Dear Sreekar Guddeti, in addition to reading the documentation you have been pointed to, please take into account the hardware (cpu and communication network) you have at hand. R and G parallelization is memory efficient but involves large and frequent communications hence it will not be efficient unless your communication network is very good. For massively parallel machines (such as blue gene etc) one needs to introduce further divide and conquer tricks (see the discussion in our recently appeared "reference paper") Other types of parallelization (k-point, neb-images) involve much less communication and can be of help even if the network is not very good. In any case at the end of PWscf output there is some timing report that should tell you how much are you spending in computing and how much in communicating ... this should give you an idea whether increasing the number of cpus can help or actually worsen the performance
Hope this helps, stefano de Gironcoli sreekar guddeti wrote: > hello QE users, > i would be grateful if u could provide me with any references for the > principles involved in parallel execution like how the grids are > divided among processors which, should supposedly enhance perfomance, > etc. because i performed a parallel execution and the CPU time taken > is more than that in the serial case > > thnks in advance > > > -- > Sreekar Guddeti > Physics Department > IIT Bombay > India > ------------------------------------------------------------------------ > > _______________________________________________ > Pw_forum mailing list > Pw_forum at pwscf.org > http://www.democritos.it/mailman/listinfo/pw_forum >
