[Beowulf] crunch per kilowatt: GPU vs. CPU

Joe Landman landman at scalableinformatics.com
Mon May 18 13:35:43 EDT 2009


Hi David

David Mathog wrote:
> Although the folks now using CUDA are likely most interested in crunch
> per unit time (time efficiency), perhaps some of you have measurements
> and can comment on the energy efficiency of GPU vs. CPU computing?  That
> is, which uses the fewest kilowatts per unit of computation.  My guess

Using theoretical rather than "actual" performance, unless you get the 
same code doing the same computation on both units:

1 GPU ~ 960 GFLOP single precision, ~100 GFLOP double precision @ 160W

1 CPU ~ 4x (3 GHz x 4 DP flops/cycle) = 48 GFLOP double precision @ 75W

You can argue about these numbers a bit, but these are reasonably close.

This said, any application will not likely be 100% efficient.  So 
ignoring the efficiency issue, its close to a wash for double precision 
FP calculation.  Not even close for single precision or integer 
calculations though, with the GPU providing far more computing power per 
watt than the CPU.


> is that the most energy efficient solution is still CPU based,  because
> Intel and AMD have both worked hard on that issue.  Seems like this sort
> of information would be useful when comparing CPU and GPU based
> solutions, in order to determine the overall cost efficiency (total
> crunch /(purchase price + operating expense).

NVidia has recently been marketing these as "replaced a large cluster 
with a much smaller one".  Then we have seen infrastructure cost 
comparisons.  These make sense if your applications map onto the Cuda 
systems very well (GPU-HMMer), and you can distribute computations 
across many of them (MPI-HMMer) at once to realize these performance deltas.

Not all applications will work this way though, so YMMV.  And your power 
too...

> 
> Thanks,
> 
> David Mathog
> mathog at caltech.edu
> Manager, Sequence Analysis Facility, Biology Division, Caltech

-- 
Joseph Landman, Ph.D
Founder and CEO
Scalable Informatics LLC,
email: landman at scalableinformatics.com
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