Files
project_6/cccl_upstream/thrust/thrust/random/normal_distribution.h
EngineX CI 56fd68e7dd [INFRA] Import NVIDIA/CCCL upstream as optimization reference library
CCCL (CUDA C++ Core Libraries) provides:
- CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk)
- Thrust: high-level parallel algorithms (transform_reduce, sort, scan)
- libcudacxx: CUDA C++ standard library (atomics, barriers, memory)
- cudax: experimental features (memory resources, allocators)
- Tuning policies: per-SM hardware-specific algorithm parameters

Competition optimization vectors mapped to CCCL:
- Output TPS (83% weight): warp_reduce, block_reduce, device_topk
- Input TPS (14% weight): device_scan, block_load, prefetch
- Cache TPS (3% weight): prefix caching strategy patterns
- Memory (0.9 util): pooled/cached/buddy allocators

Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only)
License: Apache-2.0
2026-07-30 09:35:51 +00:00

244 lines
8.8 KiB
C++

// SPDX-FileCopyrightText: Copyright (c) 2008-2013, NVIDIA Corporation. All rights reserved.
// SPDX-License-Identifier: Apache-2.0
/*! \file normal_distribution.h
* \brief A normal (Gaussian) distribution of real-valued numbers.
*/
#pragma once
#include <thrust/detail/config.h>
#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
# pragma GCC system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
# pragma clang system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
# pragma system_header
#endif // no system header
#include <thrust/random/detail/normal_distribution_base.h>
#include <thrust/random/detail/random_core_access.h>
#include <cuda/std/__host_stdlib/istream>
#include <cuda/std/__host_stdlib/ostream>
#include <cuda/std/__utility/pair.h>
THRUST_NAMESPACE_BEGIN
namespace random
{
/*! \addtogroup random_number_distributions
* \{
*/
/*! \class normal_distribution
* \brief A \p normal_distribution random number distribution produces floating point
* Normally distributed random numbers.
*
* \tparam RealType The type of floating point number to produce.
*
* The following code snippet demonstrates examples of using a \p normal_distribution with a
* random number engine to produce random values drawn from the Normal distribution with a given
* mean and variance:
*
* \code
* #include <thrust/random/linear_congruential_engine.h>
* #include <thrust/random/normal_distribution.h>
*
* int main()
* {
* // create a minstd_rand object to act as our source of randomness
* thrust::minstd_rand rng;
*
* // create a normal_distribution to produce floats from the Normal distribution
* // with mean 2.0 and standard deviation 3.5
* thrust::random::normal_distribution<float> dist(2.0f, 3.5f);
*
* // write a random number to standard output
* std::cout << dist(rng) << '\n';
*
* // write the mean of the distribution, just in case we forgot
* std::cout << dist.mean() << '\n';
*
* // 2.0 is printed
*
* // and the standard deviation
* std::cout << dist.stddev() << '\n';
*
* // 3.5 is printed
*
* return 0;
* }
* \endcode
*/
template <typename RealType = double>
class normal_distribution : public detail::normal_distribution_base<RealType>::type
{
private:
using super_t = typename detail::normal_distribution_base<RealType>::type;
public:
// types
/*! \typedef result_type
* \brief The type of the floating point number produced by this \p normal_distribution.
*/
using result_type = RealType;
/*! \typedef param_type
* \brief The type of the object encapsulating this \p normal_distribution's parameters.
*/
using param_type = ::cuda::std::pair<RealType, RealType>;
// constructors and reset functions
/*! This constructor creates a new \p normal_distribution from two values defining the
* half-open interval of the distribution.
*
* \param mean The mean (expected value) of the distribution. Defaults to \c 0.0.
* \param stddev The standard deviation of the distribution. Defaults to \c 1.0.
*/
_CCCL_HOST_DEVICE explicit normal_distribution(RealType mean = 0.0, RealType stddev = 1.0);
/*! This constructor creates a new \p normal_distribution from a \p param_type object
* encapsulating the range of the distribution.
*
* \param parm A \p param_type object encapsulating the parameters (i.e., the mean and standard deviation) of the
* distribution.
*/
_CCCL_HOST_DEVICE explicit normal_distribution(const param_type& parm);
/*! Calling this member function guarantees that subsequent uses of this
* \p normal_distribution do not depend on values produced by any random
* number generator prior to invoking this function.
*/
_CCCL_HOST_DEVICE void reset();
// generating functions
/*! This method produces a new Normal random integer drawn from this \p normal_distribution's
* range using a \p UniformRandomNumberGenerator as a source of randomness.
*
