Hi Guys,

Due to my being out of the loop regarding hardware for awhile, some bad advice, and the draconian return policies of a local computer store which I'll never be doing business with again, I got stuck with an AMD A10-7850k "12 core" processor, which is actually a 4 core where AMD calls the on-board GPU another 8 cores. (I don't game.) And the 4 cpu cores have a reputation for being... disappointing, with each 2 cpu cores sharing a single floating point unit. But I'd kind of like to know how bad it really is. I'm running 4 simultaneous HadSM3P with Moses II models. They've only been running for about 18 hours and are only at 0.5%, but the estimated total elapsed time is holding steady at 350 hours per model. So how good/bad/ok is finishing 4 of those in 350 hours? I've been kinda out of the loop regarding CPDN models, too.

Thanks so much for any opinions,

Sincerely,
Steve Bergman

I don't have any A10 or similar CPUs but I have the older Phenom II type CPUs and to give you an idea of their run times on a couple of different models here they are (they run at 3.2 GHz standard clock, running Linux Fedora 16 64 bit)

This is quoted RUN Time, CPU Time is often quite a bit less,

MOSES II Landsurface Scheme around 1,008,800 seconds (280 Hours)

MOSES II and TRIFFID Europe around 1,004,000 seconds (279 Hours)

Coupled Model Full Resolution Ocean from 1,230,000 to 1,550,000 seconds (341 to 430 Hours)

I currently have 2 MOSES II and TRIFFID models running and they are

192 Hours at 67% with 92 Hours to go
242 Hours at 83% with 47 Hours to go

This at least will give you an idea as to what to expect, I am hoping that as you have much more recent chips then the times will be a lot lower, I am hoping this as I will have to update soon myself.

Conan

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Thanks. That does give me some idea. The A10-7850K is AMD's top of the line of a *very* interesting new architecture. It's not even called a CPU anymore. It's an APU. It has 4 cpu cores and 8 radeon gpu cores sharing up to 32GB of DDR3-2400 main memory. It employs technologies like HSA and hUMA (which have been used by smartphones for years.) What this does is put the cpus and gpus on an even footing, with a shared virtual and physical address space with no memory copy necessary to move data back and forth between cpu and gpu. And from the programmer's standpoint, the the gpus are just another type of processor available with its own own characteristics, like being *really fast* for vector processing. Basically opencl done right and on steroids. But the programmer needs to write for it. LibreOffice calc does, and the results are pretty spectacular.

A silver lining to all this is that it prompted me to research, and I found PlayOnLinux which is pretty spectacular. I installed it, installed Windows Steam in it, and I'm now happily playing one of my old favorites, Doom 3, at 1920x1080 with 8x antialiasing and 512MB "Ultra" texture quality at great frame rates. Not bad for on-cpu... err... on-APU graphics. (I could never have done that with my $500 Nvidia GeForce 3 9600GT back when the game came out.)

And of course, that means that I should do well on opencl apps. The problem is that while I don't care about credits and competition on BOINC, I do care deeply about being excited about the science I'm helping. And my favorite projects, Einstein@Home gravity wave search and CPDN are CPU only. (CPDN for excellent reasons, I should add.). So if I want to leverage the GPU, I'm pretty much limited to signal processing like looking for pulsars, which is a worthy pursuit, but doesn't really grab me all that much.

I still use Debian 7 for my customers' local servers and Centos/Scientific Linux for the ones in other cities. But I just recently moved my own desktop from Debian 7 to Mint 17.1 Cinnamon and am loving it!

And of course, that means that I should do well on opencl apps. The problem is that while I don't care about credits and competition on BOINC, I do care deeply about being excited about the science I'm helping. And my favorite projects, Einstein@Home gravity wave search and CPDN are CPU only. (CPDN for excellent reasons, I should add.). So if I want to leverage the GPU, I'm pretty much limited to signal processing like looking for pulsars, which is a worthy pursuit, but doesn't really grab me all that much.

I still use Debian 7 for my customers' local servers and Centos/Scientific Linux for the ones in other cities. But I just recently moved my own desktop from Debian 7 to Mint 17.1 Cinnamon and am loving it!

The new POEM (2.21) is OpenCL, optimized for AMD. I think it works with Linux and the A10 OK.

@Steve You could also have a peak at http://wuprop.boinc-af.org/
It collects (among other things) the elapsed time for each boinc application, see e.g.
http://wuprop.boinc-af.org/results/projet.py?projet=climateprediction.net&application=UK+Met+Office+Coupled+Model+Full+Resolution+Ocean

The statistics might be a bit sketchy if there are few people attached to both cpdn and wuprop. You can contribute by attaching boinc to wuprop.

Thanks! I'll have a look.