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Configuration Mapping Algorithms to Reduce Energy and Time Reconfiguration Overheads in Reconfigurable Systems

机译:配置映射算法可减少可重配置系统中的能源和时间重配置开销

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In spite of the increasing success of reconfigurable hardware, the dynamic reconfiguration can introduce important overheads, both in terms of energy consumption and time, especially when configurations are fetched from an external memory. To address this problem, this paper presents a configuration memory hierarchy including two on-chip memory modules with different access time and energy consumption features. In addition, we have developed two configuration mapping algorithms that take advantage of these memories to reduce the system energy consumption, while increasing its performance. The first algorithm has been optimized for systems with reduced dynamic behavior; hence it optimizes the system for each given set of tasks. The second algorithm targets dynamic systems where the active tasks change unpredictably. Thus, its objective is also to decrease the pressure on the on-chip memories to reduce capacity conflicts. The presented results will demonstrate that, with the proper management, our configuration memory hierarchy leads to an energy consumption reduction up to 81% with respect to fetching the configurations from the external memory, while keeping the system performance very close to the ideal upper-bound one.
机译:尽管可重新配置的硬件取得了越来越大的成功,但是动态重新配置会在能耗和时间方面引入重要的开销,尤其是当从外部存储器获取配置时。为了解决这个问题,本文提出了一种配置存储器层次结构,其中包括两个具有不同访问时间和能耗特性的片上存储器模块。此外,我们还开发了两种配置映射算法,这些算法利用这些内存来减少系统能耗,同时提高其性能。第一种算法已经针对动态行为降低的系统进行了优化。因此,它针对每个给定的任务集优化了系统。第二种算法针对动态系统,在这些系统中活动任务发生不可预测的变化。因此,其目的还在于减少片上存储器上的压力以减少容量冲突。呈现的结果将表明,通过适当的管理,相对于从外部存储器中获取配置,我们的配置内存层次结构可将能耗降低多达81%,同时使系统性能非常接近理想的上限。一。

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