Hardware acceleration is crucial in modern embedded system design to meet the explosive demands on performance and cost. Selected computation kernels for acceleration are usually captured by nest loops, which are optimized by state-of-the-art techniques like loop tiling and loop pipelining. However, memory bandwidth bottlenecks prevent designs to reach optimal throughput with respect to available parallelism. In this paper we present an automatic memory partitioning technique which can efficiently improve throughput and reduce energy consumption of pipelined loop kernels for given throughput constraints and platform requirement. Our partition scheme consists of two steps, the first step considers cycle accurate scheduling information to meet the hard constraints on memory bandwidth requirements specifically for synchronized hardware designs. Experimental results show an average 6X throughput improvement on a set of real world designs with moderate area increase (about 45% on average),...