LSOracle: a Logic Synthesis Framework Driven by Artificial Intelligence: Invited Paper

LSOracle: a Logic Synthesis Framework Driven by Artificial Intelligence: Invited Paper
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DOI:
10.1109/iccad45719.2019.8942145
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发表时间:
2019-11
期刊:
2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
影响因子:
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通讯作者:
Walter Lau Neto;Max Austin;Scott Temple;L. Amarù;Xifan Tang;P. Gaillardon
Walter Lau Neto;Max Austin;Scott Temple;L. Amarù;Xifan Tang;P. Gaillardon
中科院分区:
其他
文献类型:
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作者:
Walter Lau Neto;Max Austin;Scott Temple;L. Amarù;Xifan Tang;P. Gaillardon

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现代集成电路(IC)的复杂性日益增加,导致系统由各种不同的知识产权(IP)块组成,称为片上系统(SoC)。这种复杂性需要工程师的强大专业知识,依赖于广泛的商业EDA工具。为了克服这种限制,需要一个自动化的开源逻辑综合流程。在这种情况下,这项工作提出了LSAracle:一种新的自动化混合逻辑综合框架。LSAracle是第一个利用最先进的与反相图(AIG)和多数反相图(MATRITY-INVERTER GRAPH)逻辑优化器的公司,并依赖于深度神经网络(DNN)来自动决定哪个优化器应该处理电路的不同部分。为此,LSOracle应用$k-way$分区将DAG拆分为多个分区,并使用选择最适合的优化器。针对一组混合逻辑电路的7 nm ASAP标准单元库的后技术映射ASIC结果显示,与AIG和ASIC相比,面积延迟积的平均改善分别为6.87%(高达10.26%)和2.70%(高达6.27%)。此外,我们表明,对于所考虑的电路,LSOracle实现了一个区域接近AIG(提供更小的电路)与MIG,提供更快的电路的类似性能。
The increasing complexity of modern Integrated Circuits (ICs) leads to systems composed of various different Intellectual Property (IPs) blocks, known as System-on-Chip (SoC). Such complexity requires strong expertise from engineers, that rely on expansive commercial EDA tools. To overcome such a limitation, an automated open-source logic synthesis flow is required. In this context, this work proposes LSOracle: a novel automated mixed logic synthesis framework. LSOracle is the first to exploit state-of-the-art And-Inverter Graph (AIG) and Majority-Inverter Graph (MIG) logic optimizers and relies on a Deep Neural Network (DNN) to automatically decide which optimizer should handle different portions of the circuit. To do so, LSOracle applies $k-way$ partitioning to split a DAG into multiple partitions and uses a to chose the best-fit optimizer. Post-tech mapping ASIC results, targeting the 7nm ASAP standard cell library, for a set of mixed-logic circuits, show an average improvement in area-delay product of 6.87% (up to 10.26%) and 2.70% (up to 6.27%) when compared to AIG and MIG, respectively. In addition, we show that for the considered circuits, LSOracle achieves an area close to AIGs (which delivered smaller circuits) with a similar performance of MIGs, which delivered faster circuits.