Oh yeah, once again someone said awhile back that they would be monitoring the boards for discussions like this one. Once again the system fails and no one see's or says anything about it.

It's not really an issue about the system failing - it simply that we don't (currently) have jobs that are ready to run right this minute. The running of the jobs on R@h is only one step in the process - it takes a while to figure out what sorts of jobs will give usable scientific results, to set up the jobs, test them to make sure they won't cause a huge failure rate, and then at the end of the runs to process the results to figure out what the next round should do. Usually we have enough things going on that the computational lull in one project will be covered by the compute phase of a different one. We just happen to have hit a point where none of the currently active projects is in an active compute phase. (And doesn't help that we're maximally distant from both the previous and next CASP - as you've probably noticed, activity seems to ramp up before [mad rush to finalize improvements], during, and after [post-analyis] CASP.)

We're aware that the queue is empty - a message has been sent out on the appropriate internal mailing list. While we want to provide you with work units, we don't want to waste your time with scientifically pointless make-work. - It's somewhat trivial to re-run old jobs, but is that worth doing if no one is going to look at the results?

I hesitate to say this, as I don't want it to sound like we're chasing you away(*), but I'd agree with the implicit recommendation stated above to crunch other projects while we have this momentary lull. You can increase your stats on other projects secure in the knowledge that no one will gain on you with Rosetta@home. With any luck, we'll have new jobs for you early next week. (e.g. "We apologize for the inconvenience - Regular service should resume shortly.")

*) We really do appreciate your efforts. Having access to the computational resources of R@h allows us to do things we couldn't do otherwise. Frankly speaking, I was surprised how quickly and easily R@h handled my recent jobs. I would have monopolized our local computational resources, but R@h crunched through it like it was nothing. - It's prompted me to think about possible process improvement experiments that I probably wouldn't have otherwise considered due to the computational cost. (Unfortunately, it's in the very preliminary stages and nowhere near the point where I could actually launch any jobs.)