<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">Hi Gurvinder,<div class="">I think Monday/Tuesday is a bit too early for having identified any suspects. The NLPL infrastructure team will probably discuss this tomorrow, and we can get back to you ( I am anyway unavailable Monday and Tuesday).</div><div class=""><br class=""></div><div class="">You can delete the ‘nlpr’ project space and make a new one ‘nlpl’. There is nothing of value in the ‘nlpr’-space.</div><div class=""><br class=""></div><div class="">Best Regards</div><div class="">Bjørn <br class=""><div><br class=""><blockquote type="cite" class=""><div class="">On 13 Sep 2018, at 19:04, Gurvinder Singh <<a href="mailto:gurvinder.singh@uninett.no" class="">gurvinder.singh@uninett.no</a>> wrote:</div><br class="Apple-interchange-newline"><div class="">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" class="">
<div class="">
<div style="font-family:sans-serif" class=""><div style="white-space:normal" class=""><p dir="auto" class="">Hei Stephan,</p><p dir="auto" class="">We, at Uninett, are positive to this proposal and it should provide us feedback from a new user domain. DaaS is a research cluster with 8 GPUs in it (7 Titan X/Xp and 1 P5000) whereas NIRD service platform is a production cluster. Currently NIRD SP lacks GPUs but GPUs (Volta V100) have been ordered and will be available on platform in a month or two. From end user perspective both platform provide a user friendly App Store. So your team can start using DaaS and later on can get access to Volta GPUs on NIRD SP. </p><p dir="auto" class="">Regarding access, use the Appstore (<a href="https://appstore.ioudaas.no/" style="color:#3983C4" class="">https://appstore.ioudaas.no/</a>) to deploy <code style="background-color:#F7F7F7; border-radius:3px; margin:0; padding:0 0.4em" bgcolor="#F7F7F7" class="">Deep-learning-tools</code> application. It already has Tensorflow, Pytorch, Keras and few other machine learning framework in it. Documentation is located here <a href="https://appstore.ioudaas.no/docs/" style="color:#3983C4" class="">https://appstore.ioudaas.no/docs/</a> and if your team members would like to have the kubectl level access not just appstore then use docs here <a href="https://docs.ioudaas.no/access/" style="color:#3983C4" class="">https://docs.ioudaas.no/access/</a> Access is controlled using Dataporten, so any user from Norwegian higher education community should be OK also most users from education community in Europe.</p><p dir="auto" class="">As Bjørn mentioned I already have a <code style="background-color:#F7F7F7; border-radius:3px; margin:0; padding:0 0.4em" bgcolor="#F7F7F7" class="">nlpr</code> project space. I can create a new group called <code style="background-color:#F7F7F7; border-radius:3px; margin:0; padding:0 0.4em" bgcolor="#F7F7F7" class="">nlpl</code> or rename the current one, please let me know which is preferred. I think, it would be good to have a short (30-60 mins) video meeting next week (Monday anytime between 1000-1200 or Tuesday before lunch time) where I can walk you and your team through the various things to get started and get to know more about your use case as well.</p><p dir="auto" class="">-- Gurvinder</p><p dir="auto" class="">On 13 Sep 2018, at 12:04, Stephan Oepen wrote:</p>
<blockquote style="border-left:2px solid #777; color:#777; margin:0 0 5px; padding-left:5px" class=""><p dir="auto" class="">dear colleagues,</p><p dir="auto" class="">in our NeIC-funded project NLPL (‘<a href="http://www.nlpl.xn--eu-o2t/" style="color:#777" class="">http://www.nlpl.eu’</a>), we are<br class="">
currently running up against limited gpu availability on the Abel and<br class="">
(finnish) Taito clusters.</p><p dir="auto" class="">hence, i am wondering whether it would make sense for us to explore<br class="">
usage of the DaaS service platform? we have a handful of<br class="">
technologically reasonably seasoned doctoral fellows who will be eager<br class="">
to gain access to gpus (typically to run TensorFlow or PyTorch).</p><p dir="auto" class="">if this sounded like a plausible trial use case to you at this point,<br class="">
i would suggest you set up a namespace (preferably ‘nlpl’ :-) for us<br class="">
and point us at available documentation for users to gain access and<br class="">
get started.</p><p dir="auto" class="">all NLPL users (including those from outside norway) have MAS<br class="">
accounts, to access Abel, so i am hoping non-feide users will also be<br class="">
able to connect to DaaS?</p><p dir="auto" class="">with thanks in advance, oe</p>
</blockquote>
</div>
</div>
</div>
</div></blockquote></div><br class=""></div></body></html>