A new massively parallel version of CRYSTAL for large systems on high performance computing architectures

被引:38
|
作者
Orlando, Roberto [1 ,2 ]
Delle Piane, Massimo [1 ,2 ]
Bush, Ian J. [3 ]
Ugliengo, Piero [1 ,2 ]
Ferrabone, Matteo [1 ,2 ]
Dovesi, Roberto [1 ,2 ]
机构
[1] Univ Turin, Dept Chem, I-10125 Turin, Italy
[2] Ctr Excellence, I-10125 Turin, Italy
[3] NAG, Oxford OX2 8DR, England
关键词
HPC; DFT; B3LYP; MCM-41; massive parallel; CRYSTAL; AB-INITIO; DENSITY; SIMULATION; MCM-41;
D O I
10.1002/jcc.23072
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Fully ab initio treatment of complex solid systems needs computational software which is able to efficiently take advantage of the growing power of high performance computing (HPC) architectures. Recent improvements in CRYSTAL, a periodic ab initio code that uses a Gaussian basis set, allows treatment of very large unit cells for crystalline systems on HPC architectures with high parallel efficiency in terms of running time and memory requirements. The latter is a crucial point, due to the trend toward architectures relying on a very high number of cores with associated relatively low memory availability. An exhaustive performance analysis shows that density functional calculations, based on a hybrid functional, of low-symmetry systems containing up to 100,000 atomic orbitals and 8000 atoms are feasible on the most advanced HPC architectures available to European researchers today, using thousands of processors. (c) 2012 Wiley Periodicals, Inc.
引用
收藏
页码:2276 / 2284
页数:9
相关论文
共 50 条
  • [41] Large-scale powder mixer simulations using massively parallel GPU architectures
    Radeke, Charles A.
    Glasser, Benjamin J.
    Khinast, Johannes G.
    CHEMICAL ENGINEERING SCIENCE, 2010, 65 (24) : 6435 - 6442
  • [42] Massively parallel computing with coupled algorithm for introduction of large-eddy simulation
    Arakawa, C
    Saito, K
    Shimano, K
    COMPUTATIONAL FLUID DYNAMICS 2000, 2001, : 399 - 404
  • [43] Massively Parallel Algorithms for Computing TIN DEMs and Contour Trees for Large Terrains
    Nath, Abhinandan
    Fox, Kyle
    Agarwal, Pankaj K.
    Munagala, Kamesh
    24TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2016), 2016,
  • [44] Massively parallel computing at the Large Hadron Collider up to the HL-LHC
    Lujan, P.
    Halyo, V.
    JOURNAL OF INSTRUMENTATION, 2015, 10
  • [45] Massively Parallel Simulation of Large-Scale Electromagnetic Problems Using One High-Performance Computing Scheme and Domain Decomposition Method
    Wang, Wei-Jie
    Xu, Ran
    Li, Han-Yu
    Liu, Yang
    Guo, Xing-Yue
    Xu, Yong
    Li, Hai-Long
    Zhou, Hai-Jing
    Yin, Wen-Yan
    IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 2017, 59 (05) : 1523 - 1531
  • [46] High performance computing and simulation: architectures, systems, algorithms, technologies, services, and applications
    Smari, Waleed W.
    Fiore, Sandro
    Hill, David
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2013, 25 (10): : 1313 - 1318
  • [47] Photonic Network-on-Chip (NoC) Architectures for the High Performance Computing Systems
    Sarkar, Sayani
    Pal, Shantanu
    PROCEEDINGS OF 2018 IEEE APPLIED SIGNAL PROCESSING CONFERENCE (ASPCON), 2018, : 198 - 203
  • [48] Viable architectures for high-performance computing
    Ziavras, SG
    Wang, Q
    Papathanasiou, P
    COMPUTER JOURNAL, 2003, 46 (01): : 36 - 54
  • [49] New trends in programming and execution models for parallel architectures, heterogeneously distributed systems and mobile computing
    Zima, H
    Di Martino, B
    JOURNAL OF SYSTEMS ARCHITECTURE, 1999, 45 (15) : 1259 - 1261
  • [50] Streamlining Offload Computing to High Performance Architectures
    Purcell, Mark
    Callanan, Owen
    Gregg, David
    COMPUTATIONAL SCIENCE - ICCS 2009, PART I, 2009, 5544 : 974 - 983