Research on parallel principal component analysis based on ternary optical computer

Abstract

Principal component analysis (PCA) is a widely used algorithm in the field of artificial intelligence and statistical analysis. When dealing with a large number of high-dimensional data, the traditional PCA algorithm has some shortcomings, such as slow processing speed, high power consumption, low computational efficiency. By taking advantage of several characteristics which include large number of data bits, easy-expansion of data bits, and parallel computing in ternary optical computer (TOC), the implementation scheme of parallel PCA algorithm is studied. Through the analysis of the traditional PCA algorithm, the parallel parts are found out and parallel design is carried out. Then, the elaborate implementation flow of the algorithm is given, and the clock cycle and hardware resources of the algorithm are also analyzed. Finally, the validity of the parallel scheme is proved by experiments. Compared with the traditional PCA algorithm, the PCA algorithm based on TOC has better time performance, operational efficiency, and gives full play to the advantage of ternary optical computer in processing complex computation.