<div>Hi <span>Amit,</span></div><div><span><br></span></div><div>unfortunately, we never manged to eliminate those block size constraints from ELPA.</div><div>Going forward our hope rests on the new DLA-Future library which should arrive in CP2K soon.</div><br><div>-Ole<br></div><br><div class="gmail_quote"><div dir="auto" class="gmail_attr">On Wednesday, November 2, 2022 at 1:22:42 AM UTC+1 Amit Gupta wrote:<br/></div><blockquote class="gmail_quote" style="margin: 0 0 0 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;"><div>I have finally got the GPU version of CP2K working. However when I run, I get the following warnings:</div><div>```</div><div> ELPA: Warning, CUDA kernel only works with block size 2^n (n = 1, 2, ..., 10)!<br> The compute kernel will be executed on CPUs!<br> We recommend changing the block size to 2^n</div><div>```</div><div><br></div><div>There have been discussions here: <a href="https://github.com/cp2k/cp2k/issues/464" target="_blank" rel="nofollow" data-saferedirecturl="https://www.google.com/url?hl=en&q=https://github.com/cp2k/cp2k/issues/464&source=gmail&ust=1667487505690000&usg=AOvVaw0Xj1n-2Jhx6KavNHthruUi">https://github.com/cp2k/cp2k/issues/464</a></div><div>I am not sure what was the outcome, but it does say certain commits for closing the issues.</div><div><br></div><div>1. How to define the block size?</div><div>2. What are other "good practices" for extracting the most out of GPU?</div><div><br></div><div>CP2K version: 2022.2</div><div>Configuration:  --with-libxc=install --with-libint=install --with-fftw=install 
--with-mkl=system --with-libxsmm=install  --with-elpa=install   --with-spla=install   
--with-cosma=install <br><div><br></div><div>Thank you--with-intel=system --enable-cuda --gpu-ver=V100  --with-openmpi=system  <br><br></div></div></blockquote></div>

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