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

[Raj Rajkumar]

Hi Gautam:

Unfortunately, June 5th does not work for me (I'm in Taiwan).   Thanks,

---
Raj

Gautam Thaker wrote:
> Raj Rajkumar wrote:
>> Hi Alan, Patrick and Gautam:
>>
>> Can we have a short discussion about computing e2e times in general?  
>> I apologize if this was discussed in some recent meetings and/or 
>> telecons; I may not have been present when these discussions occurred.
>>
>> Clearly, e2e delay is a sum of delay components along the entire path 
>> (processors and links) of an application string.  There are 
>> worst-case and average-case considerations.
>>
>> Beyond the above, real-time scheduling theory holds that when 
>> individual components have different arrival rates (e.g. periods), 
>> execution times and a scheduling policy (preemptive or not, fixed 
>> priority or not), the response time for a task on a processor (or a 
>> communication link) is a function of not just utilizations but also 
>> the individual parameters (C's and T's of the task at hand + all its 
>> higher priority tasks, not just the total utilization).   Just having 
>> e2e times be a function of utilizations runs counter to scheduling 
>> theory (+ real measurements, one would argue).
>>
>> Thoughts?  Thanks,
>
> Hi Raj:
>
> I think Alan was probably not suggesting that traditional scheduling 
> theory be dropped in any way but just seeking to understand the 
> current data better. Thus, i see his use of 6 CPU utils as just 
> something he is looking at for the time being. I am not surprised if 
> good model fit can be found for *average* end to end time and CPU loads.
>
> I believe we do have enough time in CADYNCE the seedling to talk of 
> all these things. we can do more teleconferences or propose a 1 day 
> meeting, no one has yet responded to my proposal for June 5th (though 
> may be best to wait till Todd's May 24th meeting to see what is best.)
>
> Gautam
>
>>
>> ---
>> Raj
>>
>> Alan F. Karr wrote:
>>> 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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>