Layered Spiral Algorithm for memory-aware mapping and scheduling on Network-on-Chip

Shuo Li, Fahimeh Jafari, A. Hemani, Shashi Kumar
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引用次数: 3

Abstract

In this paper, Layered Spiral Algorithm (LSA) is proposed for memory-aware application mapping and scheduling onto Network-on-Chip (NoC) based Multi-Processor System-on-Chip (MPSoC). The energy consumption is optimized while keeping high task level parallelism. The experimental evaluation indicates that if memory-awareness is not considered during mapping and scheduling, memory overflows may occur. The underlying problem is also modeled as a Mixed Integer Linear Programming (MILP) problem and solved using an efficient branch-and-bound algorithm to compare optimal solutions with results achieved by LSA. Comparing to MILP solutions, the LSA results demonstrate only about 20% and 12% increase of total communication cost in case of a small and middle size synthetic problem, respectively, while it is order of magnitude faster than the MILP solutions. Therefore, the LSA can find acceptable total communication cost with a low runtime complexity, enabling quick exploration of large design spaces, which is infeasible for exhaustive search.
片上网络内存感知映射和调度的分层螺旋算法
本文提出了分层螺旋算法(LSA),用于内存感知应用映射和调度到基于片上网络(NoC)的多处理器片上系统(MPSoC)。在保持高任务级并行性的同时,优化了能耗。实验评估表明,如果在映射和调度过程中不考虑内存感知,可能会发生内存溢出。潜在的问题也被建模为混合整数线性规划(MILP)问题,并使用有效的分支定界算法来解决最优解与LSA得到的结果进行比较。与MILP解决方案相比,LSA的结果表明,对于小型和中型综合问题,LSA的总通信成本分别只增加了约20%和12%,而比MILP解决方案快了几个数量级。因此,LSA能够以较低的运行复杂度找到可接受的总通信成本,从而实现对大型设计空间的快速探索,这是穷穷搜索所无法实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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