firstprivate clause in OpenMP does not work
0
I have a loop which operate with class objects and functions. Also it calculate several sum values. I've try to parallel it with OpenMP:
Network net = *m_pNetwork;
TrainingSet tran = trainingSet;
omp_set_num_threads(4);
#pragma omp parallel for reduction(+:MSE, incorrectEntries) firstprivate(tran, net) lastprivate(net) private(outputIdx)
for (int i = 0; i < tran.size(); i++)
{
net->Evaluate(tran[i].m_inputs);
Backpropagate(tran[i].m_expectedOutputs);
// Check all outputs from neural network against desired values
bool resultCorrect = true;
for (outputIdx = 0; outputIdx < net->m_numOutputs; outputIdx++)
{
if (net->m_clampedOutputs[outputIdx] != tran[i].m_expectedOutputs[outputIdx])
{
resultCorrect = false;
}
MSE += pow((net->m_outputNeurons[outputIdx] - tran[i].m_expectedOutputs[outputIdx]), 2);
}
if (!resultCorrect)
{
//#pragma omp atomic
incorrectEntries++;
}
}
*m_pNetwork = net;
My problem is the sum values are the same each iterations. So what i've not properly done?
c++ parallel-processing synchronization openmp
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
|
show 4 more comments
0
I have a loop which operate with class objects and functions. Also it calculate several sum values. I've try to parallel it with OpenMP:
Network net = *m_pNetwork;
TrainingSet tran = trainingSet;
omp_set_num_threads(4);
#pragma omp parallel for reduction(+:MSE, incorrectEntries) firstprivate(tran, net) lastprivate(net) private(outputIdx)
for (int i = 0; i < tran.size(); i++)
{
net->Evaluate(tran[i].m_inputs);
Backpropagate(tran[i].m_expectedOutputs);
// Check all outputs from neural network against desired values
bool resultCorrect = true;
for (outputIdx = 0; outputIdx < net->m_numOutputs; outputIdx++)
{
if (net->m_clampedOutputs[outputIdx] != tran[i].m_expectedOutputs[outputIdx])
{
resultCorrect = false;
}
MSE += pow((net->m_outputNeurons[outputIdx] - tran[i].m_expectedOutputs[outputIdx]), 2);
}
if (!resultCorrect)
{
//#pragma omp atomic
incorrectEntries++;
}
}
*m_pNetwork = net;
My problem is the sum values are the same each iterations. So what i've not properly done?
c++ parallel-processing synchronization openmp
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
1
netis a pointer. In a parallel section, each thread has its own copy ofnet, however, they all point to the same object. IsNetwork::evaluatethread-safe?
– Daniel Langr
Nov 28 '18 at 13:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
1
No idea what these sum values are. However, note that now,netwill be after parallel loop set to a single privatenetof the thread that run the last iteration. Is it what you want? (Seelastprivatedocs.)
– Daniel Langr
Nov 28 '18 at 14:23
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51
|
show 4 more comments
0
0
0
I have a loop which operate with class objects and functions. Also it calculate several sum values. I've try to parallel it with OpenMP:
Network net = *m_pNetwork;
TrainingSet tran = trainingSet;
omp_set_num_threads(4);
#pragma omp parallel for reduction(+:MSE, incorrectEntries) firstprivate(tran, net) lastprivate(net) private(outputIdx)
for (int i = 0; i < tran.size(); i++)
{
net->Evaluate(tran[i].m_inputs);
Backpropagate(tran[i].m_expectedOutputs);
// Check all outputs from neural network against desired values
bool resultCorrect = true;
for (outputIdx = 0; outputIdx < net->m_numOutputs; outputIdx++)
{
if (net->m_clampedOutputs[outputIdx] != tran[i].m_expectedOutputs[outputIdx])
{
resultCorrect = false;
}
MSE += pow((net->m_outputNeurons[outputIdx] - tran[i].m_expectedOutputs[outputIdx]), 2);
}
if (!resultCorrect)
{
//#pragma omp atomic
incorrectEntries++;
}
}
*m_pNetwork = net;
My problem is the sum values are the same each iterations. So what i've not properly done?
