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Rik
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« Reply #25 on: Jul 29, 2010, 10:39:58 »

It will be interesting to see how long it takes the software to catch up with the hardware, won't it.
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esh
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« Reply #26 on: Jul 29, 2010, 10:47:43 »

We have some software here used for the modelling of binary star systems, and it will literally eat a single CPU for hours on a single run (and sometimes you have to do it dozens of times, tweaking by hand after each solution). Since I have a 2x4 Intel Xeon rig with a stack of RAM in it, we thought since it was our own code, we could make it MP (multiprocessor). In the most naieve way possible, we ran Valgrind (code profiler) on it, found the most intensive algorithms where the CPU sat, and wrapped them in OpenMP directives, namely each cycle of the internal loop of code should go to another processor. You would think you'd suddenly be at 800%.. but on average the code now ran at 133%, ie. it was using 1+1/3 processors for its effective runtime. Not particularly impressive. Of course, this was a very simple implementation and a 33% benefit is better than nothing, but it does go to show that it will probably need a hefty rewrite to accomplish a lot better utilisation. It's just not easy... there's a lot of subtle interactions, and when anything has to fetch data from the disc -- it all goes to hell. But that's always been the case.
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Rik
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« Reply #27 on: Jul 29, 2010, 10:53:04 »

Thanks for the insight.  Thumbs up
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« Reply #28 on: Jul 29, 2010, 15:24:47 »

Oo that's interesting. What do you do? The nerd in me needs to know Cheesy
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« Reply #29 on: Jul 29, 2010, 15:27:34 »

Probably works for Jodrell Bank
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« Reply #30 on: Jul 29, 2010, 16:46:25 »

We have some software here used for the modelling of binary star systems, and it will literally eat a single CPU for hours on a single run (and sometimes you have to do it dozens of times, tweaking by hand after each solution). Since I have a 2x4 Intel Xeon rig with a stack of RAM in it, we thought since it was our own code, we could make it MP (multiprocessor). In the most naieve way possible, we ran Valgrind (code profiler) on it, found the most intensive algorithms where the CPU sat, and wrapped them in OpenMP directives, namely each cycle of the internal loop of code should go to another processor. You would think you'd suddenly be at 800%.. but on average the code now ran at 133%, ie. it was using 1+1/3 processors for its effective runtime. Not particularly impressive. Of course, this was a very simple implementation and a 33% benefit is better than nothing, but it does go to show that it will probably need a hefty rewrite to accomplish a lot better utilisation. It's just not easy... there's a lot of subtle interactions, and when anything has to fetch data from the disc -- it all goes to hell. But that's always been the case.

You said you tweak it by hand, would it not be more efficient to run 4 separate processes each with a different set of variables? Then you utilise 100% of each of the cores. I suppose it's no good if your researching just one system. Even then, you can reach an average/correct result quicker. By selecting a high variable, a mid and a low, and then going off the closest of the three from there. Should give you less runs to get to the correct variables.
BTW, IANAS (I am not a scientist) so take that with a pinch of salt. Wink
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« Reply #31 on: Jul 29, 2010, 18:11:21 »

A lot of video (and music) encoding software now supports mutiple processors/cores. DBpoweramp is a good example - say you are re-encoding a load of music, it will do each music file on a seperate core up to the number of cores in your machine.
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« Reply #32 on: Jul 29, 2010, 18:13:41 »

That's the one program I really miss on the Mac and works exactly as you say,speeds up the transcode dramatically on a multicore.
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esh
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« Reply #33 on: Jul 30, 2010, 09:59:45 »

Yes, you can run multiple processes simultaneously (careful not to let them overwrite each other's results, of course I never made that mistake!). In fact, we often do when running an MCMC simulation using the program (to achieve a distribution of the variables, ie. variance and error). The problem of recent was in fact the data was too good; we got preliminary downlink from Kepler (a space satellite) and because it is just so unbelievably precise we needed millions of grid points to model what we were seeing, this shoots up the computational time from 'hours' to 'weeks'. The stuff you get off of there is just amazing.
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« Reply #34 on: Aug 01, 2010, 09:40:06 »

Sounds like you have a very interesting job. Want to switch jobs? Grin
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« Reply #35 on: Aug 06, 2010, 00:03:42 »

Will this machine be powerful enough for my iTunes and checking email?
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« Reply #36 on: Aug 06, 2010, 06:52:18 »

 Welcome to IDNetters Have a Karma!
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Glenn
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Rik
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« Reply #37 on: Aug 06, 2010, 10:23:33 »

Will this machine be powerful enough for my iTunes and checking email?

Definitely not. For that, you'd need 24 cores. Wink

Hi and welcome to the forum. Welcome to IDNetters Have a Karma!
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Rik
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