Please help me understand PDGDeadline

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Are the partitions you are talking about something on Deadline side?
Since if you mean wrapping all work items into a single partition on TOP side then I imagine you lose granular dependencies on input workitems essentially becoming wait for all, which can be undesirable in many scenarios and also is not very friendly towards true dynamic workitems or mixed with other type of partitioning since this sounds like otherwise unnecessary additional partition wrapper and I dont know if you can nest partitions
Tomas Slancik
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Method Studios, NY
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Indeed we mean waiting for all/part of upstream tasks. Partitions could contain batches that are directly translated to batches in Deadline. The way Deadline works, it takes a frame range and a path template, and manages itself to determine job tasks.
It's true that we might lose some efficiencies this way, but it will be solid, an avoid the race condition of dynamically producing DL tasks.
Edited by monomon - Oct. 8, 2024 03:57:20
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Partitions are on the houdini side - when we have work items that are per frame, we can partition them into work items that are per job. Deadline needs the frame range for the job, we can provide that from a work item attribute.
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Hi All,

Just an update. We recently had discussions with AWS Thinkbox regarding the challenges that Houdini users are facing with the new H20.5 PDG Deadline Scheduler. In light of these discussions as well as new limitations reported by users, we have decided to add a toggle to the PDG Deadline Scheduler that will enable you to switch from the H20.0 behaviour of one-job-of-many-tasks (will be the default) and the H20.5 behaviour of one-batch-of-many-jobs.

Our aim is to roll the new toggle into an upcoming H20.5 production build update, hopefully some time near the end of November or the beginning of December.

Cheers,
Rob
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That's awesome, I'm definitely going to use the toggle and try my luck with the old approach. It's good to have both solutions.
Edited by alexmajewski - Nov. 1, 2024 06:36:51
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