Spatial accelerators provide massive parallelism with an array of homogeneous PEs, and enable efficient data reuse with PE array dataflow and on-chip memory. Many previous works have studied the dataflow architecture of spatial accelerators, including performance analysis and automatic generation. However, existing accelerator generators fail to exploit the entire memory-level reuse opportunities, and generate suboptimal designs with data duplication and inefficient interconnection.