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Fix MSVC OpenMP issue #757

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Dec 6, 2024
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fix: fix the compatibility with OpenMP 2.0 in MSVC
HanatoK committed Dec 6, 2024
commit d15b871fc1e6f4ee2e4c681c31bb5bcdb2667c84
40 changes: 20 additions & 20 deletions src/colvarbias_opes.cpp
Original file line number Diff line number Diff line change
@@ -395,15 +395,15 @@ cvm::real colvarbias_opes::getProbAndDerivatives(
std::vector<cvm::real> omp_deriv(der_prob.size(), 0);
std::vector<cvm::real> tmp_dist(num_variables());
#pragma omp for reduction(+:prob) nowait
for (size_t k = 0; k < m_kernels.size(); ++k) {
for (int k = 0; k < static_cast<int>(m_kernels.size()); ++k) {
prob += evaluateKernel(m_kernels[k], cv, omp_deriv, tmp_dist);
}
#pragma omp critical
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
der_prob[i]+=omp_deriv[i];
}
#pragma omp single
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
dist[i] = tmp_dist[i];
}
}
@@ -448,16 +448,16 @@ cvm::real colvarbias_opes::getProbAndDerivatives(
std::vector<cvm::real> omp_deriv(der_prob.size(), 0);
std::vector<cvm::real> tmp_dist(num_variables());
#pragma omp for reduction(+:prob) nowait
for (size_t nk = 0; nk < m_nlist_index.size(); ++nk) {
for (int nk = 0; nk < static_cast<int>(m_nlist_index.size()); ++nk) {
const size_t k = m_nlist_index[nk];
prob += evaluateKernel(m_kernels[k], cv, omp_deriv, tmp_dist);
}
#pragma omp critical
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
der_prob[i]+=omp_deriv[i];
}
#pragma omp single
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
dist[i] = tmp_dist[i];
}
}
@@ -947,8 +947,8 @@ int colvarbias_opes::update_opes() {
#pragma omp parallel num_threads(m_num_threads)
{
#pragma omp for reduction(+:sum_uprob) nowait
for (size_t k = 0; k < m_kernels.size(); ++k) {
for (size_t kk = 0; kk < m_kernels.size(); ++kk) {
for (int k = 0; k < static_cast<int>(m_kernels.size()); ++k) {
for (int kk = 0; kk < static_cast<int>(m_kernels.size()); ++kk) {
sum_uprob += evaluateKernel(m_kernels[kk], m_kernels[k].m_center);
}
}
@@ -992,8 +992,8 @@ int colvarbias_opes::update_opes() {
#pragma omp parallel num_threads(m_num_threads)
{
#pragma omp for reduction(+:delta_sum_uprob) nowait
for (size_t i = 0; i < m_kernels.size(); ++i) {
for (size_t d = 0; d < m_delta_kernels.size(); ++d) {
for (int i = 0; i < static_cast<int>(m_kernels.size()); ++i) {
for (int d = 0; d < static_cast<int>(m_delta_kernels.size()); ++d) {
const int sign = m_delta_kernels[d].m_height < 0 ? -1 : 1;
delta_sum_uprob += evaluateKernel(m_delta_kernels[d], m_kernels[i].m_center) + sign * evaluateKernel(m_kernels[i], m_delta_kernels[d].m_center);
}
@@ -1034,9 +1034,9 @@ int colvarbias_opes::update_opes() {
#pragma omp parallel num_threads(m_num_threads)
{
#pragma omp for reduction(+:delta_sum_uprob) nowait
for (size_t i = 0; i < m_nlist_index.size(); ++i) {
for (int i = 0; i < static_cast<int>(m_nlist_index.size()); ++i) {
const size_t k = m_nlist_index[i];
for (size_t d = 0; d < m_delta_kernels.size(); ++d) {
for (int d = 0; d < static_cast<int>(m_delta_kernels.size()); ++d) {
const double sign = m_delta_kernels[d].m_height < 0 ? -1 : 1;
delta_sum_uprob += evaluateKernel(m_delta_kernels[d], m_kernels[k].m_center) + sign * evaluateKernel(m_kernels[k], m_delta_kernels[d].m_center);
}
@@ -1080,8 +1080,8 @@ int colvarbias_opes::update_opes() {
#pragma omp parallel num_threads(m_num_threads)
{
#pragma omp for reduction(+:delta_sum_uprob)
for (size_t d = 0; d < m_delta_kernels.size(); ++d) {
for (size_t dd = 0; dd < m_delta_kernels.size(); ++dd) {
for (int d = 0; d < static_cast<int>(m_delta_kernels.size()); ++d) {
for (int dd = 0; dd < static_cast<int>(m_delta_kernels.size()); ++dd) {
const int sign = m_delta_kernels[d].m_height < 0 ? -1 : 1;
delta_sum_uprob -= sign * evaluateKernel(m_delta_kernels[dd], m_delta_kernels[d].m_center);
}
@@ -1540,13 +1540,13 @@ size_t colvarbias_opes::getMergeableKernel(const std::vector<cvm::real>& giver_c
#if defined(_OPENMP)
#pragma omp parallel num_threads(m_num_threads)
{
size_t min_k_omp = min_k;
int min_k_omp = min_k;
cvm::real min_norm2_omp = m_compression_threshold2;
#pragma omp for nowait
for (size_t k = 0; k < m_kernels.size(); ++k) {
if (k == giver_k) continue;
for (int k = 0; k < static_cast<int>(m_kernels.size()); ++k) {
if (k == static_cast<int>(giver_k)) continue;
double norm2 = 0;
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
norm2 += variables(i)->dist2( giver_center[i], m_kernels[k].m_center[i]) / (m_kernels[k].m_sigma[i] * m_kernels[k].m_sigma[i]);
if (norm2 >= min_norm2_omp) break;
}
@@ -1620,11 +1620,11 @@ size_t colvarbias_opes::getMergeableKernel(const std::vector<cvm::real>& giver_c
size_t min_k_omp = min_k;
cvm::real min_norm2_omp = m_compression_threshold2;
#pragma omp for nowait
for (size_t nk = 0; nk < m_nlist_index.size(); ++nk) {
for (int nk = 0; nk < static_cast<int>(m_nlist_index.size()); ++nk) {
const size_t k = m_nlist_index[nk];
if (k == giver_k) continue;
double norm2 = 0;
for (size_t i = 0; i < num_variables(); ++i) {
for (int i = 0; i < static_cast<int>(num_variables()); ++i) {
norm2 += variables(i)->dist2(giver_center[i], m_kernels[k].m_center[i]) / (m_kernels[k].m_sigma[i] * m_kernels[k].m_sigma[i]);
if (norm2 >= min_norm2_omp) break;
}