorithm becomes the core of a highly efficient and interactive MC
implementation. For graphics hardware lacking GSs, such as mobile GPUs, the
concept of HP data expansion is easily generalized, opening new application
domains in mobile visual computing. Further, to serve recent developments, we
present how the HP can be implemented in the parallel programming language CUDA
(compute unified device architecture), by using a novel 1D chunk/layer
construction.