Distributed Processing
This mode assumes that the data set is split into
nblocks
blocks across computation nodes.Algorithm Parameters
The correlation and variance-covariance matrices 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:
|
outputMatrixType | covarianceMatrix | The type of the output matrix. Can be:
|
Computation of correlation and variance-covariance matrices follows the general schema described in Algorithms:
Step 1 - on Local Nodes
In this step, the correlation and variance-covariance matrices 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 correlation and variance-covariance matrices 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 . |
crossProduct | Pointer to
numeric table with the cross-product matrix computed so far on the local node.By default, this table is an object of the HomogenNumericTable class,
but you can define the result as an object of any class derived from NumericTable
except PackedSymmetricMatrix , PackedTriangularMatrix , and CSRNumericTable . |
sum | Pointer to
numeric table with partial sums computed so far on the local node.By default, this table is an object of the HomogenNumericTable class,
but you can define the result as an object of any class derived from NumericTable
except PackedSymmetricMatrix , PackedTriangularMatrix , and CSRNumericTable . |
Step 2 - on Master Node
In this step, the correlation and variance-covariance matrices 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 results computed in Step 1 on local nodes ( nObservations , crossProduct , and sum ).The collection can contain objects of any class derived from the NumericTable class
except PackedSymmetricMatrix and PackedTriangularMatrix . |
In this step, the correlation and variance-covariance matrices 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 | Result |
|---|---|
covariance | Use when outputMatrixType``=``covarianceMatrix . Pointer to the numeric table with the
variance-covariance matrix.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 PackedTriangularMatrix and CSRNumericTable . |
correlation | Use when outputMatrixType``=``correlationMatrix . Pointer to the numeric table with the
correlation matrix.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 PackedTriangularMatrix and CSRNumericTable . |
mean | Pointer to the
numeric table with means.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 PackedTriangularMatrix , PackedSymmetricMatrix , and CSRNumericTable . |
Optimization Notice |
|---|
Intel’s compilers may or may not optimize to the same degree for
non-Intel microprocessors for optimizations that are not unique to
Intel microprocessors. These optimizations include SSE2, SSE3, and
SSSE3 instruction sets and other optimizations. Intel does not
guarantee the availability, functionality, or effectiveness of any
optimization on microprocessors not manufactured by Intel.
Microprocessor-dependent optimizations in this product are intended
for use with Intel microprocessors. Certain optimizations not
specific to Intel microarchitecture are reserved for Intel
microprocessors. Please refer to the applicable product User and
Reference Guides for more information regarding the specific
instruction sets covered by this notice. Notice revision #20110804 |