Maximum complete subgraph-based embedded system register allocation method

Abstract

The invention provides a maximum complete subgraph-based embedded system register allocation method, which mainly solves the problems that a heuristic algorithm has poor allocation effect and overflow cost is too high due to no consideration of the overflow cost in a crossover operator part in an evolutionary algorithm. The method is implemented by the following steps of: (1) taking a complement from an intermediate variable mutual interference graph to obtain the complement G; (2) randomly dividing all nodes into two classes, respectively putting the nodes into a set A or a set B, and completing initialization of population; (3) crossing an individual in the population by using an overflow cost-based maximum complete subgraph crossover operator SC-MCX to generate a subgeneration individual; and (4) optimizing the subgeneration individual by using a local search operator LSP, replacing an individual having the maximum fitness function value in parent individuals by using the optimized subgeneration individual, and continuously participating in population evolution. By the method, the population evolution speed is improved, the overflow cost and the overflow variable number of the individual are reduced, and the method can be used for embedded system register allocation.

Description

technical field [0001] The invention belongs to the field of computer technology, and relates to an embedded system, in particular to a method for allocating registers of an embedded system based on a maximum complete subgraph. Intermediate variables are stored in registers as much as possible, thereby reducing overflow costs and the number of overflow variables, improving the utilization of registers, and improving the compilation efficiency of programs in embedded systems. Background technique [0002] In an embedded system, a program is usually written to achieve a fixed function, so it is required that the written program can generate high-quality code after compilation and have high execution efficiency. Both memory and registers are used to store intermediate variables generated during program compilation. Compared with memory, the access speed of registers is much faster, but the number is very small. During program compilation, if registers cannot store all interme...

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Problems solved by technology

Although CFPX is better than GPX in design, it fully considers the conflict relationship between the intermediate variables stored in the inherited registers, but it only considers the number of intermediate variables, and does not consider the overflow cost of each variable, so it cannot Called a perfect crossover operator, the obtained register allocation scheme still has more intermediate variables spilled into the memory, which reduces the efficiency of register allocation

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