Automated synthesis of compact crossbars for sneak-path based in-memory computing
Automated synthesis of compact crossbars for sneak-path based in-memory computing
复制标题
自动合成紧凑交叉开关，用于基于潜行路径的内存计算
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Sumit Kumar Jha
中科院分区：
文献类型：
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作者：
Dwaipayan Chakraborty;Sumit Kumar Jha
数据密集型计算负载的兴起暴露了冯诺依曼架构中的处理器内存瓶颈，并增强了对使用忆阻器等设备进行内存计算的需求。关于使用纳米级忆阻器交叉开关中的潜行路径计算布尔公式的现有文献仅集中于短布尔公式。有两个悬而未决的问题：（i）可以合成基于潜行路径的交叉开关来计算大型布尔公式吗？ (ii) 可以使用潜行路径计算给定布尔公式的忆阻器交叉开关的大小是多少？在本文中，我们在这两个问题上都取得了进展。首先，我们证明计算布尔公式所需的行数和列数最多与表示布尔函数的降序二元决策图的大小成线性关系。其次，我们演示了如何使用布尔决策图来合成纳米级交叉开关，该交叉开关可以使用自然发生的潜行路径计算给定的布尔公式。特别是，我们首次使用基于潜行路径的交叉开关计算来合成大型逻辑电路，例如 128 位加法器。
The rise of data-intensive computational loads has exposed the processor-memory bottleneck in Von Neumann architectures and has reinforced the need for in-memory computing using devices such as memristors. Existing literature on computing Boolean formula using sneak-paths in nanoscale memristor crossbars has only focussed on short Boolean formula. There are two open questions: (i) Can one synthesize sneak-path based crossbars for computing large Boolean formula? (ii) What is the size of a memristor crossbar that can compute a given Boolean formula using sneak paths? In this paper, we make progress on both these problems. First, we show that the number of rows and columns required to compute a Boolean formula is at most linear in the size of the Reduced Ordered Binary Decision Diagram representing the Boolean function. Second, we demonstrate how Boolean Decision Diagrams can be used to synthesize nanoscale crossbars that can compute a given Boolean formula using naturally occurring sneak paths. In particular, we synthesize large logical circuits such as 128-bit adders for the first-time using sneak-path based crossbar computing.