Largest proteins ever run on R@h coming soon.
In the quest for knowledge about COVID and other proteins, R@h is adapting to meet the challenge.

I wanted to try to help everyone be aware that the project is preparing some of the largest protein WUs even run on R@h. These will take much longer to run per model than smaller proteins. This is going to make "estimated runtime remaining" very difficult to show accurately. It will increase the likelihood of tasks running longer than your WU runtime preference, especially if you have a runtime preference that is less than the 8 hours default. To accommodate, the watchdog will be napping longer that he used to. Only ending WUs that have run more than 10 CPU hours longer than the runtime preference.

These long-running models are going to result in a high degree of variation in runtime between tasks. You might see one task granted nearly twice as much credit as another. That because it ran two models rather than one. Credit should generally be proportional to the amount of CPU time invested in the task.

This high variation in runtime is going to present a challenge for the BOINC Manager in deciding how much work it should be requesting. You can help the BOINC Manager avoid pulling down too much work if you adjust your preferences for how much work to store to be under a day.

Also, several of you have recently reported work units that have completed before their runtime preference. This is going to become more common with these long-running models as well. As an example if you have the default 8 hour runtime preference and the first model takes 5 hours to complete, then 5 hours is where it will stop and report back because a second model would exceed the preference. The Project Team prefers you leave the runtime preference unset, which presently results in 8 hour runtimes. But if these high variations in runtimes are presenting problems for you, I should point out that setting a longer runtime preference will generally result in more consistent completion times. Just beware that runtime preference changes are applied to your existing downloaded work units as well as new work requests. So I always suggest making changes only when you have settings for a small work cache, and to only change the runtime preference a couple of notches at a time, so the BOINC Manager has time to see WUs complete with the new runtimes. This helps it request the amount of work that matches your preferences.

The work units that were running very short models and ending when they reached 1,000 models (before their runtime preference), or other very round numbers, have been adjusted to allow a larger maximum number of models. This will help them fill out their runtime preference, using the additional time to compute more models. This will help runtimes of this type of work unit to be more consistent.

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