So, since you are interested in the best GPU performance, I But there have been a few changes since that time. Then, you are (mostly) using the version of 1.3b4, which is the

(and their communication speed with the CPU). So your performance is based on the particular GPUs Sorry for that.ДЇirst, my guess was actually completely incorrect, since 'internalДЇields' is the GPU time (mostly), while 'scattered fields' is One more duplicate to get this message into the correct thread. May be very different from pure Gflops that you mentioned.Д«y the way, current version of ADDA wikis are atДЄnd coming back to your specific questions: There may be even some benchmarksДЄt the corresponding website. ), so try it if you are ready to experiment a little bit.ДЄlso, in terms of performance of different GPUs, it is a good idea Issue, but this option is not documented (see. (works only with bicg iterative solver), which may help with this We have an experimental option OCL_BLAS in Makefile And Nvidia cardsДЄre usually faster in this copying, which may explain theДifference. This copying may become noticeable on fast GPUs comparing with theД¬omputational part (mainly using clFFT library). Time for scattered fields - and they are not GPU accelerated - seeД«e determined by the used CPU, which is probably not the same forДЄll runs, is it? In general, one should look, first, at 'InternalД«ut even then, by default only the matrix-vector product isДЄccelerated by the GPU and copying of input to the GPU memory (and The latter contained detailed timing information in theД®nd, which may be relevant for our discussion.ДЄs a first wild guess, you may spend major fraction of simulation Can you please additionally provide the usedД¬ommand line to execute ADDA and, ideally, the resulting logДЇiles. Thanks for your interest in OpenCL mode of ADDA and for testing it Is there a way to utilize two (2) or more GPUs in one (1) Motherboard, in order to speed up the process? 2011, in order to speed up the calculations significantly? Is there a way to take advantage of the DP performance of Tesla GPUs, as is stated in Huntemann et al. How is the accuracy of the result impacted by the GPU runs (due to SP)? Judging from the above results, the best solution for runnning ADDA is currently the nVidia GTX1080 Ti, since the AMD cards seem to fall behind considerably despite similar FP32 and FP64 performance. It is evident that the FP64 (DP) performance is completely irrelevant to the overall performance of the ADDA algorithm. I have run the latest version of ADDA (Feb 2017) in different GPU's with the following results:

Tesla k80 fp64