rand - Create codistributed array of uniformly distributed random numbers - MATLAB (original) (raw)

Create codistributed array of uniformly distributed random numbers

Syntax

Description

`cR` = rand([n](#mw%5F5ba576ca-eee1-4794-8a1b-48e024502161),[codist](#mw%5Fa6246d27-ce67-4a35-b077-35e3dfa44871)) creates an n-by-n codistributed matrix of uniformly distributed random numbers and uses codist to specify the distribution of the array values across the workers. Each element incR is between 0 and 1.

Specify codist as "codistributed" to use the default codistributor1d distribution scheme or the distribution scheme defined by a codistributor1d or codistributor2dbc object.

When you create the codistributed array in a communicating job or spmd block, the function creates an array on each worker. If you create a codistributed array outside of a communicating job or spmd block, the array is stored only on the worker or client that creates the codistributed array.

By default, the codistributed array has the underlying type double.

example

`cR` = rand([sz](#mw%5Fcfee96c3-514f-4f66-a73c-2a37201eedc2),[codist](#mw%5Fa6246d27-ce67-4a35-b077-35e3dfa44871)) creates a codistributed array of uniformly distributed random numbers where the size vector sz defines the size of cR. For example,rand([2 3],"codistributed") creates a 2-by-3 codistributed array.

`cR` = rand([sz1,...,szN](#mw%5F001e395a-3595-48f9-acbe-eb19235ffaf8),[codist](#mw%5Fa6246d27-ce67-4a35-b077-35e3dfa44871)) creates an sz1-by-...-by-szN codistributed array of uniformly distributed random numbers where sz1,...,szN indicates the size of each dimension.

`cR` = rand(___,[datatype](#mw%5F237fbdac-cf7e-4b46-b7d8-e8c8e5f40c42),[codist](#mw%5Fa6246d27-ce67-4a35-b077-35e3dfa44871)) creates a codistributed array of uniformly distributed random numbers with the underlying type datatype. For example,rand(1,"single","codistributed") creates a codistributed single-precision random number. You can use this syntax with any of the size arguments in the previous syntaxes. You must specify codist after the array size and data type arguments.

`cR` = rand(___,"noCommunication") creates a codistributed array of uniformly distributed random numbers without using communication between workers.

When you create very large arrays or your communicating job or spmd block uses many workers, worker-worker communication can slow down array creation. Use this syntax to improve the performance of your code by removing the time required for worker-worker communication.

Tip

When you use this syntax, some error checking steps are skipped. Use this syntax to improve the performance of your code after you prototype your code without specifying "noCommunication".

You must specify "noCommunication" after the size, data type andcodist arguments.

`cR` = rand(___,like=[p](#mw%5Fa464987c-4764-4c43-b114-c016ac376c3b)) uses the array p to create a codistributed array of uniformly distributed random numbers. You can also specify "noCommunication" as part of the function call.

The returned array cR has the same underlying type, sparsity, and complexity (real or complex) as p.

Examples

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Create Codistributed Rand Matrix

Create a 1000-by-1000 codistributed double matrix ofrands, distributed by its second dimension (columns).

spmd(4) C = rand(1000,"codistributed"); end

With four workers, each worker contains a 1000-by-250 local piece ofC.

Create a 1000-by-1000 codistributed single matrix ofrands, distributed by its columns.

spmd(4) codist = codistributor1d(2,100*[1:spmdSize]); C = rand(1000,1000,"single",codist); end

Each worker contains a 100-by-spmdIndex local piece ofC.

Input Arguments

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n — Size of square matrix

integer

Size of the square matrix, specified as an integer.

• If n is 0, then cR is an empty matrix.
• If n is negative, then the function treats it as0.

codist — Distribution scheme for codistributed array

"codistributed" | codistributor1d object | codistributor2dbc object

Distribution scheme for codistributed array, specified as one of these options:

• "codistributed" — Uses the default distribution scheme defined by the default codistributor1d object.
• codistributor1d object — Uses the one-dimensional distribution scheme defined in acodistributor1d object. To use the default 1-D distribution scheme, you can specify the codistributor1d function without arguments.
• codistributor2dbc object — Uses the two-dimensional block-cyclic distribution scheme defined in acodistributor2dbc object. To use the default 2-D block-cyclic distribution scheme, you can specify thecodistributor2dbc function without arguments.

sz — Size of each dimension (as a row vector)

integer row vector

Size of each dimension, specified as an integer row vector. Each element of this vector indicates the size of the corresponding dimension:

• If the size of any dimension is 0, thencR is an empty array.
• If the size of any dimension is negative, then the function treats it as0.
• Beyond the second dimension, rand ignores trailing dimensions with a size of 1. For example, rand([3 1 1 1],"codistributed") produces a 3-by-1 codistributed vector of uniformly distributed random numbers.

Example: sz = [2 3 4] creates a 2-by-3-by-4 codistributed array.

sz1,...,szN — Size of each dimension (as separate arguments)

integer values

Size of each dimension, specified as separate arguments of integer values.

• If the size of any dimension is 0, thencR is an empty array.
• If the size of any dimension is negative, then the function treats it as0.
• Beyond the second dimension, the function ignores trailing dimensions with a size of 1.

datatype — Array underlying data type

"double" (default) | "single" | "logical" | "int8" | "uint8" | ...

Underlying data type of the returned array, specified as one of these options:

• "double"
• "single"
• "logical"
• "int8"
• "uint8"
• "int16"
• "uint16"
• "int32"
• "uint32"
• "int64"
• "uint64"

p — Prototype of array to create

codistributed array

Prototype of array to create, specified as a codistributed array.

If you do not specify the datatype, the resulting codistributed array has the same underlying type, sparsity, and complexity (real or complex) asp.

Version History

Introduced in R2006b