Address compression for scalable load/store queue implementation

Contemporary superscalar processors employ the load/store queue for memory disambiguation. A load/store queue is typically implemented with a CAM structure to search the address for collision and consequently poses scalability challenges of energy consumption and area cost. This paper proposes an address compression technique for load/store queue to improve the power efficiency and scalability. Using the proposed approach, the LSQ can reduce the energy consumption ranging from 38% to 72% and area cost ranging from 32% to 66%, depending on the compression parameter and system configuration. The approach can provide 3.08% overall processor energy reduction and causes only 0.22% performance loss at a balanced configuration.