Synthesis of power-optimized and area-optimized circuits from hierarchical behavioral descriptions

G. Lakshminarayana, N. Jha
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引用次数: 4

Abstract

We present a technique for synthesizing power- as well as area-optimized circuits from hierarchical data flow graphs under throughput constraints. We allow for the use of complex RTL modules, such as FFTs and filters, as building blocks for the RTL circuit, in addition to simple RTL modules such as adders and multipliers. Unlike past techniques in the area, we also customize the complex RTL modules to match the environment in which they find themselves. We present a fast and efficient algorithm for mapping multiple behaviors onto the same RTL module during the course of synthesis, thus allowing our synthesis system to explore previously unexplored regions of the design space. These techniques are at the core of an iterative improvement based approach which can accept temporary degradation in solution quality in its quest for a globally optimal solution. The moves in our iterative improvement procedure explore optimizations along different dimensions such as functional unit selection, resource allocation, resource sharing, resource splitting, and selection and resynthesis of complex RTL modules. These inter-related optimizations are dynamically traded off with each other during the course of synthesis, thus exploiting the benefits that arise from their interaction. The synthesis framework also tackles other related high-level synthesis tasks such as scheduling, clock selection, and V/sub dd/ selection. Experimental results demonstrate that our algorithm produces circuits whose area and power consumption are comparable to or better than those produced using flattened synthesis, within much shorter CPU times. The efficacy of our algorithm in the power-optimization mode is illustrated by the fact that it produces circuits that consume up to 6.7 times less power than area-optimized circuits working at 5 Volts at area overheads not exceeding 50%.
基于分层行为描述的功率优化和面积优化电路的综合
我们提出了一种在吞吐量约束下从分层数据流图合成功率和面积优化电路的技术。除了简单的RTL模块(如加法器和乘法器)外,我们还允许使用复杂的RTL模块(如fft和滤波器)作为RTL电路的构建块。与该领域过去的技术不同,我们还定制了复杂的RTL模块,以匹配它们所处的环境。我们提出了一种快速有效的算法,用于在合成过程中将多个行为映射到相同的RTL模块上,从而使我们的合成系统能够探索设计空间中以前未探索的区域。这些技术是基于迭代改进的方法的核心,该方法在寻求全局最优解的过程中可以接受解决方案质量的暂时下降。探索优化迭代改进过程中的移动沿着不同维度等功能单元选择、资源分配、资源共享、资源分割,并选择和再合成复杂的RTL模块。在合成过程中,这些相互关联的优化会动态地相互权衡,从而利用它们相互作用带来的好处。合成框架还处理其他相关的高级合成任务,如调度、时钟选择和V/sub / dd/选择。实验结果表明,我们的算法在更短的CPU时间内产生的电路的面积和功耗与使用扁平合成产生的电路相当或更好。我们的算法在功率优化模式下的有效性可以通过以下事实来说明:在面积开销不超过50%的情况下,它产生的电路比在5伏特下工作的面积优化电路消耗的功率少6.7倍。
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