Random¶
Usage
use Random;
Submodules
Support for pseudorandom number generation
This module defines an abstraction for a stream of pseudorandom numbers,
RandomStreamInterface
. Use makeRandomStream
to
create such an stream. Each stream supports methods to get the next
random number in the stream (getNext
),
to fastforward to a specific value in the stream
(skipToNth
and
getNth
), to iterate over random values
possibly in parallel (iterate
), or to
fill an array with random numbers in parallel
(fillRandom
).
The module also provides several standalone convenience functions that can be
used without manually creating a RandomStreamInterface
object.
fillRandom
fills an array with random numbers in parallelshuffle
randomly rearranges the elements of an arraypermutation
creates a random permutation and stores it in an array.
In these and other methods, generated integer values are uniformly distributed from min(T) to max(T), where T is the integral type and the boundaries are included. Generated floating point values are uniformly distributed in [0.0, 1.0] with the caveat that it currently depends on the RNG whether the boundary values 0.0 and 1.0 can be produced.
Use makeRandomStream
or the constructor for a specific RNG
implementation to get a RandomStream. See the documentation for
each RNG implementation for more information:
Note
Right now, NPBRandomStream
and
RandomStream
are available (where
RandomStream
implements the PCG algorithm). In the
future, we expect that PCGRandomStream will be available as another name
for the PCG RNG stream. At that point, RandomStream will change to a
type alias for the default RNG. The function makeRandomStream
is
available to avoid compatibility problems from this naming change.
Programs that need to specifically request PCG should do so with
makeRandomStream
until the name PCGRandomStream is available..
Note
The RandomStream API (RandomStreamInterface
) is expected to
change.

enum
RNG
{ PCG = 1, NPB = 2 }¶ Select between different supported RNG algorithms. See
PCGRandom
andNPBRandom
for details on these algorithms.

proc
fillRandom
(arr: [], seed: int(64) = SeedGenerator.oddCurrentTime, param algorithm = defaultRNG)¶ Fill an array of numeric elements with pseudorandom values in parallel using a new stream implementing
RandomStreamInterface
created specifically for this call. The first arr.size values from the stream will be assigned to the array's elements in rowmajor order. The parallelization strategy is determined by the array.Note
NPBRandom
only supports real(64), imag(64), and complex(128) numeric types.PCGRandom
supports all primitive numeric types.Arguments:  arr : [] T  The array to be filled, where T is a primitive numeric type
 seed : int(64)  The seed to use for the PRNG. Defaults to
oddCurrentTime from
RandomSupport.SeedGenerator
.  algorithm :
RNG
 A param indicating which algorithm to use. Defaults to PCG.

proc
shuffle
(arr: [], seed: int(64) = SeedGenerator.oddCurrentTime, param algorithm = RNG.PCG)¶ Shuffle the elements of an array into a random order.
Arguments:  arr  a 1D nonstrided array
 seed  the seed to use when shuffling. Defaults to
oddCurrentTime from
RandomSupport.SeedGenerator
.  algorithm :
RNG
 A param indicating which algorithm to use. Defaults to PCG.

proc
permutation
(arr: [], seed: int(64) = SeedGenerator.oddCurrentTime, param algorithm = RNG.PCG)¶ Produce a random permutation, storing it in a 1D array. The resulting array will include each value from low..high exactly once, where low and high refer to the array's domain.
Arguments:  arr  a 1D nonstrided array
 seed  the seed to use when creating the permutation. Defaults to
oddCurrentTime from
RandomSupport.SeedGenerator
.  algorithm :
RNG
 A param indicating which algorithm to use. Defaults to PCG.

proc
makeRandomStream
(type eltType, seed: int(64) = SeedGenerator.oddCurrentTime, param parSafe: bool = true, param algorithm = defaultRNG)¶ Constructs a new stream of random numbers using the specified seed and parallel safety. Ensures that the seed value meets the PRNG's constraints.
Note
The
NPBRandom
RNG will halt if provided an even seed.PCGRandom
has no restrictions on the provided seed value.Arguments:  eltType : type  The element type to be generated.
 seed : int(64)  The seed to use for the PRNG. Defaults to oddCurrentTime from
RandomSupport.SeedGenerator
.  parSafe : bool  The parallel safety setting. Defaults to true.
 algorithm :
RNG
 A param indicating which algorithm to use. Defaults to PCG.
Returns: an owned RandomStream

class
RandomStreamInterface
¶ Models a stream of pseudorandom numbers. This class is defined for documentation purposes and should not be instantiated. See
PCGRandom
andNPBRandom
for RNGs that can be instantiated. To create a random stream, usemakeRandomStream
.Note
This RandomStreamInterface is expected to change.
Note
At present, different implementations of this interface can vary in whether or not they can generate 0.0 and/or 1.0. (e.g. They can be generated by
PCGRandom
but not byNPBRandom
).Note
We plan to support general serial and parallel iterator methods on
RandomStreamInterface
; however, providing the full suite of iterators is not possible with our current parallel iterator framework. Specifically, ifRandomStreamInterface
is a follower in a zippered iteration context, there is no way for it to update the total number of random numbers generated in a safe/sane/coordinated way. We are exploring a revised leaderfollower iterator framework that would support this idiom (and other cursorbased ones). With Chapel's recent support for standalone parallel iterators, one could define a standalone parallel iterator forRandomStreamInterface
, but this effort has not yet been taken on.Note
The
RandomStreamInterface
is included here only for documentation and does not help with compilation in any way. In the future, we hope to turn it into an interface.
type
eltType
= real(64)¶ Specifies the type of value generated by the RandomStream. Not all RandomStream implementations support all types.

param
parSafe
: bool = true¶ Indicates whether or not the RandomStream needs to be parallelsafe by default. If multiple tasks interact with it in an uncoordinated fashion, this must be set to true. If it will only be called from a single task, or if only one task will call into it at a time, setting to false will reduce overhead related to ensuring mutual exclusion.

const
seed
: int(64)¶ The seed value for the PRNG. There may be constraints upon legal values depending on the specific RNG.

proc
getNext
(): eltType¶ Returns the next value in the random stream.
Returns: The next value in the random stream as type eltType
.

proc
skipToNth
(n: integral) throws¶ Advances/rewinds the stream to the nth value in the sequence. The first value is with n=1. n must be > 0, otherwise an IllegalArgumentError is thrown.
Arguments: n : integral  The position in the stream to skip to. Must be > 0.

proc
getNth
(n: integral): eltType throws¶ Advance/rewind the stream to the nth value and return it (advancing the stream by one). n must be > 0, otherwise an IllegalArgumentError is thrown. This is equivalent to
skipToNth()
followed bygetNext()
.Arguments: n : integral  The position in the stream to skip to. Must be > 0. Returns: The nth value in the random stream as type eltType
.

proc
fillRandom
(arr: [] eltType)¶ Fill the argument array with pseudorandom values. This method is identical to the standalone
fillRandom
procedure, except that it consumes random values from theRandomStreamInterface
object on which it's invoked rather than creating a new stream for the purpose of the call.Arguments: arr : [] eltType
 The array to be filled

proc
iterate
(D: domain, type resultType = eltType)¶ Returns an iterable expression for generating D.numIndices random numbers. The RNG state will be immediately advanced by D.numIndices before the iterable expression yields any values.
The returned iterable expression is useful in parallel contexts, including standalone and zippered iteration. The domain will determine the parallelization strategy.
Arguments:  D  a domain
 resultType  the type of number to yield
Returns: an iterable expression yielding random resultType values

type