Parallelization of Atomic Image Reconstruction from X-ray Fluorescence Holograms with XcalableMP

X-ray fluorescence holography is a three-dimensional middle range local structure analysis method, which can provide three-dimensional atomic images around specific elements within a radius of a few nanometers. Three-dimensional atomic images are reconstructed by applying discrete Fourier transform (DFT) to hologram data. Presently, it takes long time to process this DFT. In this study, the DFT program is parallelized by using a parallel programming language XcalableMP. The DFT process, whose input is 21 holograms data of 179 × 360 points and output is a three-dimensional atomic image of 1923 points, is executed on PC cluster which consists of 8 nodes of Intel Xeon X5660 processors and 96 cores in total and we confirmed that the parallelized DFT execution is 94 times faster than the sequential execution.

Performance of Parallel Distributed Bat Algorithm using MPI on a PC Cluster

Optimization algorithms are often used to obtain optimal solutions to complex nonlinear problems and appear in many areas such as control, communication, computation, and others. Bat algorithm is a heuristic optimization algorithm and efficient in obtaining approximate best solutions to non-linear problems. In many situations complex problems involve large amount of computations that may require simulations to run for days or weeks or even years for an algorithm to converge to a solution. In this research, a Parallel Distributed Bat Algorithm (PDBA) is formulated using Message Passing Interface (MPI) in C language code for a PC Cluster. The time complexity of PDBA is determined and presented. The performance in terms of speed-up, efficiency, elapsed time, and number of times fitness function is executed is also presented.