基于RRAM的多目标BDD优化电路设计

S. Shirinzadeh, Mathias Soeken, R. Drechsler
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引用次数: 15

摘要

电阻性开关特性使得非易失性存储计算器件的设计等各种有前景的应用受到了人们的高度关注。在这项工作中,我们提出了一种基于RRAM的逻辑电路设计的多目标BDD优化方法。与经典的BDD优化不同,在这种情况下,评估电路的成本指标不仅取决于BDD节点的数量,而且更高级。我们利用非支配排序遗传算法进行双目标BDD优化,涉及所需rram的数量和计算步骤,分别解决所得到电路的面积和延迟。该算法还允许优先考虑一个目标,如果它是更重要的。实验结果表明,与现有的多目标遗传算法相比,本文提出的多目标遗传算法在上述两个指标上都有较大的降低。
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Multi-objective BDD optimization for RRAM based circuit design
Resistive switching property enables various promising applications such as design of non-volatile in-memory computing devices which has attracted high attention to Resistive Random Access Memories (RRAMs). In this work, we present a multi-objective BDD optimization approach for RRAM based logic circuit design. Dissimilar to classical BDD optimization, evaluating the cost metrics of the circuits in this case does not only depend on the number of BDD nodes but is more advanced. We have utilized a non-dominated sorting genetic algorithm for bi-objective BDD optimization with respect to the number of required RRAMs and computational steps addressing the area and delay of the resulting circuits, respectively. The algorithm also allows preference to one of the objectives if it is of higher significance. Experimental results show that the proposed multi-objective genetic algorithm achieves considerable reduction in both aforementioned criteria in comparison with an existing approach.
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