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TMVA, DNN, reduce memory allocation in minimizer #262

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71aa5c2
Ontology: steepest gradient descent. Allow for small variations in th…
re-cursion Jul 18, 2016
ced47cd
started to add reuse of memory for maximizing algorithm
re-cursion Sep 19, 2016
3f1dd9a
Ontology: steepest gradient descent. Allow for small variations in th…
re-cursion Jul 18, 2016
b782b0b
started to add reuse of memory for maximizing algorithm
re-cursion Sep 19, 2016
e720a88
resuse vector within the same thread. Avoid getting the memory at eac…
re-cursion Sep 22, 2016
ab8e3ee
resolved conflict. Two differing versions of reducing memory allocati…
re-cursion Sep 22, 2016
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started to add reuse of memory for maximizing algorithm
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@re-cursion
re-cursion committed Sep 22, 2016
commit b782b0bdaf0a239b494cfc24ac1788e3e0185306
26 changes: 26 additions & 0 deletions tmva/tmva/inc/TMVA/NeuralNet.h
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Expand Up @@ -39,6 +39,7 @@
#include <thread>
#include <future>
#include <type_traits>
#include <mutex>

#include "Pattern.h"
#include "Monitoring.h"
Expand Down Expand Up @@ -372,6 +373,31 @@ namespace TMVA
double m_alpha; ///< internal parameter (learningRate)
double m_beta; ///< internal parameter (momentum)
std::vector<double> m_prevGradients; ///< vector remembers the gradients of the previous step





/* typedef std::smart_ptr<std::vector<double> > VecPtr; */
/* typedef std::vector<VecPtr> VecPool; */
/* VecPool m_local; */
/* VecPool m_localInUse; */
/* std::mutex m_vec_mutex; */


/* VecPtr getVec () */
/* { */
/* std::lock_guard<std::mutex> lock (m_vec_mutex); */

/* } */

/* void releaseVec (VecPtr vecPtr) */
/* { */
/* std::lock_guard<std::mutex> lock (m_vec_mutex); */
/* VecPool::iterator it = m_localInUse.find (vecPtr); */
/* m_local.push_back (*it); */
/* m_localInUse.erase (it); */
/* } */
};


Expand Down