The reconfigurable computing system became an important choice according to accelerating compute-intensive applications.Among most compute-intensive applications

the matrix triangularization decomposition always was in the central position of research subjects and presented a great value to solve linear equation systems and matrix eigenvalue problems in science or engineering area.This paper analyzed the linear computing process of triangularization and proposed a hardware-adaptive parallel sub-matrix identity updating algorithm and a high-performance parallel structure hardware template for matrix triangularization on FPGA (Field Programmable Gate Array) according to the common triangularization computing process of the matrix triangularization decomposition.The research focused on the high-performance FPGA parallel structure implementation and optimization methods for the LU matrix triangularization decomposition.In theoretical analysis

the proposed algorithm presents better pipeline-parallelism and data-parallelism during the matrix triangularization process.The experimental result shows that the proposed structure gets over decuple speedup compared to general-purpose processors and the previous works in vital performance.