G'day,
This is my first post so please forgive me if this has already been asked.

I've only been a member of GPUGRID for a few weeks - in that time, I've noted that no matter what I set the "Maintain enough work for an additional - Enforced by version 5.10+" option - which I currently have set at 1/4 of a day, I end up with 4 GPUGRID workunits, to be returned in 4 days.
The time that my PC is on is quite variable and I'm often away from it for long periods when it is on, therefore I seem to be missing the deadline on some units. This seems to be to be such a waste of processing power.
It would make much more sense to me to only queue 1 unit at a time, especially with their variable size and with that BOINC option set; instead of downloading four at once. How is the scheduling of units determined, and is it something that may be configured?
I don't have any issue with the deadline of 4 days - any modern computer with a decent GPU should be able to complete one unit in that time, even if only on for a fraction of each day.

Hats off to GPUGRID for having such an innovative project. :)
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Well, I thought that someone may have posted an answer to this, surely I'm not the only user with this issue?

E.G this morning I had to cancel two units as they would not have completed by the deadline. I specifically left my PC crunching all night in order to meet the deadlines, only to discover that for whatever reason, the WU restarted during the night when my PC rebooted because of Windows automatic updates... to say I was annoyed is an understatement.

These two units were the third and fourth handed out in the four day cycle that I seem to get, where I receive four units at a time.

Please just send one unit at a time!

sorry no one posted to this earlier. The setting you used is only for CPU apps. At this time there is no way to limit the work you get for a GPU app except from the server. It is currently set to download a limit of one workunits per CPU core. It is planed in the future to both allow work sent based on number of GPU cores and to allow a work cache setting for GPU applications.

Remember, everything about this project is beta, from the science app, to the client you are running, to the server side software.