c++ parallel-processing synchronization openmp
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
I have a loop which operate with class objects and functions. Also it calculate several sum values. I've try to parallel it with OpenMP:
Network net = *m_pNetwork;
TrainingSet tran = trainingSet;
omp_set_num_threads(4);
#pragma omp parallel for reduction(+:MSE, incorrectEntries) firstprivate(tran, net) lastprivate(net) private(outputIdx)
for (int i = 0; i < tran.size(); i++)
{
net->Evaluate(tran[i].m_inputs);
Backpropagate(tran[i].m_expectedOutputs);
// Check all outputs from neural network against desired values
bool resultCorrect = true;
for (outputIdx = 0; outputIdx < net->m_numOutputs; outputIdx++)
{
if (net->m_clampedOutputs[outputIdx] != tran[i].m_expectedOutputs[outputIdx])
{
resultCorrect = false;
}
MSE += pow((net->m_outputNeurons[outputIdx] - tran[i].m_expectedOutputs[outputIdx]), 2);
}
if (!resultCorrect)
{
//#pragma omp atomic
incorrectEntries++;
}
}
*m_pNetwork = net;
My problem is the sum values are the same each iterations. So what i've not properly done?
c++ parallel-processing synchronization openmp
c++ parallel-processing synchronization openmp
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
edited Nov 28 '18 at 14:15
MrLebovsky
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
asked Nov 28 '18 at 12:20
MrLebovskyMrLebovsky
14
14
1
netis a pointer. In a parallel section, each thread has its own copy ofnet, however, they all point to the same object. IsNetwork::evaluatethread-safe?
– Daniel Langr
Nov 28 '18 at 13:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
1
No idea what these sum values are. However, note that now,netwill be after parallel loop set to a single privatenetof the thread that run the last iteration. Is it what you want? (Seelastprivatedocs.)
– Daniel Langr
Nov 28 '18 at 14:23
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51
|
show 4 more comments
1
netis a pointer. In a parallel section, each thread has its own copy ofnet, however, they all point to the same object. IsNetwork::evaluatethread-safe?
– Daniel Langr
Nov 28 '18 at 13:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
1
No idea what these sum values are. However, note that now,netwill be after parallel loop set to a single privatenetof the thread that run the last iteration. Is it what you want? (Seelastprivatedocs.)
– Daniel Langr
Nov 28 '18 at 14:23
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51
1
1
net is a pointer. In a parallel section, each thread has its own copy of net, however, they all point to the same object. Is Network::evaluate thread-safe?– Daniel Langr
Nov 28 '18 at 13:00
net is a pointer. In a parallel section, each thread has its own copy of net, however, they all point to the same object. Is Network::evaluate thread-safe?– Daniel Langr
Nov 28 '18 at 13:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
1
1
No idea what these sum values are. However, note that now,
net will be after parallel loop set to a single private net of the thread that run the last iteration. Is it what you want? (See lastprivate docs.)– Daniel Langr
Nov 28 '18 at 14:23
No idea what these sum values are. However, note that now,
net will be after parallel loop set to a single private net of the thread that run the last iteration. Is it what you want? (See lastprivate docs.)– Daniel Langr
Nov 28 '18 at 14:23
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51
|
show 4 more comments
0
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1
netis a pointer. In a parallel section, each thread has its own copy ofnet, however, they all point to the same object. IsNetwork::evaluatethread-safe?– Daniel Langr
Nov 28 '18 at 13:00
@DanielLangr yep that's stupid mistake sorry. Now I've replaced Network * net = m_pNetwork ----> Network net = *m_pNetwork. New problem: sum values are the same each iterations.
– MrLebovsky
Nov 28 '18 at 14:00
1
No idea what these sum values are. However, note that now,
netwill be after parallel loop set to a single privatenetof the thread that run the last iteration. Is it what you want? (Seelastprivatedocs.)– Daniel Langr
Nov 28 '18 at 14:23
@DanielLangr same values without lastprivate clause too
– MrLebovsky
Nov 28 '18 at 14:45
Programming by trying and observing whether it works isn't in my opinion the best approach. Read some good book about OpenMP, or its documentation, or some tutorials before using it.
– Daniel Langr
Nov 28 '18 at 14:51