Optimal Data Scheduling for Uniform Multidimensional Applications

Uniform nested loops are broadly used in scientific and multi-dimensional digital signal processing applications. Due to the amount of data handled by such applications, on-chip memory is required to improve the data access and overall system performance. In this study, a static data scheduling method, carrot-hole data scheduling, is proposed for multi-dimensional applications, in order to control the data traffic between different levels of memory. Based on this data schedule, optimal partitioning and scheduling are selected. Experiments show that by using this technique, on-chip memory misses are significantly reduced as compared to results obtained from traditional methods. The carrot-hole data scheduling method is proven to obtain smallest on-chip memory misses compared with other linear scheduling and partitioning schemes. This work was supported in part by the NSF CAREER grant MIP 95-01006, and by the William D. Mensch, Jr. Fellowship.