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Visible to Intel only — GUID: GUID-A57F4EC5-9A8F-4FF6-93E3-D45CCF8B6FAE
Distributed Processing
This mode assumes that the data set is split into nblocks blocks across computation nodes.
Algorithm Parameters
The low order moments algorithm in the distributed processing mode has the following parameters:
Parameter |
Default Valude |
Description |
---|---|---|
computeStep |
Not applicable |
The parameter required to initialize the algorithm. Can be:
|
algorithmFPType |
float |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
method |
defaultDense |
Available methods for computation of low order moments:
|
estimatesToCompute |
estimatesAll |
Estimates to be computed by the algorithm:
|
Computation of low order moments follows the general schema described in Algorithms:
Step 1 - on Local Nodes
In this step, the low order moments algorithm accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID |
Input |
---|---|
data |
Pointer to the numeric table of size that represents the i-th data block on the local node. While the input for defaultDense, singlePassDense, or sumDense method can be an object of any class derived from NumericTable, the input for fastCSR, singlePassCSR, or sumCSR method can only be an object of the CSRNumericTable class. |
In this step, the low order moments algorithm calculates the results described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Result ID |
Result |
---|---|
nObservations |
Pointer to the numeric table that contains the number of observations processed so far on the local node. By default, this result is an object of the HomogenNumericTable class, but you can define the result as an object of any class derived from NumericTable except CSRNumericTable. |
Partial characteristics computed so far on the local node, each in a numeric table. By default, each table is an object of the HomogenNumericTable class, but you can define the tables as objects of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.
Result ID |
Result |
---|---|
partialMinimum |
Partial minimums |
partialMaximum |
Partial maximums |
partialSum |
Partial sums |
partialSumSquares |
Partial sums of squares |
partialSumSquaresCentered |
Partial sums of squared differences from the means |
Step 2 - on Master Node
In this step, the low order moments algorithm accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID |
Input |
---|---|
partialResults |
A collection that contains numeric tables with partial results computed in Step 1 on local nodes (six numeric tables from each local node). These numeric tables can be objects of any class derived from the NumericTable class except PackedSymmetricMatrix and PackedTriangularMatrix. |
In this step, the low order moments algorithm calculates the results described in the following table. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Result ID |
Characteristic |
---|---|
minimum |
Minimums |
maximum |
Maximums |
sum |
Sums |
sumSquares |
Sums of squares |
sumSquaresCentered |
Sums of squared differences from the means |
mean |
Estimates for the means |
secondOrderRawMoment |
Estimates for the second order raw moments |
variance |
Estimates for the variances |
standardDeviation |
Estimates for the standard deviations |
variation |
Estimates for the variations |
Product and Performance Information |
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Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex. Notice revision #20201201 |