A new parallel version of a dichotomy based algorithm for indexing powder diffraction data
One of the key parts of the crystal structure solution process from powder diffraction data is the determination of the lattice parameters from experimental data shortly called indexing. The successive dichotomy method is the one of the most common ones for this process because it allows an exhaustive search. In this paper, we discuss several improvements for this indexing method that significantly reduce the search space and decrease the solution time. We also propose a combination of this method with other indexing methods: grid search and TREOR. The effectiveness and time-consumption of such algorithm were tested on several datasets, including orthorhombic, monoclinic, and triclinic examples. Finally, we discuss the impacts of the proposed improvements.
Efficient Converting of Large Sparse Matrices to Quadtree Format
Stať ve sborníku
Computations with sparse matrices are widespread in scientific projects. Used data format affects strongly the performance and also the space-efficiency. Commonly used storage formats (such as COO or CSR) are not suitable neither for some numerical algebra operations (e.g., The sparse matrix-vector multiplication) due to the required indirect addressing nor for I/O file operations with sparse matrices due to their high space complexities. In our previous papers, we prove that the idea of using the quad tree for these purposes is viable. In this paper, we present a completely new algorithm based on bottom-up approach for the converting matrices from common storage formats to the quad tree format. We derive the asymptotic complexity of our new algorithm, design the parallel variant of the classical and the new algorithm, and discuss their performance.