Author Topic: RDGRAD Failing in SMP with RIJK  (Read 6207 times)

tjmustard

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RDGRAD Failing in SMP with RIJK
« on: April 25, 2012, 09:27:09 PM »
Hi all,

I currently have an issue with a RIJK jobex optimization failing on the first RDGRAD. Has anyone seen this error?


.......
.......
           ------------------
           density functional
           ------------------
 Becke-3-Parameter hybrid functional: B3-LYP
 exchange:    0.8*LDA + 0.72*B88 + 0.2*HF
 correlation: 0.19*LDA(VWN) + 0.81*LYP
 iterations will be done with small grid
 
 spherical integration : Lebedev's spherical grid
 spherical gridsize    :           3
    i.e. gridpoints    :         302
 value for diffuse not defined
 radial integration    : Chebyshev 2nd kind (scaling 3)
 radial gridsize       :           3
 integration cells     :          16
 partition function    : becke
 partition sharpness   :           3
 
 
           ------------------------
             RDGRAD - INFORMATION
           ------------------------
 
     
           0  shell pairs used , remaining=        3570
 Task specific shell ranges
 DYNAMIC TASKS
   #task        #minshell    #maxshell
       3           42           60
       4            2           42
       5            1            2
 maximum shell range =          41
 Local memory allocated for RDGRAD: 1 MiB
 PQ decomposition by fast serial Cholesky
SEVERE ERROR from node:   0 symink not yet adapted to gradients
error in gradient step (1)


Thank you,
TJ Mustard

uwe

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Re: RDGRAD Failing in SMP with RIJK
« Reply #1 on: April 27, 2012, 12:27:37 PM »
Hello,

RI-K is not parallelized at all in rdgrad. The method was developed as a way to speed up Hartree-Fock when doing MP2 calculations. RI-K works best with medium-sized molecules and larger basis sets (at least TZVP) and if you have enough memory to store the RI matrices completely in RAM.

For DFT jobs the basis sets in use are usually smaller, so here RI-K can be even slower than the conventional DFT calculation.

B3-LYP works really good with RI-J only (i.e. without RI-K) also in parallel. Here a (so called) linear scaling exchange algorithm is being used which makes the calculation faster than the non-RI-J case by a factor of two and more (depends on the size of the molecule, but if you run it in parallel, I assume that it is not a small job).

Regards,

Uwe