Combined loop transformation and hierarchy allocation for data reuse optimization

External memory bandwidth is a crucial bottleneck in the majority of computation-intensive applications for both performance and power consumption. Data reuse is an important technique for reducing the external memory access by utilizing the memory hierarchy. Loop transformation for data locality and memory hierarchy allocation are two major steps in data reuse optimization flow. But they were carried out independently. This paper presents a combined approach which optimizes loop transformation and memory hierarchy allocation simultaneously to achieve global optimal results on external memory bandwidth and on-chip data reuse buffer size. We develop an efficient and optimal solution to the combined problem by decomposing the solution space into two subspaces with linear and nonlinear constraints respectively. We show that we can significantly prune the solution space without losing its optimality. Experimental results show that our scheme can save up to 31% of on-chip memory size compared to the separated two-step method when the memory hierarchy allocation problem is not trivial. Also, run-time complexity is acceptable for the practical cases.