The management of the energy consumption and thermal dissipation of multi-core heterogeneous platforms is becoming increasingly important as it can have direct impact on the platform performance. This paper discusses an approach that enables fast exploration and validation of heterogeneous system on chips (SoCs) platform configurations with respect to their thermal dissipation. Such platforms can be configured to find the optimal trade-off between performance and power consumption. This directly reflects in the head dissipation of the platform, which when increases over a given threshold will actually decrease the performance of the platform. Therefore, it is important to be able to quickly probe and explore different configurations and identify the most suitable one. However, this task is hindered by the large space of possible configurations of such platforms and by the time required to benchmark each configurations. As such, we propose an approach in which we construct a model of the thermal dissipation of a given platform using a system identification methods and then we use this model to explore and validate different configurations. The approach allows us to decrease the exploration time with several orders of magnitude. We exemplify the approach on an Odroid-XU4 board featuring an Exynos 5422 SoC.
翻译:管理多核心多元平台的能源消耗和热耗散正在变得日益重要,因为它能够对平台性能产生直接影响。本文讨论一种能够快速探索和验证芯片(SoCs)平台配置的多元系统及其热耗散的方法。可以配置这些平台,以找到性能和电能消耗的最佳取舍。这直接反映在平台的头部消散中,当某一阈值增加时,平台的性能实际上会下降。因此,必须能够快速探测和探索不同的配置,并找出最合适的配置。然而,由于这些平台可能配置的空间巨大,以及设定每个配置基准所需的时间,这项任务受到阻碍。因此,我们提出一种方法,即我们用系统识别方法构建一个特定平台热耗散模型,然后我们用这个模型来探索和验证不同的配置。该方法使我们能够用几个数量级来减少探索时间。我们用一个Odroid-XU4板展示了该方法,该方法具有Exyn22 Exynos。