warpcore: warpcore Namespace Reference

Namespaces
	checks
	assertion helpers

	defaults
	default types and values

	detail

	hashers
	hash functions

	kernels
	CUDA kernels.

	probing_schemes
	probing scheme iterators

	status_handlers
	status handlers to use for per key status information

	storage
	storage classes

	tags
	type tags

Classes
class	BloomFilter
	bloom filter More...

class	BucketListHashTable
	bucket list hash table More...

class	CountingHashTable
	counting hash table More...

class	HashSet
	hash set More...

struct	ArrayBucket

class	MultiBucketHashTable
	multi-value hash table More...

class	MultiValueHashTable
	multi-value hash table More...

class	SingleValueHashTable
	single-value hash table More...

class	Status
	status/error indicator More...

Typedefs
using	index_t = std::uint64_t

using	status_base_t = std::uint32_t

Functions
template<class T >
constexpr __host____device__ T	transform_range (const T x, const T a, const T b, const T c, const T d) noexcept
	transforms interval (a, b) into interval (c, d) More...

template<class T , class Rng >
__host__ void	uniform_distribution (T *out, std::uint64_t n, std::uint32_t seed) noexcept
	generates `n` uniform random elements on a CUDA device More...

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	uniform_distribution (std::uint32_t *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint64_t>>
__host__ void	uniform_distribution (std::uint64_t *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	uniform_distribution (float *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	uniform_distribution (double *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class T , class Rng >
__host__ void	unique_distribution (T *out, std::uint64_t n, std::uint32_t seed) noexcept
	generates `n` unique random elements on a CUDA device More...

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	unique_distribution (std::uint32_t *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint64_t>>
__host__ void	unique_distribution (std::uint64_t *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	unique_distribution (float *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class Rng = kiss::Kiss<std::uint32_t>>
__host__ void	unique_distribution (double *out, std::uint64_t n, std::uint32_t seed) noexcept

template<class T , class Rng = kiss::Kiss<std::uint32_t>, class P = double>
__host__ void	zipf_distribution (T in, std::uint64_t n_in, T out, std::uint64_t n_out, P s, std::uint32_t seed) noexcept
	generates `n` zipf distributed random elements on a CUDA device More...

template<class OStream >
OStream &	operator<< (OStream &os, Status status)

Typedef Documentation

◆ index_t

using warpcore::index_t = typedef std::uint64_t

Definition at line 23 of file base.cuh.

◆ status_base_t

using warpcore::status_base_t = typedef std::uint32_t

Definition at line 24 of file base.cuh.

Function Documentation

◆ operator<<()

template<class OStream >

OStream& warpcore::operator<<	(	OStream &	os,
		Status	status
	)

Definition at line 217 of file status.cuh.

◆ transform_range()

template<class T >

constexpr __host____device__ T warpcore::transform_range	(	const T	x,
		const T	a,
		const T	b,
		const T	c,
		const T	d
	)

inlineconstexprnoexcept

transforms interval (a, b) into interval (c, d)

Template Parameters

T data type

Parameters

[in]	x	value to be transformed into new interval
[in]	a	lower bound of input interval
[in]	b	upper bound of input interval
[in]	c	lower bound of output interval
[in]	d	upper bound of output interval

Returns: value in new interval

Definition at line 24 of file random_distributions.cuh.

◆ uniform_distribution() [1/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::uniform_distribution	(	double *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 126 of file random_distributions.cuh.

◆ uniform_distribution() [2/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::uniform_distribution	(	float *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 113 of file random_distributions.cuh.

◆ uniform_distribution() [3/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::uniform_distribution	(	std::uint32_t *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 87 of file random_distributions.cuh.

◆ uniform_distribution() [4/5]

template<class Rng = kiss::Kiss<std::uint64_t>>

__host__ void warpcore::uniform_distribution	(	std::uint64_t *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 100 of file random_distributions.cuh.

◆ uniform_distribution() [5/5]

template<class T , class Rng >

__host__ void warpcore::uniform_distribution	(	T *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

generates n uniform random elements on a CUDA device

Template Parameters

T	data type to be generated
Rng	type of random number generator

Parameters

[out]	out	pointer to the output array
[in]	n	number of elements to generate
[in]	seed	initial random seed for the RNG

Definition at line 52 of file random_distributions.cuh.

◆ unique_distribution() [1/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::unique_distribution	(	double *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 237 of file random_distributions.cuh.

◆ unique_distribution() [2/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::unique_distribution	(	float *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 224 of file random_distributions.cuh.

◆ unique_distribution() [3/5]

template<class Rng = kiss::Kiss<std::uint32_t>>

__host__ void warpcore::unique_distribution	(	std::uint32_t *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 198 of file random_distributions.cuh.

◆ unique_distribution() [4/5]

template<class Rng = kiss::Kiss<std::uint64_t>>

__host__ void warpcore::unique_distribution	(	std::uint64_t *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

Definition at line 211 of file random_distributions.cuh.

◆ unique_distribution() [5/5]

template<class T , class Rng >

__host__ void warpcore::unique_distribution	(	T *	out,
		std::uint64_t	n,
		std::uint32_t	seed
	)

inlinenoexcept

generates n unique random elements on a CUDA device

Template Parameters

T	data type to be generated
Rng	type of random number generator

Parameters

[out]	out	pointer to the output array
[in]	n	number of elements to generate
[in]	seed	initial random seed for the RNG

Definition at line 146 of file random_distributions.cuh.

◆ zipf_distribution()

template<class T , class Rng = kiss::Kiss<std::uint32_t>, class P = double>

__host__ void warpcore::zipf_distribution	(	T *	in,
		std::uint64_t	n_in,
		T *	out,
		std::uint64_t	n_out,
		P	s,
		std::uint32_t	seed
	)

inlinenoexcept

generates n zipf distributed random elements on a CUDA device

Template Parameters

T	data type to be generated
Rng	type of random number generator
P	data type used for probabilities

Parameters

[in]	in	set of unique elements to be considered
[in]	n_in	cardinality of input set
[out]	out	pointer to the output array
[in]	n_out	number of elements to generate
[in]	s	skew of the distribution
[in]	seed	initial random seed for the RNG

Definition at line 261 of file random_distributions.cuh.

warpcore 0.0.1 Hashing at the Speed of Light on modern CUDA-accelerators

Namespaces

Classes

Typedefs

Functions

Typedef Documentation

◆ index_t

◆ status_base_t

Function Documentation

◆ operator<<()

◆ transform_range()

◆ uniform_distribution() [1/5]

◆ uniform_distribution() [2/5]

◆ uniform_distribution() [3/5]

◆ uniform_distribution() [4/5]

◆ uniform_distribution() [5/5]

◆ unique_distribution() [1/5]

◆ unique_distribution() [2/5]

◆ unique_distribution() [3/5]

◆ unique_distribution() [4/5]

◆ unique_distribution() [5/5]

◆ zipf_distribution()