Applications run in embedded systems should usually be completed within the constrained time to reduce energy consumption. Therefore, the memory of embedded system should satisfy time-efficient and energy-efficient. Domain Wall Memory (DWM) achieves high energy efficiency, high density, non-volatile and low cost advantages. However, the data access on DWM always requires shift operations to align the domain with the port which can access the data in the domain. In the case that there are multi-core processors with multi-port DWM, the data placement and scheduling, therefore, can extremely affect the parallelism, total execution time and performance. In this paper, we handle the data placement and scheduling on multi-port DWM in multi-core system (DPSMDMS), and provide the integer linear programming (ILP) algorithm to solve this problem optimally. What is more, we propose a layering and grouping for data placement and scheduling (LGPS) heuristic algorithm to get the approximate optimal solution in polynomial time. In benchmarks, the experimental results show that ILP and LGPS reduce on average 64.6% and 64.8% of the total execution time, respectively, compared with the non-optimized strategy.

在嵌入式系统中运行的应用程序通常应在有限的时间内完成，以减少能耗。因此，嵌入式系统的存储器应满足省时和节能的要求。域墙内存（DWM）具有高能效，高密度，非易失性和低成本优势。但是，DWM上的数据访问始终需要进行移位操作才能使域与可以访问域中数据的端口对齐。如果存在具有多端口DWM的多核处理器，那么数据的放置和调度会极大地影响并行性，总执行时间和性能。在本文中，我们处理多核系统（DPSMDMS）中多端口DWM上的数据放置和调度，并提供整数线性规划（ILP）算法来最佳地解决此问题。此外，我们提出了一种用于数据放置和调度（LGPS）启发式算法的分层和分组方法，以获得多项式时间内的近似最优解。在基准测试中，实验结果表明，与非优化策略相比，ILP和LGPS分别平均减少了总执行时间的64.6％和64.8％。