Parallel And-Inverter Graph Simulation Using a Task-graph Computing System

被引:6
作者
Dzaka, Elmir [1 ]
Lin, Dian-Lun [1 ]
Huang, Tsung-Wei [1 ]
机构
[1] Univ Utah, Dept Elect & Comp Engn, Salt Lake City, UT USA
来源
2023 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, IPDPSW | 2023年
基金
美国国家科学基金会;
关键词
gate-level simulation; and-inverter graph; scalable pipeline; event-driven simulation; Taskflow; CPP-TASKFLOW; OPENTIMER;
D O I
10.1109/IPDPSW59300.2023.00150
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Acquiring significant speedup in gate-level simulation has proven challenging due to limitations such as synchronization and partition overhead. As a result, serial event-driven simulation remains the industry standard despite its slow runtime performance. This paper presents the utilization of Taskflow, a task-graph computing system, to effectively enhance the speedup of gate-level simulation. Taskflow provides solutions to challenges faced in previous attempts at parallelizing gate-level simulation, such as scalable pipelines, conditional tasking, and heterogeneous work stealing. The focus of the paper is on improving speedup within and-inverter graphs, which are used to represent structural implementations of circuits at the gate-level. Experimental results demonstrate significant speedup within and-inverter graph benchmarks.
引用
收藏
页码:923 / 929
页数:7
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