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An efficient computation of minimal correction subformulas for SAT-based ATPG of digital circuits

机译:数字电路基于SAT的ATPG的最小校正子公式的有效计算

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Lately, research has been focused on the problem of extracting the main unsatisfiable cores from infeasible constraints. The main reasons of infeasibility can be represented by subsets of unsatisfied clauses referred to “Minimal Correction Subsets”. Various developed algorithms for computing MCSes can be used for fault detection technique which is considered a core of SAT-based Automatic Test Pattern Generation (ATPG) on digital VLSI circuits. This paper presents an efficient CPU-GPU algorithm for extracting the complete MCSes that can be optimized on NVIDIA General Purpose Graphics Processing Unit paradigm which is considered one of the most common platforms for GPU parallel computing. Our proposed algorithm is evaluated using a C++ algorithm for generating and reducing a SAT instance of VLSI digital circuits from ISCAS'85, ISCAS'89 and synthetic benchmarks. The proposed algorithm, utilizing our presented parallel SAT-solver, delivers about 1.4x speedup compared to the CUDA@SAT tool.
机译:最近,研究集中在从不可行的约束中提取主要无法满足的核心问题。不可行的主要原因可以由不满意的条款的子集来表示,这些条款被称为“最小校正子集”。各种用于计算MCSes的已开发算法都可以用于故障检测技术,该技术被认为是数字VLSI电路上基于SAT的自动测试模式生成(ATPG)的核心。本文提出了一种用于提取完整MCS的高效CPU-GPU算法,该算法可以在NVIDIA通用图形处理单元范例中进行优化,该范例被认为是GPU并行计算最常见的平台之一。我们使用C ++算法评估了我们提出的算法,该算法用于根据ISCAS'85,ISCAS'89和综合基准来生成和减少VLSI数字电路的SAT实例。与CUDA @ SAT工具相比,利用我们提出的并行SAT求解器提出的算法可将速度提高约1.4倍。

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