面向计算流体力学的图形处理器资源管理

针对求解计算流体力学过程中图形处理器资源利用率低的问题,提出面向计算流体力学的图形处理器资源优化管理方案。基于计算流体力学的算法特性和同时运行任务的执行特点,设计合理的调度方案。通过动态改变不同任务的启动规模和启动时间,在减少资源竞争的同时提高图形处理器资源的有效使用。实验结果表明:本文提出的资源管理方案相比基线方法在不同任务规模下的平均加速比达到 1.64,对图形处理器的硬件资源使用也有了显著的提升。

Graphics processing unit resource management for computational fluid dynamics

Aiming at the problem of low resource utilization of GPU (graphics processing unit) in the process of solving CFD (computational fluid dynamics), a CFD-oriented GPU resource optimization management scheme was proposed. Based on the characterization of the CFD and tasks running concurrently, a reasonable scheduling scheme was designed. By dynamically changing the startup scale and time of different tasks, our method was able to reduce resource competition while improving the effective use of GPU resources. The experimental results show that compared with the baseline method, the average speedup ratio of our proposed resource management scheme reaches 1.64x speedup under different task scales, and the use of GPU hardware resources has also been significantly improved.