SimPart: A Simple Yet Effective Replication-Aided Partitioning Algorithm for Logic Simulation on GPU

doi:10.1007/978-3-031-99872-0_14

SimPart: A Simple Yet Effective Replication-Aided Partitioning Algorithm for Logic Simulation on GPU

2026-01-01

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DOI：10.1007/978-3-031-99872-0_14

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Replication-aided partitioning (RAP) has recently been introduced to facilitate the design of parallel logic simulation algorithms. By replicating overlapped work, RAP can significantly reduce the cost of inter-thread synchronization. However, the state-of-the-art RAP algorithm, RepCut, relies on time-consuming hypergraph construction and partitioning, where minimizing cut size corresponds to reducing replication. To overcome this runtime challenge, we introduce SimPart, a simple yet highly effective and efficient GPU-parallel replication-aided partitioner. SimPart tackles the partitioning problem directly without solving another proxy problem and proposes a hybrid strategy that can maximally utilize GPU threads for simulation atop our partitions. Compared to RepCut, SimPart achieves an average speedup of 23.x in partitioning and 1.58.x in GPU-parallel simulation, while increasing the original graph size by only 0.3%.

Keywords:

RTL simulation

Graph partitioning

Task graph parallelism

SimPart: A Simple Yet Effective Replication-Aided Partitioning Algorithm for Logic Simulation on GPU

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