Coffee: COmpiler Framework for Energy-Aware Exploration
Coffee: COmpiler Framework for Energy-Aware Exploration
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Coffee：用于能源感知探索的 COpiler 框架
DOI：
10.1007/978-3-540-77560-7_14
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
D. Verkest
中科院分区：
文献类型：
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作者：
P. Raghavan;A. Lambrechts;J. Absar;M. Jayapala;F. Catthoor;D. Verkest
现代移动的设备需要非常节能。由于这些设备的日益复杂，能量感知设计探索变得越来越重要。当前的勘探工具通常不支持能量估计，或者在估计成为可能之前需要非常详细的设计。在设计的所有阶段和更高的抽象级别上获得有关性能和能耗的早期反馈非常重要。本文提出了一个统一的优化和探索框架，从源代码级转换到处理器架构设计。所提出的可重定向编译器和模拟器框架可以将应用程序映射到一系列处理器和内存配置，模拟并报告详细的性能和能量估计。介绍了一种精确的能量建模方法，该方法可以在组件级估计处理器和存储器的能量消耗，有助于指导设计过程。使用示例处理器来说明快速能量感知架构探索。使用两个国家的最先进的处理器和处理器上的先进的低功耗扩展存储器的代表性无线基准的流程进行了演示。该框架还支持各种新颖的低功耗扩展及其组合的探索。我们表明，一个统一的框架，使快速反馈的应用程序代码的源代码级转换的最终周期计数和能源消耗的影响。
Modern mobile devices need to be extremely energy efficient. Due to the growing complexity of these devices, energy aware design exploration has become increasingly important. Current exploration tools often do not support energy estimation, or require the design to be very detailed before the estimate is possible. It is important to get early feedback on both performance and energy consumption during all phases of the design and at higher abstraction levels. This paper presents a unified optimization and exploration framework, from source level transformation to processor architecture design. The proposed retargetable compiler and simulator framework can map applications to a range of processors and memory configurations, simulate and report detailed performance and energy estimates. An accurate energy modeling approach is introduced, which can estimate the energy consumption of processor and memories at a component level, which can help to guide the design process. Fast energy-aware architecture exploration is illustrated using an example processor. The flow is demonstrated using a representative wireless benchmark on two state of the art processors and on a processor with advanced low power extensions for memories. The framework also supports exploration of various novel low power extensions and their combinations. We show that a unified framework enables fast feedback on the effect of source level transformations of the application code on the final cycle count and energy consumption.