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

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 numeric table that represents the -th data block on the local node. Note that each data block must have sufficient size: .
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

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 .
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 upper triangular 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 the
PackedSymmetricMatrix
class,
CSRNumericTable
class, and
PackedTriangularMatrix
class with the
lowerPackedTriangularMatrix
layout.

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 matrix .
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.