Distributed Processing
Algorithm Parameters
Parameter
 Default Value
 Description
 

computeStep  Not applicable
 The parameter required to initialize the algorithm. Can be:
 
algorithmFPType  float  The floatingpoint type that the algorithm uses for intermediate computations. Can be
float or
double .
 
method  defaultDense  Available methods for computation of correlation and variancecovariance matrices:
 
outputMatrixType  covarianceMatrix  The type of the output matrix. Can be:

Step 1  on Local Nodes
Input ID
 Input
 

data  Pointer to the
n _{i} x
p numeric table 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.

Result ID
 Result
 

nObservations  Pointer to the 1 x 1 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 the
p x
p numeric table with the crossproduct 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
CSRNumericTable .
 
sum  Pointer to the 1 x
p 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
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 .

Result ID
 Result
 

covariance  Use when
outputMatrixType =covarianceMatrix . Pointer to the numeric table with the
p x
p variancecovariance 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
p x
p 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 1 x
p 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 nonIntel 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. Microprocessordependent 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
