Field-programmable gate arrays (FPGAs) can efficiently implement custom applications via their embedded digital signal processor (DSP) slices, including binary multipliers. An increasing number of binary multipliers belonging to a DSP slice usually demonstrate that it has the capacity to process as many multiplication operations as possible in one clock cycle. In order to fully utilize the DSP resource, in this paper, we propose a novel DSP slice optimization method to achieve parallel multiplication on single DSP slice, namely PMSDS. First, the PMSDS splits multiplicators into two separate parts, i.e., valid bits and vacant bits, using a customized polynomial algebra method. Then, the PMSDS pre-calculates the maximum number of overflow bits combining the above-mentioned polynomial algebra method. Finally, it computes the total multiplicators' bit numbers and parallel the final multiplicators. We also propose an optimization model to find the best parallel solution according to the performance and precision of a single DSP slice. Moreover, we implement a PMSDS-based matrix multiplication algorithm supporting the computing precision dynamically changing. The experiments based on a large-scale and real-world matrix multiplication show that the PMSDS has better performance in latency and resource utilization than the traditional, add-tree, and full-unroll methods and is more outstanding in frequency and dynamic power consumption comparing with the state-of-the-art methods.