密度矩阵重正化群的异构并行优化

密度矩阵重正化群方法（DMRG）在求解一维强关联格点模型的基态时可以获得较高的精度，在应用于二维或准二维问题时，要达到类似的精度通常需要较大的计算量与存储空间.本文提出一种新的DMRG异构并行策略，可以同时发挥计算机中央处理器（CPU）和图形处理器（GPU）的计算性能.针对最耗时的哈密顿量对角化部分，实现了数据的分布式存储，并且给出了CPU和GPU之间的负载平衡策略.以费米Hubbard模型为例，测试了异构并行程序在不同DMRG保留状态数下的运行表现，并给出了相应的性能基准.应用于4腿梯子时，观测到了高温超导中常见的电荷密度条纹，此时保留状态数达到10⁴，使用的GPU显存小于12 GB.     

基于区域分解的CTF全堆子通道热工计算研究

分别用CTF和反应堆蒙卡程序RMC对BEAVRS基准题进行全堆精细建模,由RMC统计径向及轴向功率分布并作为CTF的功率输入。利用CTF的区域分解技术,进行BEAVRS全堆pin by pin子通道计算,采用193个核并行计算,耗时268 s,得到了精细的燃料棒中心及表面温度、冷却剂温度及密度、空泡份额、包壳温度等重要参数,验证了CTF进行全堆子通道计算的高效性及可靠性,为实现基于RMC和CTF的核热耦合计算奠定了重要基础。     

Improvement of parallelization performance of GAMESS: global sum and (semi-)direct integral calculation in multireference perturbation calculation

Performance benchmark tests of the multireference perturbation theory (MRPT2) calculation in the GAMESS suite of programs have been performed on a 128-node PC cluster system. The benchmark results point to two kinds of problems with GAMESS: network delay and slow access to disk files. To overcome these bottlenecks, we employ (semi-)direct atomic orbital integral calculations and a new algorithm for the "global sum" operation. These modifications produce remarkable performance improvements, especially in the 128-node PC cluster system, which was almost twice as fast in our version as in the original version. The modification of "global sum" also improved the performance of other types of molecular orbital calculations in GAMESS, such as density functional theory.     

密度矩阵重正化群的异构并行优化

密度矩阵重正化群方法（DMRG）在求解一维强关联格点模型的基态时可以获得较高的精度，在应用于二维或准二维问题时，要达到类似的精度通常需要较大的计算量与存储空间.本文提出一种新的DMRG异构并行策略，可以同时发挥计算机中央处理器（CPU）和图形处理器（GPU）的计算性能.针对最耗时的哈密顿量对角化部分，实现了数据的分布式存储，并且给出了CPU和GPU之间的负载平衡策略.以费米Hubbard模型为例，测试了异构并行程序在不同DMRG保留状态数下的运行表现，并给出了相应的性能基准.应用于4腿梯子时，观测到了高温超导中常见的电荷密度条纹，此时保留状态数达到10⁴，使用的GPU显存小于12 GB.     

密度矩阵重正化群的异构并行优化

密度矩阵重正化群方法（DMRG）在求解一维强关联格点模型的基态时可以获得较高的精度，在应用于二维或准二维问题时，要达到类似的精度通常需要较大的计算量与存储空间.本文提出一种新的DMRG异构并行策略，可以同时发挥计算机中央处理器（CPU）和图形处理器（GPU）的计算性能.针对最耗时的哈密顿量对角化部分，实现了数据的分布式存储，并且给出了CPU和GPU之间的负载平衡策略.以费米Hubbard模型为例，测试了异构并行程序在不同DMRG保留状态数下的运行表现，并给出了相应的性能基准.应用于4腿梯子时，观测到了高温超导中常见的电荷密度条纹，此时保留状态数达到10⁴，使用的GPU显存小于12 GB.     

Lattice-Boltzmann Simulation of Particle Suspensions in Shear Flow

Inclusion of short-range particle–particle interactions for increased numerical stability in a lattice-Boltzmann code for particle-fluid suspensions, and handling of the particle phase for an effective implementation of the code for parallel computing, are discussed and formulated. In order to better understand the origin of the shear-thickening behavior observed in real suspensions, two simplified cases are considered with the code thus developed. A chain-like cluster of suspended particles is shown to increase the momentum transfer in a shear flow between channel walls, and thereby the effective viscosity of the suspension in comparison with random configurations of particles. A single suspended particle is also shown to increase the effective viscosity under shear flow of this simple suspension for particle Reynolds numbers above unity, due to inertial effects that change the flow configuration around the particle. These mechanisms are expected to carry over to large-scale particle-fluid suspensions.     

Performance of a three‐dimensional unstructured mesh compressible flow solver on NVIDIA Fermi‐class graphics processing unit hardware

We describe the performance of Chicoma , a 3D unstructured mesh compressible flow solver, on graphics processing unit (GPU) hardware. The approach used to deploy the solver on GPU architectures derives from the threaded multicore execution model used in Chicoma , and attempts to improve memory performance via the application of graph theory techniques. The result is a scheme that can be deployed on the GPU with high‐level programming constructs, for example, compiler directives, rather than low‐level programming extensions. With an NVIDIA Fermi‐class GPU (NVIDIA Corp., Sta. Clara, CA, USA) and double precision floating point arithmetic, we observe performance gains of 4–5 × on problem sizes of 10⁶– 10⁷ tetrahedra. We also compare GPU performance to threaded multicore performance with OpenMP and demonstrate hybrid multicore‐GPU calculations with adaptive mesh refinement. Published 2012. This article is a US Government work and is in the public domain in the USA.     

密度矩阵重正化群的异构并行优化

密度矩阵重正化群方法（DMRG）在求解一维强关联格点模型的基态时可以获得较高的精度,在应用于二维或准二维问题时,要达到类似的精度通常需要较大的计算量与存储空间.本文提出一种新的DMRG异构并行策略,可以同时发挥计算机中央处理器（CPU）和图形处理器（GPU）的计算性能.针对最耗时的哈密顿量对角化部分,实现了数据的分布式存储,并且给出了CPU和GPU之间的负载平衡策略.以费米Hubbard模型为例,测试了异构并行程序在不同DMRG保留状态数下的运行表现,并给出了相应的性能基准.应用于4腿梯子时,观测到了高温超导中常见的电荷密度条纹,此时保留状态数达到10⁴,使用的GPU显存小于12 GB.     

闪光X射线照相蒙特卡罗程序的并行化

研究了闪光X射线辐射照像蒙特卡罗程序(FXRMC)在MPI平台下的并行计算实现,给出了实现过程中并行随机数的产生方法。对并行程序的测试结果表明：并行程序与串行程序结果一致,加速比比较理想,呈线性增长,并行效率在16个处理器上可达80%以上。算例的结果说明了并行化可有效地解决程序计算散射技术性能时的耗时问题,从而有效化解FXRMC耗时和大规模计算的困难,提高了FXRMC程序的计算规模和计算速度,达到了研究要求。 (Institute of Fluid Physics, CAEP, P. O. Box 919-105, Mianyang 621900, China)     

Direct Numerical Simulation of a Recirculating, Swirling Flow

A direct numerical simulation (DNS) of a recirculating, swirling flow is performed at a Reynolds number of 5000. Detailed one and two point statistics are presented in this paper. Flow visualization and frequency analysis are used to identify a precessing vortex core and to characterize its position, extent and influence on the flow field. The results are compared with laser Doppler velocimetry (LDV) measurements as well as large eddy simulation (LES) data reported in the literature. The present work constitutes a first step in setting up a DNS data base for complex flows.