A distributed 3D print driver

Determining material arrangements to control high-resolution multi-material 3D printers for reproducing shape and visual attributes of a 3D model (e.g. spatially-varying color, translucency and gloss) requires large computational effort. Today's resolution and print tray sizes allow prints with more than 1012 voxels each filled with one of the available printing materials (today up to 7 materials can be combined in a single print). Cuttlefish, a 3D printing pipeline, processes the input in a serial fashion leading to increased computation time for higher number of models. Distributed computing is one way of achieving better performance for large computations. Through this master thesis, we have developed a distributed version of the cuttlefish printer driver in which the computational task is distributed amongst multiple nodes in the cluster and the resulting partial output is merged to generate the full slices. The architecture supports streaming, which is required to rapidly start the print before the full computation is finished, as cuttlefish processes the input in small parts and generates chunk-wise output. Finally, the comparison of the performance achieved by the distributed vs the non-distributed cuttlefish version is established to get a better understanding of the advantages and the challenges of distributed computing.