Intel® oneAPI Data Analytics Library Developer Guide and Reference

Developer Guide and Reference

  • 2021.6
  • 04/11/2022
  • Public Content
Contents

Distributed Processing

This mode assumes that the data set is split into
nblocks
 blocks across computation nodes.

Algorithm Parameters

QR decomposition in the distributed processing mode has the following parameters:
Algorithm Parameters for QR Decomposition without Pivoting (Distributed Processing)
Parameter
Default Valude
Description
computeStep
Not applicable
The parameter required to initialize the algorithm. Can be:
  • step1Local
     - the first step, performed on local nodes
  • step2Master
     - the second step, performed on a master node
  • step3Local
     - the final step, performed on local nodes
algorithmFPType
float
The floating-point type that the algorithm uses for intermediate computations. Can be
float
 or
double
.
method
defaultDense
Performance-oriented computation method, the only method supported by the algorithm.
Use the three-step computation schema to compute QR decomposition:

Step 1 - on Local Nodes

QR Decomposition without Pivoting: Distributed Processing, Step 1 - on Local Nodes
In this step, QR decomposition 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 for QR Decomposition without Pivoting (Distributed Processing, Step 1)
Input ID
Input
data
Pointer to the LaTex Math image. numeric table that represents the LaTex Math image.-th data block on the local node. Note that each data block must have sufficient size: LaTex Math image..
The input can be an object of any class derived from
NumericTable
.
In this step, QR decomposition calculates the results described below. Pass the
Partial Result ID
 as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Partial Results for QR Decomposition without Pivoting (Distributed Processing, Step 1)
Partial Result ID
Result
outputOfStep1ForStep2
A collection that contains numeric tables each with the partial result to transmit to the master node for Step 2.
By default, these tables are objects of the
HomogenNumericTable
 class, but you can define them as objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
 class,
CSRNumericTable
 class, and
PackedTriangularMatrix
 class with the
lowerPackedTriangularMatrix
 layout.
outputOfStep1ForStep3
A collection that contains numeric tables each with the partial result to keep on the local node for Step 3.
By default, these tables are objects of the
HomogenNumericTable
 class, but you can define them as objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
,
PackedTriangularMatrix
, and
CSRNumericTable
.

Step 2 - on Master Node

QR Decomposition without Pivoting: Distributed Processing, Step 2 - on Master Node
In this step, QR decomposition accepts the input from each local node described below. Pass the
Input ID
 as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input for QR Decomposition without Pivoting (Distributed Processing, Step 2)
Input ID
Input
inputOfStep2FromStep1
A collection that contains results computed in Step 1 on local nodes (
outputOfStep1ForStep2
).
This collection can contain objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
 class and
PackedTriangularMatrix
 class with the
lowerPackedTriangularMatrix
 layout.
key
A key, a number of type int. Keys enable tracking the order in which partial results from Step 1 (
inputOfStep2FromStep1
) come to the master node, so that the partial results computed in Step 2 (
outputOfStep2ForStep3
) can be delivered back to local nodes in exactly the same order.
In this step, QR decomposition calculates the results described below. Pass the
Result ID
 or
Partial Result ID
 as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Partial Results for QR Decomposition without Pivoting (Distributed Processing, Step 2)
Partial Result ID
Result
outputOfStep2ForStep3
A collection that contains numeric tables to be split across local nodes to compute LaTex Math image..
By default, these tables are objects of the
HomogenNumericTable
 class, but you can define them as objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
 class,
CSRNumericTable
 class, and
PackedTriangularMatrix
 class with the
lowerPackedTriangularMatrix
 layout.
Output for QR Decomposition without Pivoting (Distributed Processing, Step 2)
Result ID
Result
matrixR
Pointer to the numeric table with the LaTex Math image. upper triangular matrix LaTex Math image..
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 the
PackedSymmetricMatrix
 class,
CSRNumericTable
 class, and
PackedTriangularMatrix
 class with the
lowerPackedTriangularMatrix
 layout.

Step 3 - on Local Nodes

QR Decomposition without Pivoting: Distributed Processing, Step 3 - on Local Nodes
In this step, QR decomposition 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 for QR Decomposition without Pivoting (Distributed Processing, Step 3)
Input ID
Input
inputOfStep3FromStep1
A collection that contains results computed in Step 1 on local nodes (
outputOfStep1ForStep3
).
The collection can contain objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
 and
PackedTriangularMatrix
.
inputOfStep3FromStep2
A collection that contains results computed in Step 2 on local nodes (
outputOfStep2ForStep3
).
The collection can contain objects of any class derived from
NumericTable
 except the
PackedSymmetricMatrix
 class and
PackedTriangularMatrix
 class with the
lowerPackedTriangularMatrix
 layout.
In this step, QR decomposition 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.
Output for QR Decomposition without Pivoting (Distributed Processing, Step 3)
Result ID
Result
matrixQ
Pointer to the numeric table with the LaTex Math image. matrix LaTex Math image..
By default, the result 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
.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.