electronic visualization laboratory, university of illinois at chicago Sort Last Parallel Rendering for Viewing Extremely Large Data Sets on Tile Displays (PVG 2001) Kenneth Moreland, Sandia National Labs

electronic visualization laboratory, university of illinois at chicago Summary General idea - N processors running a T tile display generate T images, 1 for each tile Images are composite and displayed at the processors controlling the tiles Polygons to be rendered at distributed on N processors and projection information is scattered, telling the processors which tiles their images should go to

electronic visualization laboratory, university of illinois at chicago 4 strategies Four different strategies are described for composition 1. Serial (every node in charge of a tile generates T images for that tile and composes) – worst case algorithm. 2. Virtual trees 3. Tile, Split and Delegate 4. Reduce to a single tile

electronic visualization laboratory, university of illinois at chicago Virtual Trees Compositing is done in several binary trees in parallel The tiles done with compositing drop the computation and join other trees The scheduling is done so that processors with least number of images to send act as receivers and vice versa A disadvantage is that during the final stage of compositing, most processors are idle

electronic visualization laboratory, university of illinois at chicago Tile, Split and Delegate Assign a processor to a section of a tile More processors are assigned for tiles which require more image composition A disadvantage is communication cost is high - O(N2)

electronic visualization laboratory, university of illinois at chicago Reduce to Single Tile Images rendered at any processor are sent directly to a single processor (for each tile) A binary swap algorithm is used to composite them Communication time – O(N*T + NlogN) – more scalable

electronic visualization laboratory, university of illinois at chicago Optimization Bucketing – do not distribute all polygons to everyone – tiles with very few polygons do not need rendering of all other polygons Active pixel encoding –the blank pixels are termed inactive –RLE compression is used –free decoding (use a max depth value for inactive pixels

electronic visualization laboratory, university of illinois at chicago Optimization, Results Floating viewport – render all polygons on one node and shift pixels when image straddles other tiles Results Reduce strategy performs better and scales with a linear speedup