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S5R3 Task Crunch Time Ready Reckoner V7C
Important Points To Read
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All times are in seconds.
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Predictions are designed for data from a single machine and a given application version only.
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For data entry particularly :
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Minumum two inputs, and generally the more the better.
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Rigorous input checking applies to CSV input into left hand side text area/pane.
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Three or four data values per line.
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Values interpreted in order as FREQUENCY,
SEQUENCE_NUMBER,
RUNTIME and
APP_VERSION respectively.
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FREQUENCY interpreted as floating point.
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SEQUENCE_NUMBER interpreted as integer.
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RUNTIME interpreted as floating point.
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if provided, APP_VERSION is accepted only if either
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the word "mixed" ( lower case )
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a floating point
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Comma to separate each value.
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No spaces within data values ( elsewhere trimming occurs ).
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Abberant lines that do not parse as above will be discarded.
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Each line represents a data point for analysis. There is no assumption of any ordering from one line and the next.
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Choose a spread of task phases for a given frequency. Analysis ouput will be ascending sorted by levels of APP_VERSION, FREQUENCY and SEQUENCE_NUMBER.
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An expected peak, average and trough runtimes plus variance and error is calculated given all qualifying tasks at each given frequency. This is subject to triage as regards fitness to predict ( complex ).
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The right hand pane is editable. Any changes you make will be reflected when "Inputs and Outputs Summary" is selected.
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If no error is quoted then none applies. Zero will be explicit.
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NaN in a field indicates either an bad input somewhere earlier,
or an unacceptable calculation result ( various causes ).
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This an UNOFFICIAL toy. No warranties are implied or express whatsoever.
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I would be very glad to receive any & all feedback ! ;-)
Enjoy!
Cheers, Mike
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For a sequence of tasks we will attempt an estimation of runtime parameters.
This depends upon the frequency F,
sequence number S,
running time T
[
+/- application version V
]
for as many entries as your runtime system can manage. There is no pre-programmed limit, and expect noticeable pauses for large data sets!
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