Damage wrote:notfred, I think your basic formula isn't terrible, but it does have a weakness in that it doesn't really address locality, memory access patterns, and resource sharing when running similar WU types across multiple cores.
Assuming that one folding process is "glued" to each core, why would what type WU each core is working on affect the other?
I mean the amount of data that is transferred in and out while folding is pitifully small, so I am assuming and have always observed that memory system speed has little to zero impact on folding speed.
I don't think the folding processess can share any data lest the results be skewed, because I was under the impression that each run of even the same WU produce slightly different results. Maybe some of the operations that are performed would be queued or stored in the shared cache and somehow be shared, but that would be assuming that like WU were started and continued at the same pace, and I don't think that would be likely due to system stuff being ran on different cores at different times.
I think main memory, disk subsystem, Instruction cache, and L2Cache is all thats shared in a C2D system right? In folding I am assuming and thoroughly believe these systems are not stressed.
I guess there could be some skewing due to instruction cache sharing, but if you were running 4 cores with all gromacs versus 4 cores with a Tinker, a gromac, a double gromac, and say an amber, you could see if there was enough sharing to make a difference.
I think the biggest problem is going to be if there is not enough memory, and the folding processes start using diskspace for memory.
Guess I'm just curious as to what tests would rule in or out intercore afflictions.
HT.... didn't stanford warn against running HT... more forum diving.