Optimization of PISA Architecture Chip Resource Ranking Based on Genetic Algorithm

At present, high and new technology has become an important direction of scientific and technological development, and chips have become an important direction for the scientific and technological game of great powers. This article focuses on the PISA architecture of one of the mainstream architectures of the programmable chip. By discussing the multi -faceted constraints of the architecture in the execution process, the ranking method of the best source sequence is to reduce the number of levels required for the chip assembly line as much as possible. Save chip resources. This article first analyzes the multi -faceted dependencies of the basic block of the constraint procedures. For data dependence, after reading, post -reading dependencies in data dependence, designing joint judgment algorithms, and improving the judgment efficiency of two similar dependencies. After writing dependencies, the design corresponding algorithm is designed to judge and solve. The judgment of control dependence uses the relevant knowledge of the set. This article designs the True set control dependency judgment method. By analyzing whether the two basic blocks can be reached whether there is a real relationship, combined with the comprehensive judgment of the collection of the basic blocks of the difference, you can judge this two Whether the basic block is controlled. The seven resources constraints are used for modeling, and the maximum value of the streamliner level is set up to find the minimum target function, and the traditional genetic algorithm is used to solve the model.