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Application of Thread-Level Parallel Programming to Thermohydrodynamic Lubrication Computation

机译:线程级并行编程在热流体动力润滑计算中的应用

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摘要

This study presents a performance evaluation of a portable parallel programming paradigm, the OpenMP, for thermohydrodynamic (THD) lubrication analysis. The THD model is described by two coupled partial differential equations, a simplified generalized Reynolds equation and a 3-D time-dependent energy equation. The numerical methods used for solving these equations are coded and compiled as a multithread application to minimize execution time in a dual-CPU workstation. It was found that the program coded in thread-level parallelism can effectively use the computing resources in the current setup. The attributes of conditional compilation and incremental parallelization of OpenMP make it a powerful tool for fine-grain applications in shared-memory platforms. A program coded in thread-level parallelism should understand the caching operation to fully exploit the capacity of coming dual- or multi-core desktop CPUs in either uniprocessor or multiprocessor systems. As illustrated in this study, some of the parallel programming techniques used in solving the Reynolds equation and the thermal energy equation can facilitate applications using similar lubrication models.
机译:这项研究提出了对热流体动力学(THD)润滑分析的便携式并行编程范例OpenMP的性能评估。 THD模型由两个耦合的偏微分方程,一个简化的广义雷诺方程和一个与3D时间相关的能量方程来描述。用于求解这些方程的数值方法被编码并编译为多线程应用程序,以最大程度地减少双CPU工作站中的执行时间。发现以线程级并行性编码的程序可以有效地使用当前设置中的计算资源。 OpenMP的条件编译和增量并行化的属性使其成为共享内存平台中细粒度应用程序的强大工具。以线程级并行性编码的程序应了解缓存操作,以充分利用单处理器或多处理器系统中即将出现的双核或多核台式机CPU的容量。如本研究所示,用于解决雷诺方程和热能方程的一些并行编程技术可以促进使用类似润滑模型的应用。

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