* \param urng The \p UniformRandomNumberGenerator to use as a source of randomness.
*/
template <typename UniformRandomNumberGenerator>
_CCCL_HOST_DEVICE result_type operator()(UniformRandomNumberGenerator& urng);
/*! This method produces a new Normal random integer as if by creating a new \p normal_distribution
* from the given \p param_type object, and calling its <tt>operator()</tt> method with the given
* \p UniformRandomNumberGenerator as a source of randomness.
*
* \param urng The \p UniformRandomNumberGenerator to use as a source of randomness.
* \param parm A \p param_type object encapsulating the parameters of the \p normal_distribution
* to draw from.
*/
template <typename UniformRandomNumberGenerator>
_CCCL_HOST_DEVICE result_type operator()(UniformRandomNumberGenerator& urng, const param_type& parm);
// property functions
/*! This method returns the value of the parameter with which this \p normal_distribution
* was constructed.
*
* \return The mean (expected value) of this \p normal_distribution's output.
*/
_CCCL_HOST_DEVICE result_type mean() const;
/*! This method returns the value of the parameter with which this \p normal_distribution
* was constructed.
*
* \return The standard deviation of this \p uniform_real_distribution's output.
*/
_CCCL_HOST_DEVICE result_type stddev() const;
/*! This method returns a \p param_type object encapsulating the parameters with which this
* \p normal_distribution was constructed.
*
* \return A \p param_type object encapsulating the parameters (i.e., the mean and standard deviation) of this \p
* normal_distribution.
*/
_CCCL_HOST_DEVICE param_type param() const;
/*! This method changes the parameters of this \p normal_distribution using the values encapsulated
* in a given \p param_type object.
*
* \param parm A \p param_type object encapsulating the new parameters (i.e., the mean and variance) of this \p
* normal_distribution.
*/
_CCCL_HOST_DEVICE void param(const param_type& parm);
/*! This method returns the smallest floating point number this \p normal_distribution can potentially produce.
*
* \return The lower bound of this \p normal_distribution's half-open interval.
*/
_CCCL_HOST_DEVICE result_type min THRUST_PREVENT_MACRO_SUBSTITUTION() const;
/*! This method returns the smallest number larger than largest floating point number this \p
* uniform_real_distribution can potentially produce.
*
* \return The upper bound of this \p normal_distribution's half-open interval.
*/
_CCCL_HOST_DEVICE result_type max THRUST_PREVENT_MACRO_SUBSTITUTION() const;
/*! \cond
*/
private:
param_type m_param;
friend struct thrust::random::detail::random_core_access;
_CCCL_HOST_DEVICE bool equal(const normal_distribution& rhs) const;
template <typename CharT, typename Traits>
std::basic_ostream<CharT, Traits>& stream_out(std::basic_ostream<CharT, Traits>& os) const;
template <typename CharT, typename Traits>
std::basic_istream<CharT, Traits>& stream_in(std::basic_istream<CharT, Traits>& is);
/*! \endcond
*/
}; // end normal_distribution
/*! This function checks two \p normal_distributions for equality.
* \param lhs The first \p normal_distribution to test.
* \param rhs The second \p normal_distribution to test.
* \return \c true if \p lhs is equal to \p rhs; \c false, otherwise.
*/
template <typename RealType>
_CCCL_HOST_DEVICE bool operator==(const normal_distribution<RealType>& lhs, const normal_distribution<RealType>& rhs);
/*! This function checks two \p normal_distributions for inequality.
* \param lhs The first \p normal_distribution to test.
* \param rhs The second \p normal_distribution to test.
* \return \c true if \p lhs is not equal to \p rhs; \c false, otherwise.
*/
template <typename RealType>
_CCCL_HOST_DEVICE bool operator!=(const normal_distribution<RealType>& lhs, const normal_distribution<RealType>& rhs);
/*! This function streams a normal_distribution to a \p std::basic_ostream.
* \param os The \p basic_ostream to stream out to.
* \param d The \p normal_distribution to stream out.
* \return \p os
*/
template <typename RealType, typename CharT, typename Traits>
std::basic_ostream<CharT, Traits>&
operator<<(std::basic_ostream<CharT, Traits>& os, const normal_distribution<RealType>& d);
/*! This function streams a normal_distribution in from a std::basic_istream.
* \param is The \p basic_istream to stream from.
* \param d The \p normal_distribution to stream in.
* \return \p is
*/
template <typename RealType, typename CharT, typename Traits>
std::basic_istream<CharT, Traits>& operator>>(std::basic_istream<CharT, Traits>& is, normal_distribution<RealType>& d);
/*! \} // end random_number_distributions
*/
} // namespace random
using random::normal_distribution;
THRUST_NAMESPACE_END
#include <thrust/random/detail/normal_distribution.inl>