Abstract: A parallel processing apparatus includes: processors; and a network switch, wherein a first processor: generates divided matrix data by dividing the matrix data in such a manner that an overlapping portion is present with each other; transmits the divided matrix data to a second processor; generates first evaluation-value matrix data from the divided matrix data; transmits, to the second processor, first elements in a first overlapping portion of the first evaluation-value matrix data; receives, from the second processor, second elements of a second overlapping portion of second evaluation-value matrix data; calculates first added evaluation data by adding the second elements to the first elements; transmits the first added evaluation data to the second processor; receives, from the second processor, second added evaluation data; and calculates a first C point or a first F point based on the first evaluation-value matrix data which is updated using the second added evaluation data.

Abstract: A parallel processing apparatus includes: processors; and a network switch, wherein a first processor: generates divided matrix data by dividing the matrix data in such a manner that an overlapping portion is present with each other; transmits the divided matrix data to a second processor; generates first evaluation-value matrix data from the divided matrix data; transmits, to the second processor, first elements in a first overlapping portion of the first evaluation-value matrix data; receives, from the second processor, second elements of a second overlapping portion of second evaluation-value matrix data; calculates first added evaluation data by adding the second elements to the first elements; transmits the first added evaluation data to the second processor; receives, from the second processor, second added evaluation data; and calculates a first C point or a first F point based on the first evaluation-value matrix data which is updated using the second added evaluation data.

Abstract: A parallel processing method for performing operation for each row data of matrix data and outputting solution data for each row, for solving matrix simultaneous linear equations, by using at least one of the Gauss-Seidel method and the SOR method using matrix data, the parallel operation method including: performing parallel operation on elements at a right side of diagonal elements of the matrix data for each of rows of the row data to calculate right-side operation result data; performing parallel operation on elements at a left side of the diagonal elements of the matrix data for each of rows of the row data using a solution data to calculate left-side operation result data; and calculating the solution data of the diagonal elements of the matrix data of the row data using the right-side operation result data and the left-side operation result data.