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Allocate the mersenne twister used by the random number generators on the heap instead of on the stack since they tend to keep a lot of state (i.e. about 5k) around.

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This commit is contained in:
Benoit Steiner 2016-03-17 15:23:51 -07:00
parent f7329619da
commit 95b8961a9b
1 changed files with 31 additions and 18 deletions
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49
unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
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@ -364,19 +364,23 @@ template <> class UniformRandomGenerator<float> {
public: public:
static const bool PacketAccess = true; static const bool PacketAccess = true;
UniformRandomGenerator(bool deterministic = true) : m_deterministic(deterministic) { UniformRandomGenerator(bool deterministic = true) : m_deterministic(deterministic), m_generator(new std::mt19937()) {
if (!deterministic) { if (!deterministic) {
m_generator.seed(get_random_seed()); m_generator->seed(get_random_seed());
} }
} }
UniformRandomGenerator(const UniformRandomGenerator<float>& other) { UniformRandomGenerator(const UniformRandomGenerator<float>& other) {
m_generator.seed(other(0) * UINT_MAX); m_generator = new std::mt19937();
m_generator->seed(other(0) * UINT_MAX);
m_deterministic = other.m_deterministic; m_deterministic = other.m_deterministic;
} }
~UniformRandomGenerator() {
delete m_generator;
}
template<typename Index> template<typename Index>
float operator()(Index) const { float operator()(Index) const {
return m_distribution(m_generator); return m_distribution(*m_generator);
} }
template<typename Index, typename PacketType> template<typename Index, typename PacketType>
PacketType packetOp(Index i) const { PacketType packetOp(Index i) const {
@ -393,7 +397,7 @@ template <> class UniformRandomGenerator<float> {
// Make sure m_deterministic comes first to match the layout of the cpu // Make sure m_deterministic comes first to match the layout of the cpu
// version of the code. // version of the code.
bool m_deterministic; bool m_deterministic;
mutable std::mt19937 m_generator; mutable std::mt19937* m_generator;
mutable std::uniform_real_distribution<float> m_distribution; mutable std::uniform_real_distribution<float> m_distribution;
}; };
@ -401,19 +405,23 @@ template <> class UniformRandomGenerator<double> {
public: public:
static const bool PacketAccess = true; static const bool PacketAccess = true;
UniformRandomGenerator(bool deterministic = true) : m_deterministic(deterministic) { UniformRandomGenerator(bool deterministic = true) : m_deterministic(deterministic), m_generator(new std::mt19937()) {
if (!deterministic) { if (!deterministic) {
m_generator.seed(get_random_seed()); m_generator->seed(get_random_seed());
} }
} }
UniformRandomGenerator(const UniformRandomGenerator<double>& other) { UniformRandomGenerator(const UniformRandomGenerator<double>& other) {
m_generator.seed(other(0) * UINT_MAX); m_generator = new std::mt19937();
m_generator->seed(other(0) * UINT_MAX);
m_deterministic = other.m_deterministic; m_deterministic = other.m_deterministic;
} }
~UniformRandomGenerator() {
delete m_generator;
}
template<typename Index> template<typename Index>
double operator()(Index) const { double operator()(Index) const {
return m_distribution(m_generator); return m_distribution(*m_generator);
} }
template<typename Index, typename PacketType> template<typename Index, typename PacketType>
PacketType packetOp(Index i) const { PacketType packetOp(Index i) const {
@ -430,7 +438,7 @@ template <> class UniformRandomGenerator<double> {
// Make sure m_deterministic comes first to match the layout of the cpu // Make sure m_deterministic comes first to match the layout of the cpu
// version of the code. // version of the code.
bool m_deterministic; bool m_deterministic;
mutable std::mt19937 m_generator; mutable std::mt19937* m_generator;
mutable std::uniform_real_distribution<double> m_distribution; mutable std::uniform_real_distribution<double> m_distribution;
}; };
#endif #endif
@ -571,34 +579,39 @@ template <typename T> class NormalRandomGenerator {
public: public:
static const bool PacketAccess = true; static const bool PacketAccess = true;
NormalRandomGenerator(bool deterministic = true) : m_deterministic(deterministic), m_distribution(0, 1) { NormalRandomGenerator(bool deterministic = true) : m_deterministic(deterministic), m_distribution(0, 1), m_generator(new std::mt19937()) {
if (!deterministic) { if (!deterministic) {
m_generator.seed(get_random_seed()); m_generator->seed(get_random_seed());
} }
} }
NormalRandomGenerator(const NormalRandomGenerator& other) NormalRandomGenerator(const NormalRandomGenerator& other)
: m_deterministic(other.m_deterministic), m_distribution(other.m_distribution) { : m_deterministic(other.m_deterministic), m_distribution(other.m_distribution), m_generator(new std::mt19937()) {
m_generator.seed(other(0) * UINT_MAX); m_generator->seed(other(0) * UINT_MAX);
}
~NormalRandomGenerator() {
delete m_generator;
} }
template<typename Index> template<typename Index>
T operator()(Index) const { T operator()(Index) const {
return m_distribution(m_generator); return m_distribution(*m_generator);
} }
template<typename Index, typename PacketType> template<typename Index, typename PacketType>
PacketType packetOp(Index) const { PacketType packetOp(Index) const {
const int packetSize = internal::unpacket_traits<PacketType>::size; const int packetSize = internal::unpacket_traits<PacketType>::size;
EIGEN_ALIGN_MAX T values[packetSize]; EIGEN_ALIGN_MAX T values[packetSize];
for (int i = 0; i < packetSize; ++i) { for (int i = 0; i < packetSize; ++i) {
values[i] = m_distribution(m_generator); values[i] = m_distribution(*m_generator);
} }
return internal::pload<PacketType>(values); return internal::pload<PacketType>(values);
} }
private: private:
// No assignment
NormalRandomGenerator& operator = (const NormalRandomGenerator&);
bool m_deterministic; bool m_deterministic;
mutable std::normal_distribution<T> m_distribution; mutable std::normal_distribution<T> m_distribution;
mutable std::mt19937 m_generator; mutable std::mt19937* m_generator;
}; };
#elif defined (EIGEN_USE_GPU) && defined(__CUDACC__) && defined(__CUDA_ARCH__) #elif defined (EIGEN_USE_GPU) && defined(__CUDACC__) && defined(__CUDA_ARCH__)