Performance Analysis and Optimization of the OP2 Framework on Many-Core Architectures
Performance Analysis and Optimization of the OP2 Framework on Many-Core Architectures
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OP2框架在众核架构上的性能分析与优化
DOI：
10.1093/comjnl/bxr062
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Giles M
中科院分区：
文献类型：
--
作者：
Giles M
本文介绍了OP2“活动”库的基准测试、性能分析和优化研究，该库为并行执行非结构化网格应用程序提供了一个抽象框架。OP2旨在将应用程序的科学规范与其并行实现解耦，从而通过将应用程序重新定位到不同的多核/多核硬件上执行来实现代码寿命和近乎最佳的性能。在各种多核处理器系统上展示了具有代表性的非结构化网格应用程序的运行时性能结果，包括英特尔的传统X86架构（基于较老的Penryn和当前的Nehalem微架构的Xeon）和NVIDIA的GPU产品（GTX260, Tesla C2050）。我们的分析展示了使用CPU （OpenMP）和GPU （CUDA）并行实现解决由大约150万个边组成的工业大小的非结构化网格之间的对比性能。结果显示了选择正确的分区和线程块配置的重要性，限制GPU性能的因素以及对提高性能的优化的见解。
This paper presents a benchmarking, performance analysis and optimization study of the OP2 ‘active’ library, which provides an abstraction framework for the parallel execution of unstructured mesh applications. OP2 aims to decouple the scientific specification of the application from its parallel implementation, and thereby achieve code longevity and near-optimal performance through re-targeting the application to execute on different multi-core/many-core hardware. Runtime performance results are presented for a representative unstructured mesh application on a variety of many-core processor systems, including traditional X86 architectures from Intel (Xeon based on the older Penryn and current Nehalem micro-architectures) and GPU offerings from NVIDIA (GTX260, Tesla C2050). Our analysis demonstrates the contrasting performance between the use of CPU (OpenMP) and GPU (CUDA) parallel implementations for the solution of an industrial-sized unstructured mesh consisting of about 1.5million edges. Results show the significance of choosing the correct partition and thread-block configuration, the factors limiting the GPU performance and insights into optimizations for improved performance.
流动不稳定性对涡轮机械气动弹性线性分析的影响
影响因子：
1.9
作者：
M. Campobasso;Michael B. Giles
通讯作者：
Michael B. Giles
非结构化网格求解器的并行框架
DOI：
10.1007/978-3-0348-8534-8_10
发表时间：
1994
期刊：
2012 IEEE 18th International Conference on Parallel and Distributed Systems
影响因子：
--
作者：
D. A. Burgess;P. Crumpton;M. Giles
通讯作者：
M. Giles