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This may be of general interest:
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Hello Nah--
> I am noticing a big performance issue when scaling up, albeit the fact
> that these just trivially parallel calculations with no inter-process
> communications. For ex., even with my PC, i can calculate say 2
> structures in 5 mts (same script with num_Strucures = 2) when trying
> the parallel version of it with 64 processors, 1000 structures
> calculation took 2.30 hrs (whereas it should have taken ~1 hr from an
> approximation of ~4mts per structure calculation) and interestingly
> with 96 processors and for 2000 structures it's taking close to 9hrs
> for the calculation !!! /cluster/softs/xplor-nih-2.19/bin/xplor -py
> -parallel -machines 96_procs -o mod.out mod_anneal1.py and the machine
> file 96_procs has 96 processors listed (since each machine has 8
> processors, i am repeating the machine name 8 times ; 12*8 =96
> processors)
>
I guess these are Intel 8 core processors. These things have one front
side bus, so they will not scale up to 8 cores at all (as you've
found). I suspect that running more than 2, maybe 3 Xplor-NIH processes
per CPU is a waste. Note that 4-core AMD chips and the upcoming Intel
processors with the QuickPath Interconnect bus should behave much
better. Your current results are a limitation of the chip
architecture. Your chips may have 8 cores, but you don't have memory
bandwidth to use half of them efficiently.
I'm curious about the 64 vs. 96 processor results: In one case you ran
on 8 processors and the other on 12? Or was there some other difference?
best regards--
Charles
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