[cadynce] Model CPU Utlizations Predict End-to-End Times

[Alan F. Karr]

Patrick,

This is an investigation the extent to which the CPU utilizations given 
the the models predict the measured end-to-end times (averaged over 
messages--we will do the worst case times today). Everything is 
restricted to the critical path. The model is in R-like notation: the 
six CPU utilizations are the predictor (independent) variables. The six 
coefficients are implied. I've revised the PPT to try to make this a bit 
clearer, and will put it on the wiki. It's also attached, since it's so 
small.

--- Alan

Patrick Lardieri wrote:
> Hi Alan,
>
> Interesting thoughts that I am not sure I understand fully.
>
> At the 100,000 ft level it seems you are offering an alternative to 
> scheduling theory to predict the response time.  Specifically, you 
> seem to be suggesting that a linear regression model could be used to 
> predict the mean end-to-end response time of an appstring by 
> considering the  CPU utilizations  of the critical path components  as 
> the independent variables.  Is this correct?
>
> A couple of questions:
>
> 1) It is not clear in the slide what the independent variables really 
> are. Are the the software components specified worst case execution 
> time? The software component's measured mean execution time? The 
> utilization on the CPU that the application runs on?
>
> 2) The equation on slide 2 has one coefficient but slide 3 implies 
> there is a coefficient per CPU term. Which is correct?
>
> 3) You are estimating mean e2e times. Correct? Typically we are also 
> interested in worst case end to end times. Do you intend to consider 
> that problem as well?
>
> Thanks,
>
> Patrick
>
>
>
> Alan F. Karr wrote:
>> Colleagues,
>>
>> Here is some interesting evidence that the pieces of our tool chain 
>> are actually links.
>>
>> We took all configurations tested to date with 42, 43 or 44 
>> processors (As discussed yesterday, this is in some sense "where the 
>> action is") and asked whether the /*model-derived*/ CPU utilizations 
>> along the critical path predict the /*measured*/ end-to-end times, 
>> also along the critical path. So far, the only models are considered 
>> are linear regressions. The fits are quite remarkably good.
>>
>> A PowerPoint file summarizing the results is attached. Comments and 
>> reactions are welcome. I will attempt to put this on the wiki.
>>
>> --- Alan
>>
>> -- 
>> ******************************************************************
>> * Alan F. Karr, Director                     * Tel: 919.685.9300 *
>> * National Institute of Statistical Sciences * FAX: 919.685.9310 *
>> * 19 T. W. Alexander Drive (FedEx/UPS)       * karr at niss.org     *
>> * P.O. Box 14006 (USPS)                      * www.niss.org      *
>> * Research Triangle Park, NC 27709-4006      *                   *
>> ******************************************************************
>>   
>> ------------------------------------------------------------------------
>>
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-- 
******************************************************************
* Alan F. Karr, Director                     * Tel: 919.685.9300 *
* National Institute of Statistical Sciences * FAX: 919.685.9310 *
* 19 T. W. Alexander Drive (FedEx/UPS)       * karr at niss.org     *
* P.O. Box 14006 (USPS)                      * www.niss.org      *
* Research Triangle Park, NC 27709-4006      *                   *
******************************************************************

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