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Parallel computing is an important method used in high performance computing. A new SIMD architecture named ESCA (Engineering and Science Computing Accelerator) is introduced briefly in this paper. It aims to accelerate the computation for most critical scientific workload as a coprocessor by virtue of outstanding architecture and flexible parallel algorithm. As dense matrix multiplication is a widely used operation that can be accelerated by parallel computing, we maps its algorithm onto ESCA and estimates the performance, and the results imply that ESCA has some advantage and potentiality.