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Contention-Aware Mapping and Scheduling Optimization for NoC-Based MPSoCs

机译:基于NOC的MPSoC的争用感知映射和调度优化

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Network-on-Chip (NoC) has emerged as an alternative interconnecting paradigm in the state-of-the-art multi-core architectures. Its capability of parallel data transfer over various paths increases the possibility of resource contention and causes network congestion. How to avoid contention, as well as to optimize performance and energy consumption becomes a great challenge for system designers. In this paper, we consider spatial and temporal aspects of communication to avoid contention. In spatial aspect, we propose to utilize overlapped communication paths to estimate the degree of contention, such that they can be minimized in mapping stage. In temporal aspect, we sequentialize data transfer with potential contention by introducing additional latency. To optimize the design concerns with the corresponding constraint model, we further provide an efficient algorithm to search for better solutions for the problem, which integrates a local search process into a genetic algorithm and applies various heuristics in initialization and evolution process. Experimentations from random and real-case benchmarks demonstrate the efficiency of our method in multi-objective optimization and the effectiveness of our techniques in avoiding network contention, while keeping performance and energy consumption optimized.
机译:片上网(NOC)已成为最先进的多核架构中的替代互连范式。它在各种路径上并行数据传输的能力增加了资源争用的可能性并导致网络拥塞。如何避免争用,以及优化性能和能源消耗成为系统设计师的巨大挑战。在本文中,我们考虑沟通的空间和时间方面,以避免争用。在空间方面,我们建议利用重叠的通信路径来估计争用程度,使得它们可以在映射阶段中最小化。在时间方面,通过引入额外延迟,我们通过潜在的争用来顺序数据传输。为了优化与相应的约束模型的设计问题,我们还提供了一种有效的算法来搜索问题的更好解决方案,这将本地搜索过程集成到遗传算法中,并在初始化和演化过程中应用各种启发式方法。随机和实际基准的实验证明了我们在多目标优化中的方法的效率和我们在避免网络争用方面的技术的有效性,同时保持性能和能耗优化。

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