Abstract: To improve the efficiency of program, it is used to arrange multiple function units in modern superscalar processor, supporting to execute instructions in parallel.The allocation policy of computing resources plays an important role in taking full advantage of multiple function units.Although the policy of how to allocate computing resources and schedule instruction has been well studied in literature, the proposed solutions almost concentrate on optimization methods at compile time, which is mostlystatic, inflexible and inefficient because of lack of computing pipeline information at run time.To mitigate the negative impacts of improper computing resource allocation and maximize the power of multiple function units, this paper abstracts the mathematical model of resource allocation problem at run time and makes a study of hardware fine-grained automatic method based on symmetric and asymmetric configuration of function units, in order to make dynamic and wise computing resource allocating decision when instructions are issued in general situation.As a result, a load-balanced greedy resource allocation strategy is proposed and evaluated.The experimental results show that our policy is efficient to minimize blocking time caused by unfair allocation of computing resources.Furthermore, the more computing resources are provided, the better performance our policy can yield.

Key words: Instruction issue, Instruction scheduling, Load balance, Pipeline, Resource allocation