High performance air pollution modeling for a power plant environment

The aim of this work is to provide a high performance air quality simulation using the STEM-II (Sulphur Transport Eulerian Model 2) program, a large-scale pollution modeling application. First, we optimize the sequential program with the aim of increasing data locality. Then, we parallelized the program using OpenMP directives for shared memory systems, and the MPI library for distributed memory machines. Performance results are presented for a SGI O2000 multiprocessor, a Fujitsu AP3000 multicomputer and a Cluster of PCs. Experimental results show that the parallel versions of the code achieve important reductions in the CPU time needed by each simulation. This will allow us to obtain results with adequate speed and reliability for the industrial environment where it is intended to be applied.     

OpenMDSP: Extending OpenMP to Program Multi-Core DSPs

Abstract Multi-core digital signal processors （DSPs） are widely used in wireless telecommunication, core network transcoding, industrial control, and audio/video processing technologies, among others. In comparison with general-purpose multi-processors, multi-core DSPs normally have a more complex memory hierarchy, such as on-chip core-local memory and non-cache-coherent shared memory. As a result, efficient multi-core DSP applications are very difficult to write. The current approach used to program multi-core DSPs is based on proprietary vendor software development kits （SDKs）, which only provide low-level, non-portable primitives. While it is acceptable to write coarse-grained task-level parallel code with these SDKs, writing fine-grained data parallel code with SDKs is a very tedious and error-prone approach. We believe that it is desirable to possess a high-level and portable parallel programming model for multi-core DSPs. In this paper, we propose OpenMDSP, an extension of OpenMP designed for multi-core DSPs. The goal of OpenMDSP is to fill the gap between the OpenMP memory model and the memory hierarchy of multi-core DSPs. We propose three classes of directives in OpenMDSP, including 1） data placement directives that allow programmers to control the placement of global variables conveniently, 2） distributed array directives that divide a whole array into sections and promote the sections into core-local memory to improve performance, and 3） stream access directives that promote big arrays into core-local memory section by section during parallel loop processing while hiding the latency of data movement by the direct memory access （DMA） of a DSP. We implement the compiler and runtime system for OpenMDSP on PreeScale MSC8156. The benchmarking results show that seven of nine benchmarks achieve a speedup of more than a factor of 5 when using six threads.     

铸造数值模拟超线程并行计算的研究

OpenMP作为共享存储并行编程标准，以其良好的易用性、支持增量并行等优点，成为并行程序设计的主流模型之一。本文主要探讨了铸造数值模拟温度场在重力补缩与非重力补缩条件下的并行计算。实例表明，在支持超线程的硬件环境中，使用OpenMP技术可以取得良好的并行性，大大提高运算效率。     

Performance Evaluation of a Multi-Zone Application in Different OpenMP Approaches

We describe a performance study of a multi-zone application benchmark implemented in several OpenMP approaches that exploit multi-level parallelism and deal with unbalanced workload. The multi-zone application was derived from the well-known NAS Parallel Benchmarks (NPB) suite that involves flow solvers on collections of loosely coupled discretization meshes. Parallel versions of this application have been developed using the Subteam concept and Workqueuing model as extensions to the current OpenMP. We examine the performance impact of these extensions to OpenMP and compare with hybrid and nested OpenMP approaches on several large parallel systems.     

Multi-core CPUs,Clusters, and Grid Computing: A Tutorial

The nature of computing is changing and it poses both challenges and opportunities for economists. Instead of increasing clock speed, future microprocessors will have “multi-cores” with separate execution units. “Threads” or other multi-processing techniques that are rarely used today are required to take full advantage of them. Beyond one machine, it has become easy to harness multiple computers to work in clusters. Besides dedicated clusters, they can be made up of unused lab computers or even your colleagues’ machines. Finally, grids of computers spanning the Internet are now becoming a reality.     

面向神威高性能多核处理器的并行编译优化方法

在神威高性能多核服务器上,自动并行化编译系统为识别和申明程序中的并行性,产生的OpenMP程序没有经过充分的优化,其采用简单的fork-join模型,存在大量的并行循环嵌套,导致运行效率低。为提升自动并行化编译系统产生的OpenMP程序的运行效率,提出一种并行域重构优化技术。并行域重构技术通过合并程序中的并行域和扩展嵌套循环中的并行域范围,减少OpenMP程序的并行域数目,降低线程组频繁创建和合并等控制开销,将简单fork-join模型的OpenMP程序转换为性能更为高效的单程序多数据模型的OpenMP程序。实验结果表明,在新一代神威高性能多核服务器SW1621平台上,并行域重构技术在NPB3.3-OMP测试集和SPEC OMP2012测试集上的运行效率分别提高了10.77%和7.94%的,可有效提升自动并行化编译系统OpenMP程序的执行效率。     

多核环境下的图像分割并行算法研究

对多核环境下的图像分割并行算法进行研究,在基于正交小波分解的多分辨率图像锥中引入模糊C-均值(FCM)算法,采用OpenMP语言设计P-FCM多核并行模型,并给出该模型的算法实现步骤。在对初始图像数据预处理时,采用矩形块数据分割法进行图像分块,将分块后的子图像数据作为并行运算时的输入数据由主线程分给不同的处理器。实验结果表明,在处理较大图像时,该算法效率较高。     

OpenMP compiler for distributed memory architectures

OpenMP is an emerging industry standard for shared memory architectures. While OpenMP has advantages on its ease of use and incremental programming, message passing is today still the most widely-used programming model for distributed memory architectures. How to effectively extend OpenMP to distributed memory architectures has been a hot spot. This paper proposes an OpenMP system, called KLCoMP, for distributed memory architectures. Based on the partially replicating shared arrays memory model, we propose ...     

一种基于蚁群算法的生物序列并行比对方法

生物序列比对是生物信息领域的重要课题,比对结果的合理性和正确性关系到基于比对结果研究的正确性。在保证正确性的前提下利用并行计算充分挖掘计算潜力对提高比对效率有重要意义。针对双序列的全局比对问题,提出了基于蚁群算法的双序列比对并行化方案。对耗时最多的搜索比对路径和信息素更新两个步骤给出了基于共享内存模型的并行化方法。"天河二号"上OpenMP实验结果表明,8线程并行情况下,加速比可达5.03,且序列越长性能越高。     

多色SSOR-PCG的MPI+OpenMP混合编程实现

针对对称逐步超松驰预处理共轭梯度（Symmetric Successive Over Relaxation Preconditioned Conjugate Gradient,SSOR-PCG）法并行化时每步迭代都要并行求解2个三角方程组的困难,采用多色排序技术提高并行度,基于MPI＋OpenMP混合编程模型开发适合于分布共享内存计算机的并行程序,通过测试选择有效的MPI通信函数,并给出3种避免共享数据竞争的措施,供不同规模问题和不同内存容量计算机情况选用．