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L1TMuonEndCapTrackProducer::produce() takes 96 MB memory per stream #42526
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assign l1 |
New categories assigned: l1 @epalencia,@aloeliger you have been requested to review this Pull request/Issue and eventually sign? Thanks |
A new Issue was created by @makortel Matti Kortelainen. @Dr15Jones, @perrotta, @dpiparo, @rappoccio, @makortel, @smuzaffar can you please review it and eventually sign/assign? Thanks. cms-bot commands are listed here |
Moving the Tensorflow stuff to |
Hi @makortel , as you said the main contribution here is loading of the BDT in Regarding the Tensorflow stuff and |
Hi @eyigitba I think addressing the The Tensorflow part would be nice (e.g. if the model would become larger in the future, or serving as an example for others), but with 0.5 MB / stream not that important today. |
Hi @makortel , ok we'll look into the BDT loading and also see how we can improve the Tensorflow part. How urgent is this btw? |
Memory budget is 2GB per stream (including shared component and I/O buffers). |
BTW: why using your own implementation of a Forest and not the highly optimized common CMS one I would advice to switch to that. |
Thanks for the advice @VinInn . I don't know why it was implemented like this, but this code is quite old, from 2016 or so. I unfortunately don't have much time these couple of weeks, but we'll discuss in the EMTF group to come up with a solution soon. |
The In my opinion it would be great if this would be addressed for 2025 data taking. |
cms-bot internal usage |
type performance-improvements |
@eyigitba @cms-sw/l1-l2 Any news? |
@makortel , not yet from my side. I have a student looking into this but nothing to discuss for now |
Came up in #46975 (comment) |
Live memory profiles of #40437 (comment) show that
L1TMuonEndCapTrackProducer::produce()
takes 100 MB memory / streamThe
L1TMuonEndCapTrackProducer
module itself is anedm::stream
. The memory consumption can be split intoPtAssignmentEngine::load()
, that seems to load some kind of BDT?EMTFSetup::reload()
loading some LUTsSectorProcessor::process()
that is mostly TensorflowAssuming the
PtAssignmentEngine::load()
is indeed BDT or similar, does its representation really need to be that large? Ideally all of these would be inGlobalCache
of the module (e.g. Tensorflow stuff), or in the EventSetup (e.g. the BDT whose content apparently depends on theL1TMuonEndCapParams
andL1TMuonEndCapForest
EventSetup data products).The text was updated successfully, but these errors were encountered: