Benchmark is a method of measuring performance, and we can obtain continuous performance improvement of programming algorithm through Benchmark validation. In order to solve large-scale linear programming problems, this paper proposes an integrated Benchmark validation which integrates theoretical Benchmark analysis with advance language-based Benchmark. Through the integrated Benchmark validation, we can continuously improve an optimizing algorithm, and validate whether the new optimizing algorithm achieves the performance objectives. The results of experiments show the proposed integrated Benchmark validation is an effective method for developing large-scale linear programming algorithms.