<div dir="ltr">Hi Geng,<div><br></div><div>Could you bring the input and output files? In my case I ran AIMD with hybrid functionals adn similar amount of atoms, and the DERIV's calculations are not so expensive as in your case... but I guess in your case the atoms has d electrons which makes the calculation more expensive.</div><div><br></div><div>Regards</div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">El lun, 4 ene 2021 a las 17:31, Sun Geng (<<a href="mailto:gengs...@gmail.com">gengs...@gmail.com</a>>) escribió:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div>Dear CP2K users,</div><div><br></div><div>I am using CP2K with the ADMM method for structure optimization.</div><div>The system is an inorganic bulk with around 100 atoms in a cubic box 12x12x12 angstrom^3.</div><div>I am able to set up the calculation resulting smooth SCF convergence. </div><div>The "Number of sph. ERI's calculated on the fly" is 0 and hence the SCF converges quickly. The first SCF takes about 1800 seconds and the following SCF steps take only an impressive 20 seconds. In the end, CP2K can converge the SCF in approximate 2500 seconds.</div><div>However, I notice that in between the optimization steps, the derivatives of integrals are still calculated on the fly (see the output below), and this step appears to be very slow. CP2K did not print how long it took to compute the derivatives, but I can tell by checking the updating time in the output. My estimation is that it takes more than 2 hours to calculate the derivatives.</div><div><br></div><div> HFX_MEM_INFO| Number of cart. primitive DERIV's calculated: 11208181891200</div><div> HFX_MEM_INFO| Number of sph. DERIV's calculated: 140954718240</div><div> HFX_MEM_INFO| Number of sph. DERIV's stored in-core: 0</div><div> HFX_MEM_INFO| Number of sph. DERIV's calculated on the fly: 140954718240</div><div> HFX_MEM_INFO| Total memory consumption DERIV's RAM [MiB]: 0</div><div> HFX_MEM_INFO| Whereof max-vals [MiB]: 1</div><div> HFX_MEM_INFO| Total compression factor DERIV's RAM: 0.00</div><div><br></div><div><br></div><div>Finally, the overall efficiency of CP2K for optimization is much slower than that of VASP code for this system (both of them used HSE06 functional). In VASP, although an SCF step takes 200 seconds and SCF converged in 15 steps (resulting in 3000 seconds per optimization step), the forces are calculated with negligible cost in VASP.</div><div><br></div><div>I wonder are there any tricks in the cp2k inputs that can speed up the derivatives of the integrals? Or any pieces of advice that I can use in using CP2K/ADMM methods?</div><div>My personal impression is that CP2K/ADMM is not the optimal choice (in terms of optimization efficiency) for a small system (maybe within 150~200 atoms, I did not test though) compared with VASP code. Maybe, for a larger system, the overhead of calculating forces in CP2K/ADMM is relatively small, and in that case, CP2K/ADMM will be more efficient than VASP? Please let me know if this is a realistic point for choosing VASP and CP2K.</div><div><br></div><div>Thank you very much in advance!</div><div><br></div><div>Best </div><div>Geng</div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div>
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