Abstract: Digital Signal Processor (DSP) are widely used in numerous fields such as image proces- sing, automation control, and signal processing. Matrix DSPs, which are independently developed by ourselves, adopt a typical vectorization architecture of Single Instruction Multiple Data (SIMD) + Very Long Instruction Word (VLIW). Therefore, it is a prominent challenge to implement efficient vecto- rized programming and optimization for such architecture. According to the characteristics of Matrix DSP and the compilation performance, the analysis and optimization methods commonly used in the kernels are summarized. Furthermore, an example of general matrix multiplication (GEMM) is used to show that the execution performance can be improved by up to 1 order of magnitude. Based on the summary of optimization methods, some follow-up thoughts and discussions are proposed from the perspective of compiler optimization and programmers’ efficient programming.

Key words: Matrix DSP, vectorization programming, program optimization, compiler