The energy band memory server algorithm for parallel Monte Carlo transport calculations

被引：2

作者：

Felker, Kyle G. ^{[1
]}

Siegel, Andrew R. ^{[1
,2
]}

Smith, Kord S. ^{[3
]}

Romano, Paul K. ^{[3
]}

Forget, Benoit ^{[3
]}

机构：

[1] Argonne Natl Lab, MCS Div, 9700 S Cass Ave,Bldg 240, Argonne, IL 60439 USA

[2] Argonne Natl Lab, NE Div, 9700 S Cass Ave,Bldg 240, Argonne, IL 60439 USA

[3] MIT, Dept NSE, 77 Massachusetts Ave, Cambridge, MA 02139 USA

来源：

SNA + MC 2013 - JOINT INTERNATIONAL CONFERENCE ON SUPERCOMPUTING IN NUCLEAR APPLICATIONS + MONTE CARLO | 2014年

关键词：

Monte Carlo; memory server; cross section; energy band;

D O I：

10.1051/snamc/201404207

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

An algorithm is developed to significantly reduce the on-node footprint of cross section memory in Monte Carlo particle tracking algorithms. The classic method of per-node replication of cross section data is replaced by a memory server model, in which the read-only lookup tables reside on a remote set of disjoint processors. The main particle tracking algorithm is then modified in such a way as to enable efficient use of the remotely stored data in the particle tracking algorithm. Results of a prototype code on a Blue Gene/Q installation reveal that the penalty for remote storage is reasonable in the context of time scales for real-world applications, thus yielding a path forward for a broad range of applications that are memory bound using current techniques.

引用

页数：7

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