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Re: [Starpu-devel] Problem with performance model calibration


Chronologique Discussions 
  • From: Mirko Myllykoski <mirkom@cs.umu.se>
  • To: Samuel Thibault <samuel.thibault@inria.fr>, starpu-devel@lists.gforge.inria.fr
  • Subject: Re: [Starpu-devel] Problem with performance model calibration
  • Date: Tue, 9 Jun 2020 12:44:00 +0200
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Hi,

On 2020-06-03 20:41, Samuel Thibault wrote:

Ok. When that happens, what are the values of the other fields? We have
some code that tries to get rid of outliers, which just flushes the
content of the entry, in which case the mean will indeed be reset to
0.0, but also all other values (sum, sum2, nsample).

How/where is this outlier filtering performed? I am asking because I have been getting some weird results with a (consumer-level) GPU. Please see the attachment.

In particular, you can see that the "c" parameter is quite small for the CUDA implementation:
Non-Linear: y = a size ^b + c
a = 3.220354e-06
b = 7.817886e-01
c = 1.084335e-03
Non-Linear: y = a size ^b + c
a = 1.016593e-03
b = 3.854069e-01
c = 2.572536e-10

That is, the model is very close to being linear and clearly does not fit to the data.

I believe this happens because the fitting algorithm fails to find the correct "c" parameter. Based on the data, the "c" parameter should probably be ~0.06. However, since the "c" parameter is always smaller than "cmax" and "cmax" is ~0.006, the "c" parameter is always going to be far outside the range where the fitting algorithm can actually converge to something useful.

- Mirko

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Attachment: starpu_starneig_right_gemm_update_pm.banana.eps
Description: image/eps

Attachment: starpu_starneig_right_gemm_update_pm.banana.gp
Description: application/gnuplot




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