High Performance Computing Approaches for 3D Reconstruction of Complex Biological Specimens

Abstract

Knowledge of the structure of specimens is crucial to determine the role that they play in cellular and molecular biology. To yield the three-dimensional (3D) reconstruction by means of tomographic reconstruction algorithms, we need the use of large projection images and high processing time. Therefore, we propose the use of the high performance computing (HPC) to cope with the huge computational demands of this problem. We have implemented a HPC strategy where the distribution of tasks follows the master–slave paradigm. The master processor distributes a slab of slices, a piece of the final 3D structure to reconstruct, among the slave processors and receives reconstructed slices of the volume. We have evaluated the performance of our HPC approach using different sizes of the slab. We have observed that it is possible to find out an optimal size of the slab for the number of processor used that minimize communications time while maintaining a reasonable grain of parallelism to be exploited by the set of processors.