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[PCPer] Folding@Home NVIDIA GPU Client Confirmed - Page 5

post #41 of 54
With my CPU, should I be running SMP client? I really don't wanna lose any performance. I run normal client now.
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post #42 of 54
I'll be expecting to up my ranking.
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post #43 of 54
Finally, awesome news like everyone I have been waiting for this.
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post #44 of 54
Quote:
Originally Posted by Litlratt View Post
I'll be expecting to up my ranking.
Just a smidgen faster than the CPU one
    
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post #45 of 54
This is conjecture, but since the the whole point of the project is simulating folding in protein chains... then I assume 500ns means the GPU is able to simulate 500ns worth of time in the molecular process for each day it's running. That would be a lot, this stuff is a lot more complex than we can easily get our heads around.

Rob
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post #46 of 54
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post #47 of 54
Quote:
Originally Posted by Bal3Wolf View Post
And one post below that...

Quote:
On Friday, Stanford launched the Pervasive Parallelism Lab (PPL). There's been lots of press describing it. The general plan for the lab is to develop a common paradigm for programming new architectures like GPU's, the Cell processor, Intel's Larabee, as well as multi-core CPUs. This is something we at FAH are very interested in, as we have had to have a unique code path for each of these (i.e. a separate code for the high performance part of the ATI GPU, NVIDIA GPU, PS3, and SMP). Having a single code path for all would be very, very exciting to keep FAH code development onto new hardware going smoothly.
I've known about it for a few weeks...thought everyone did, lol.

~Gooda~
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post #48 of 54
Quote:
Originally Posted by trueg50 View Post
How is it compared to the ATI GPGPU language?

I heard the ATI one was pretty tough compared to CUDA.
Year those a two complete different approaches.

ATI's method is known as "closer to metal", meaning you can control it better and should be able to use the performance better.
But as you said it is harder to learn and more important, harder to debug.


NV's CUDA can run compiled C Code.
So if you can prog C you can easily learn CUDA.
In Terms of performance, it is more to the compiler to optimize.


The point that a programmer can control the code optimization and therefore the performance better with ATI's way is a theoretical thing!
Since R600 and G80 (and following) Chips have different architectures and different general performance, the results in real life can diver...
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post #49 of 54
anyone have any ideas on the release of this, 1 month, 1 year?
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post #50 of 54
I would expect a month or a little longer...it wont be aslong as a year I wouldnt have thought.
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