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  • 37 Topics
    171 Posts

    Whatever works, I guess 😉

  • 6 Topics
    20 Posts

    Hi!

    In a COOP calculation you aim to have a description on the interaction between pairs of orbitals or atoms. In order to do that, you need to indicate each pair you are interested to analyze. In your input, in the first line after the COOP keyword, the initial number 1 indicates that you are interested in one pair of orbitals/atoms. You still need to indicate a pair of orbitals or atoms to be considered, writing them in separated lines. Consider this example, taken from the Tutorials webpage:

    NEWK 6 6 1 0 COOP 1 200 7 14 1 12 0 -1 1 -1 2 END

    Here, the two lines before the final END keyword indicate which atoms will be considered (atoms, given that the lines start with a negative value, as stated in the manual page 322). COOP will be evaluated considering the first and second atoms of the systems (with indices 1 and 2). From your previous calculations you can recover the indices of the atoms/orbitals you are interested.

    Let me know if this information has been useful 🙂

  • Seek assistance, discuss troubleshooting tips for any technical problem you encounter and report bugs

    5 Topics
    31 Posts

    OK, here we go. It just is stuck, always the same position in the output

    (ceres20-compute-46:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95)
    (ceres24-compute-18:96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191)

    export TMPDIR=/local/bgfs/jonas.baltrusaitis/15383115
    export TMOUT=5400
    export SINGULARITY_TMPDIR=/local/bgfs/jonas.baltrusaitis/15383115

    MAX NUMBER OF SCF CYCLES 200 CONVERGENCE ON DELTAP 10**-20
    WEIGHT OF F(I) IN F(I+1) 30% CONVERGENCE ON ENERGY 10**-10
    SHRINK. FACT.(MONKH.) 6 6 6 NUMBER OF K POINTS IN THE IBZ 64
    SHRINKING FACTOR(GILAT NET) 6 NUMBER OF K POINTS(GILAT NET) 64

    *** K POINTS COORDINATES (OBLIQUE COORDINATES IN UNITS OF IS = 6)
    1-R( 0 0 0) 2-C( 1 0 0) 3-C( 2 0 0) 4-R( 3 0 0)
    5-C( 0 1 0) 6-C( 1 1 0) 7-C( 2 1 0) 8-C( 3 1 0)
    9-C( 0 2 0) 10-C( 1 2 0) 11-C( 2 2 0) 12-C( 3 2 0)
    13-R( 0 3 0) 14-C( 1 3 0) 15-C( 2 3 0) 16-R( 3 3 0)
    17-C( 0 0 1) 18-C( 1 0 1) 19-C( 2 0 1) 20-C( 3 0 1)
    21-C( 0 1 1) 22-C( 1 1 1) 23-C( 2 1 1) 24-C( 3 1 1)
    25-C( 0 2 1) 26-C( 1 2 1) 27-C( 2 2 1) 28-C( 3 2 1)
    29-C( 0 3 1) 30-C( 1 3 1) 31-C( 2 3 1) 32-C( 3 3 1)
    33-C( 0 0 2) 34-C( 1 0 2) 35-C( 2 0 2) 36-C( 3 0 2)
    37-C( 0 1 2) 38-C( 1 1 2) 39-C( 2 1 2) 40-C( 3 1 2)
    41-C( 0 2 2) 42-C( 1 2 2) 43-C( 2 2 2) 44-C( 3 2 2)
    45-C( 0 3 2) 46-C( 1 3 2) 47-C( 2 3 2) 48-C( 3 3 2)
    49-R( 0 0 3) 50-C( 1 0 3) 51-C( 2 0 3) 52-R( 3 0 3)
    53-C( 0 1 3) 54-C( 1 1 3) 55-C( 2 1 3) 56-C( 3 1 3)
    57-C( 0 2 3) 58-C( 1 2 3) 59-C( 2 2 3) 60-C( 3 2 3)
    61-R( 0 3 3) 62-C( 1 3 3) 63-C( 2 3 3) 64-R( 3 3 3)

    DIRECT LATTICE VECTORS COMPON. (A.U.) RECIP. LATTICE VECTORS COMPON. (A.U.)
    X Y Z X Y Z
    13.1430453 0.0000000 0.0000000 0.4780616 0.0000000 0.0000000
    0.0000000 11.6066979 0.0000000 0.0000000 0.5413413 0.0000000
    0.0000000 0.0000000 21.1989478 0.0000000 0.0000000 0.2963914

    DISK SPACE FOR EIGENVECTORS (FTN 10) 53868000 REALS

    SYMMETRY ADAPTION OF THE BLOCH FUNCTIONS ENABLED
    TTTTTTTTTTTTTTTTTTTTTTTTTTTTTT gordsh1 TELAPSE 186.18 TCPU 45.44

  • Discuss tools and techniques for visualizing simulated data

    3 Topics
    14 Posts

    you're the best, thank you for going extra mile

  • Communications for the community and updates on upcoming events

    5 Topics
    6 Posts

    Dear CRYSTAL community,

    We’re excited to share our recent work on accelerating linear algebra operations in the CRYSTAL code using GPUs. Our implementation boosts the performance of self-consistent field (SCF) calculations by offloading key matrix operations like multiplication, diagonalization, inversion, and Cholesky decomposition to GPUs.

    In the manuscript, we first analyze the performance and limitations of the standard parallel version of the code (Pcrystal) and then we evaluate the scalability of the new GPU-accelerated approach with 1 to 8 GPUs, observing remarkable scaling. To highlight these improvements, we present benchmark results on different systems, such as the example below.

    post_forum_1.png

    We expected significant speedups for large systems due to the limited number of k points, each requiring substantial computational effort. To ensure a fair comparison, we ran calculations using the massively parallel version of CRYSTAL (MPPcrystal) on a large MOF structure with over 30000 basis functions. Surprisingly, a single GPU on one node performed comparably to 512–1024 CPU cores running across 4–8 nodes.

    To find out more, read the full paper here.

    We aim to make this GPU-accelerated version of CRYSTAL available in the upcoming release, allowing all users to benefit from its enhanced performance for large-scale simulations. We look forward to reading your thoughts and discussing potential applications or further improvements.

    A big thanks to Lorenzo Donà, Chiara Ribaldone, and Filippo Spiga for their contributions to the development of this code!

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