用数据驱动的编程模型并行多重网格应用

Parallelizing Multigrid Application Using Data-driven Programming Model

多重网格是数值计算领域中一种加速迭代收敛的重要技术,被广泛应用。近年来,大规模并行计算系统向多核化、异构众核化发展,多重网格应用也亟须适应新的并行计算平台。文中采用一种数据驱动的任务并行语言AceMesh将遗产的NAS MG程序移植到“天河二号”和“神威·太湖之光”两种不同架构的国产超算平台上,展示了使用该语言对计算循环、通信代码的任务并行方法,验证了AceMesh语言的跨平台性能可移植性。文中定性地分析了该应用的任务图特征和计算-通信重叠的特点,并分别在两个并行计算平台上将其与现有编程模型MPI/OpenMP和MPI/OpenACC进行性能对比,分析了AceMesh任务图并行程序对访存性能和通信-计算重叠的优化效果。实验数据表明,相比传统的并行编程方法,AceMesh在“神威·太湖之光”和“天河二号”平台上分别最高获得了1.19X和1.85X的性能加速。最后,针对该应用在不同网格层的通信特点以及通信序列化导致大量通信不能隐藏的问题,提出了未来的研究方向。

Multigrid is an important family of algorithms to accelerate the convergence of iterative solvers for linear systems,and it plays an important role in large-scale scientific computing.At present,distributed-memory systems have evolved to large scale systems based on multi-core nodes or heterogeneous nodes with accelerators.Legacy applications face the urgent need to be ported to modern supercomputers with diverse node-level architectures.In this paper,a data-driven programming language,AceMesh is introduced,and using this directive language,NAS MG is ported to two home-made supercomputers which are Tianhe-2 and Sunway TaihuLight supercomputer.This paper shows how to taskify computation loops and communication-related codes in AceMesh,and analyzes the characteristics on its task graph and on its computation-communication overlapping.Experimental results show that compared with traditional programming models,the AceMesh versions achieve relative speedup up to 1.19X and 1.85X on Sunway TaihuLight and Tianhe-2 respectively.Analyses show that performance improvements come from two main reasons,memory-related optimization and communication overlapping optimization.At last,future directions are put forward to further optimize inter-process communications for the AceMesh version.