Exploring Target Function Approximation for Stochastic Circuit Minimization
Exploring Target Function Approximation for Stochastic Circuit Minimization
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DOI：
10.1145/3400302.3415701
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Chen Wang;Weihua Xiao;J. Hayes;Weikang Qian
中科院分区：
文献类型：
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作者：
Chen Wang;Weihua Xiao;J. Hayes;Weikang Qian
随机计算（SC）是一种新兴的电路设计范式，可以用简单的电路来完成复杂的计算。虽然SC电路具有较小的面积和关键路径延迟，但由于需要许多时钟周期来执行计算，因此它们具有较大的整体延迟和能量消耗。这个问题的一个解决方案是进一步最小化电路。在这项工作中，我们探索目标函数近似推导出SC电路，显着减少面积和延迟。我们提出了两种静态方法，首先构建一组功能接近给定的目标函数，然后选择最好的合成SC电路实现这些功能之一。我们还提出了一个有效的动态方法，同时搜索最佳近似的目标函数和相应的最小化SC电路。实验结果表明，平均而言，我们的动态方法显着减少了面积，关键路径延迟，面积延迟产品的SC电路的80%，59%，和91%，分别超过最先进的麦克劳林多项式为基础的方法为2%的给定误差范围。我们的方法的代码是开源的。
Stochastic computing (SC) is an emerging paradigm for designing circuits to perform complicated computation with simple circuitry. Although SC circuits have small area and critical-path delay, due to the need of many clock cycles to perform computation, they have a large overall latency and energy consumption. One solution to this problem is to further minimize the circuits. In this work, we explore target function approximation to derive an SC circuit with significantly reduced area and delay. We propose two static methods that first construct a set of functions close to the given target function and then select the best synthesized SC circuit realizing one of these functions. We also propose an efficient dynamic method that simultaneously searches for the best approximated target function and the corresponding minimized SC circuit. The experimental results show that on average, our dynamic method dramatically reduces the area, critical-path delay, and area-delay product of the SC circuits by 80%, 59%, and 91 %, respectively, over the state-of-the-art Maclaurin polynomial-based method for a given error bound of 2%. The code of our methods is made open-source.