The 3D holographic display has long been expected as a future human interface as it does not require users to wear special devices. However, its heavy computation requirement prevents the realization of such displays. A recent study says that objects and holograms with several giga-pixels should be processed in real time for the realization of high resolution and wide view angle. To this problem, first, we have adapted a conventional FFT algorithm to a GPU cluster environment in order to avoid heavy inter-node communications. Then, we have applied several single-node and multi-node optimization and parallelization techniques. The single-node optimizations include a change of the way of object decomposition, reduction of data transfer between the CPU and GPU, kernel integration, stream processing, and utilization of multiple GPUs within a node. The multi-node optimizations include distribution methods of object data from host node to the other nodes. Experimental results show that intra-node optimizations attain 11.52 times speed-up from the original single node code. Further, multi-node optimizations using 8 nodes, 2 GPUs per node, attain an execution time of 4.28 sec for generating a 1.6 giga-pixel hologram from a 3.2 giga-pixel object. It means a 237.92 times speed-up of the sequential processing by CPU and 41.78 times speed-up of multi-threaded execution on multicore-CPU, using a conventional FFT-based algorithm.

Computer-generated hologram based on ray-sampling plane method was newly applied to the projection-type holographic display that consists of the holographic projection and the holographic optical element screen. In the proposed method, geometric deformation characteristic of the holographic image via the display system was mathematically derived and canceled out by the coordinate transformation of ray-sampling condition to avoid the image distortion. In the experiment, holographic image reconstruction with the arbitral depth expression without image distortion could be optically demonstrated.