竞争条件和数据分区:常见错误给可重复并行模拟带来的风险

IF 1.3 4区 工程技术 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Simulation-Transactions of the Society for Modeling and Simulation International Pub Date : 2022-11-19 DOI:10.1177/00375497221132566
J. Nutaro, Ozgur Ozmen
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引用次数: 1

摘要

当20世纪70年代引入并行仿真算法时,它们的发展和使用只引起了并行计算专家的兴趣。随着多核处理器的普及,这种情况发生了变化,每个建模者都拥有一台并行计算机。一个自然的结果是,不熟悉并行计算的人对并行模拟越来越感兴趣。与此同时,并行仿真工具继续开发,隐含的假设是建模者对并行编程很了解。意想不到的后果是并行仿真工具的用户数量迅速增加,他们不太可能认识到竞争条件、分区策略和仿真模型中的同步动作的相互作用使结果不可重复,从而使从仿真数据中得出的结论的有效性受到质疑。我们通过使用现有并行仿真工具构建的示例模型说明了将并行算法暴露给非并行计算专家的用户的潜在危险。通过这样做,我们希望让工具开发人员重新关注可用性,即使这种新的关注会导致一些性能的损失。
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Race conditions and data partitioning: risks posed by common errors to reproducible parallel simulations
When parallel algorithms for simulation were introduced in the 1970s, their development and use interested only experts in parallel computation. This circumstance changed as multi-core processors became commonplace, putting a parallel computer into the hands of every modeler. A natural outcome is growing interest in parallel simulation among persons not intimately familiar with parallel computing. At the same time, parallel simulation tools continue to be developed with the implicit assumption that the modeler is knowledgeable about parallel programming. The unintended consequence is a rapidly growing number of users of parallel simulation tools that are unlikely to recognize when the interaction of race conditions, partitioning strategies, and simultaneous action in their simulation models make results non-reproducible, thereby calling into question the validity of conclusions drawn from the simulation data. We illustrate the potential dangers of exposing parallel algorithms to users who are not experts in parallel computation with example models constructed using existing parallel simulation tools. By doing so, we hope to refocus tool developers on usability, even if this new focus incurs loss of some performance.
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来源期刊
CiteScore
3.50
自引率
31.20%
发文量
60
审稿时长
3 months
期刊介绍: SIMULATION is a peer-reviewed journal, which covers subjects including the modelling and simulation of: computer networking and communications, high performance computers, real-time systems, mobile and intelligent agents, simulation software, and language design, system engineering and design, aerospace, traffic systems, microelectronics, robotics, mechatronics, and air traffic and chemistry, physics, biology, medicine, biomedicine, sociology, and cognition.
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