Today, due to problems in improving computing performance, parallel programming continues to evolve. There are many different languages in which you can write parallel programs. One of them is the functional-threading parallel programming language Pifagor, which in turn is very specific and allows you to write a program with maximum parallelism, as well as it is designed to solve the portability problem of parallel programs. Tools and a library of functions continue to be developed for this language. This study is devoted to the development of elements of the mathematical library and the search for the most effective mathematical parallel algorithms. The following methods are considered and used in the work: sequential, recursive (left and right recursion), factorization, and pairwise comparisons. As a result of the study, a number of mathematical functions were developed, and a study was made of the possibility of using these functions in the development of programs for multiplying large-dimensional matrices. The work demonstrates the effectiveness of using the developed simple functions implemented by different methods in matrix multiplication programs. The prospects of further work in this direction are noted, having in mind the analysis of the possibility of using artificial intelligence methods to increase efficiency and facilitate the development of parallel programs with large-sized matrices.
Formal Verification of Programs in Functional Dataflow Parallel Language
