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Energy management for battery-powered reconfigurable computing platforms

机译:电池供电的可重构计算平台的能源管理

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We define portable reconfigurable computing platforms as those which have some form of configurable logic coupled with other on-chip or off-chip processing units such as soft processors, embedded processors, and voltage-scalable processors. In the first part of this paper, we present and test a unique methodology where we dynamically change the active area of a field programmable gate array (FPGA) to vary the battery usage and lifetime of the system, by running it on several different taskgraph structures and report an average of 14% and as high as 21%, less battery capacity used, as compared to nonoptimal execution. In the second part of this paper, we integrate the above methodology with more traditional voltage and frequency scaling techniques for portable systems and present a heuristic iterative algorithm for single and multiple processing units. The iterative heuristic algorithm finds a sequence of tasks along with an appropriate design point (implementation option) for each task, such that a deadline is met and the amount of battery energy used is as small as possible. We have used several real-world benchmarks to test the effectiveness of this methodology and we will present the results.
机译:我们将便携式可重配置计算平台定义为具有某种形式的可配置逻辑,并与其他片上或片外处理单元(例如软处理器,嵌入式处理器和电压可扩展处理器)耦合的平台。在本文的第一部分中,我们介绍并测试了一种独特的方法,该方法通过在几种不同的任务图结构上运行它来动态更改现场可编程门阵列(FPGA)的有效区域,以改变系统的电池使用量和寿命。与非最佳执行相比,报告的平均电池使用量要少14%,高达21%。在本文的第二部分,我们将上述方法与便携式系统的更传统的电压和频率缩放技术集成在一起,并提出了针对单个和多个处理单元的启发式迭代算法。迭代启发式算法为每个任务找到任务序列以及适当的设计点(实现选项),这样就可以满足最后期限并且所用电池电量尽可能小。我们已经使用了多个实际基准测试来测试这种方法的有效性,并且我们将介绍结果。

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