MPI+X has been the de facto standard for distributed memory parallel programming. It is widely used primarily as an explicit two-sided communication model, which often leads to complex and error-prone code. Alternatively, PGAS model utilizes efficient one-sided communication and more intuitive communication primitives. In this paper, we present a novel approach that integrates PGAS concepts into the OpenMP programming model, leveraging the LLVM compiler infrastructure and the GASNet-EX communication library. Our model addresses the complexity associated with traditional MPI+OpenMP programming models while ensuring excellent performance and scalability. We evaluate our approach using a set of micro-benchmarks and application kernels on two distinct platforms: Ookami from Stony Brook University and NERSC Perlmutter. The results demonstrate that DiOMP achieves superior bandwidth and lower latency compared to MPI+OpenMP, up to 25% higher bandwidth and down to 45% on latency. DiOMP offers a promising alternative to the traditional MPI+OpenMP hybrid programming model, towards providing a more productive and efficient way to develop high-performance parallel applications for distributed memory systems.
Achieving Efficient Strong Scaling with PETSc using Hybrid MPI/OpenMP Optimisation
在现代高性能平台中,处理元件数量的增加和存储器与核心比率的降低使得高效的强缩放成为数值算法的关键要求。为了在大规模并行系统上实现有效的可扩展性,科学软件必须在整个堆栈上发展,以利用现代体系结构中暴露的多级并行性。在本文中,我们演示了使用混合MPI/OpenMP并行优化并行稀疏矩阵向量乘法在PETSc,广泛使用的科学图书馆的可扩展的偏微分方程的解决方案。使用Fluidity生成的大矩阵,一个开源的CFD应用程序代码,使用PETSc作为其线性求解器引擎,我们使用基于任务的并行性显式通信重叠的效果进行评估,并展示如何进一步提高性能显式负载均衡线程在MPI进程。我们展示了显着的加速比纯MPI模式和有效的强大的缩放稀疏矩阵向量乘法富士通PRIMEHPC FX 10和Cray XE 6系统。
The Use of MPI and OpenMP Technologies for Subsequence Similarity Search in Very Large Time Series on Computer Cluster System with Nodes Based on the Intel Xeon Phi Knights Landing Many-core Processor
Distributed Order Recording Techniques for Efficient Record-and-Replay of Multi-threaded Programs
Nanchang Hangkong University(南昌航空大学);Pacific Northwest National Laboratory(太平洋西北国家实验室);RIKEN R-CCS(理化学研究所计算科学研究中心);NVIDIA(英伟达);Lawrence Livermore National Laboratory(劳伦斯利弗莫尔国家实验室);Technical University of Munich(慕尼黑工业大学)
Subdomain Deflation Combined with Local AMG: a Case Study Using AMGCL Library
Kazan Branch of Joint Supercomputer Center, Russian Academy of Sciences(俄罗斯科学院联合超级计算中心喀山分院);Kazan Federal University(喀山联邦大学);Universitat Politècnica de Catalunya (UPC)(加泰罗尼亚理工大学);CIMNE — Centre Internacional de Mètodes Numèrics en Enginyeria(国际数值工程研究中心)