Path Tracing on Massively Parallel Neuromorphic Hardware
Abstract
Ray tracing on parallel hardware has recently benefit from significant advances in the graphics hardware and associated software tools. Despite this, the SIMD nature of graphics card architectures is only able to perform well on groups of coherent rays which exhibit little in the way of divergence. This paper presents SpiNNaker, a massively parallel system based on low power ARM cores, as an architecture suitable for ray tracing applications. The asynchronous design allows us to demonstrate a linear performance increase with respect to the number of cores. The performance perWatt ratio achieved within the fixed point path tracing example presented is far greater than that of a multi-core CPU and similar to that of a GPU under optimal conditions.
BibTeX
@inproceedings {10.2312:LocalChapterEvents:TPCG:TPCG12:025-028,
booktitle = {Theory and Practice of Computer Graphics},
editor = {Hamish Carr and Silvester Czanner},
title = {{Path Tracing on Massively Parallel Neuromorphic Hardware}},
author = {Richmond, Paul and Allerton, David J.},
year = {2012},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-93-7},
DOI = {10.2312/LocalChapterEvents/TPCG/TPCG12/025-028}
}
booktitle = {Theory and Practice of Computer Graphics},
editor = {Hamish Carr and Silvester Czanner},
title = {{Path Tracing on Massively Parallel Neuromorphic Hardware}},
author = {Richmond, Paul and Allerton, David J.},
year = {2012},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-93-7},
DOI = {10.2312/LocalChapterEvents/TPCG/TPCG12/025-028}
}