Direct Load: Dependence-Linked Dataflow Resolution of Load Address and Cache Coordinates

Byung-Kwon Chung: USUN02-203, Sun Microsystems

Jinsuo Zhang: Department of CISE, University of Florida

Jih-Kwon Peir: Department of CISE, University of Florida

Shih-Chang Lai: Department of ECE, Oregon State University

Konrad Lai: Microprocessor Research Lab, Intel Corp.



An increasing cache latency in future processors incurs profound performance impacts in spite of advanced out-of-order execution techniques. In this paper, we describe an early address resolution mechanism that accurately resolves both regular and irregular load addresses. The basic idea is to build dynamic dependence links from the instruction that updates the base register to the consumer load instructions. Once a new base address is available, it triggers calculations of the new load addresses for dependent loads. Furthermore, the exact cache location of the requested data is predicted based on the newly resolved load address. As a result, this direct load can access the data cache directly to achieve a zero-cycle load latency. Performance evaluation using SPEC integer programs shows that the dynamic dependence links can be established accurately. Combined with a stride-based predictor, the proposed early address resolution achieves about 97% average accuracy with less than 1% misprediction. Based on a modified SimpleScalar model, the proposed method can potentially improve the IPC by about 18%.