Optimizing Memory Hierarchy Allocation With Loop Transformations For High-Level Synthesis

For the majority of computation-intensive application systems, off-chip memory bandwidth is a critical bottleneck for both performance and power consumption. The efficient utilization of limited on-chip memory resources plays a vital role in reducing the off-chip memory accesses. This paper presents an efficient approach for optimizing the on-chip memory allocation by loop transformations in the imperfectly nested loops. We analytically model the on-chip buffer size and off-chip bandwidth after affine loop transformation, loop fusion/distribution and code motion. Branch-and-bound and knapsack reuse techniques are proposed to reduce the computation complexity in finding optimal solutions. Experimental results show that our scheme can save 40% of on-chip memory size with the same bandwidth consumption compared to the previous approaches.