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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Reliability and Energy-Aware Mapping and Scheduling of Multimedia Applications on Multiprocessor Systems
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Reliability and Energy-Aware Mapping and Scheduling of Multimedia Applications on Multiprocessor Systems

机译：多处理器系统上多媒体应用程序的可靠性和能量感知映射与调度

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摘要

Lifetime reliability is an emerging concern in multiprocessor systems as escalating power density and hence temperature variation continues to accelerate wear-out leading to a growing prominence of device defects. In this paper, we propose a system-level approach that involves performance-aware mapping of multimedia applications on a multiprocessor system to jointly minimize energy consumption and temperature related wear-out. Fundamental to this approach is a simplified temperature model that incorporates not only the transient and the steady-state behavior (temporal effect), but also the temperature dependency on the surrounding cores (spatial effect). This model is validated against the temperature obtained using the tool with transient and steady-state simulations, and is shown to be accurate within 5.5°C, leading to an MTTF estimation accuracy of an average 21 percent with respect to the state-of-the-art approaches. The proposed temperature model is integrated in a gradient-based fast heuristic that controls the voltage and frequency of the cores to limit the average and peak temperature leading to a longer lifetime, simultaneously minimizing the energy consumption. Lifetime computation considers task remapping, which is a common feature available in modern multiprocessor systems. A linear programming approach is then proposed to distribute the cores of a multiprocessor system among concurrent applications to maximize the lifetime. Experiments conducted with a set of synthetic and real-life applications represented as synchronous data flow graphs demonstrate that the proposed approach minimizes energy consumption by an average 24 percent with 47 percent increase in lifetime. For concurrent applications, the proposed lifetime-aware core distribution results in an average 10 percent improvement in lifetime as compared to performance-based core distribution.
机译：随着功率密度的不断提高，终身可靠性已成为多处理器系统中日益关注的问题，因此温度变化继续加速磨损，从而导致器件缺陷日益突出。在本文中，我们提出了一种系统级方法，该方法涉及在多处理器系统上多媒体应用程序的性能感知映射，以共同最小化能耗和与温度相关的损耗。这种方法的基础是简化的温度模型，该模型不仅包含瞬态和稳态行为（时间效应），而且还包括对周围磁芯的温度依赖性（空间效应）。该模型针对使用该工具通过瞬态和稳态仿真获得的温度进行了验证，结果表明在5.5°C内是准确的，相对于当前状态，MTTF估算精度平均为21％先进的方法。拟议的温度模型集成在基于梯度的快速启发式算法中，该算法可控制磁芯的电压和频率，以限制平均温度和峰值温度，从而延长使用寿命，同时将能耗降至最低。终生计算考虑了任务重映射，这是现代多处理器系统中可用的常见功能。然后提出了一种线性编程方法，以在并发应用程序之间分配多处理器系统的内核，以最大化其寿命。用一组以同步数据流图表示的合成和现实应用程序进行的实验表明，该方法平均将能耗降低了24％，使用寿命增加了47％。对于并发应用程序，与基于性能的核心分发相比，建议的基于生命周期的核心分发可将生存期平均提高10％。

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