OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis
复制标题
OpenABC-D：用于机器学习引导集成电路合成的大规模数据集
DOI：
--
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
S. Garg
中科院分区：
文献类型：
--
作者：
A. B. Chowdhury;Benjamin Tan;R. Karri;S. Garg
逻辑合成是一个具有挑战性且经过广泛研究的组合优化问题（IC）设计。它将诸如Verilog（Verilog）等编程语言的硬件的高级描述变成了优化的数字电路Netlist，这是一个互连的布尔逻辑门网络，可实现该功能。由于ML在解决其他域中的组合问题和图形问题方面的成功所刺激，对ML引导的逻辑合成工具的设计越来越感兴趣。但是，没有针对此问题域定义的标准数据集或原型学习任务。在这里，我们描述了OpenABC-D，这是一种通过使用领先的开源逻辑合成工具综合开源设计产生的大规模标记的数据集，并说明了其在开发，评估和基准测试ML引导的逻辑合成中的使用。 OpenABC-D的中间输出和最终输出的形式为1500个合成运行中产生的870,000和互换图（AIG）以及优化节点计数和诸如DE-LAY之类的标签。我们在此数据集上定义了一个通用的学习问题，并为其定义了基准测试解决方案。与数据集创建和基准模型相关的代码可用Athttps：//github.com/nyu-mlda/openabc.git。生成的数据集可用athttps：//archive.dyu.edu/handle/2451/63311
Logic synthesis is a challenging and widely-researched combinatorial optimization problem during integrated circuit (IC) design. It transforms a high-level description of hardware in a programming language like Verilog into an optimized digital circuit netlist, a network of interconnected Boolean logic gates, that implements the function. Spurred by the success of ML in solving combinatorial and graph problems in other domains, there is growing interest in the design of ML-guided logic synthesis tools. Yet, there are no standard datasets or prototypical learning tasks defined for this problem domain. Here, we describe OpenABC-D,a large-scale, labeled dataset produced by synthesizing open source designs with a leading open-source logic synthesis tool and illustrate its use in developing, evaluating and benchmarking ML-guided logic synthesis. OpenABC-D has intermediate and final outputs in the form of 870,000 And-Inverter-Graphs (AIGs) produced from 1500 synthesis runs plus labels such as the optimized node counts, and de-lay. We define a generic learning problem on this dataset and benchmark existing solutions for it. The codes related to dataset creation and benchmark models are available athttps://github.com/NYU-MLDA/OpenABC.git. The dataset generated is available athttps://archive.nyu.edu/handle/2451/63311