considered covered when at least one walker has independently traversed
the sampling interval.
+In practice biases are shared by setting :mdp:`awh-share-multisim` to true
+and :mdp:`awh1-share-group` (for bias 1) to a non-zero value. Here, bias 1
+will be shared between simulations that have the same share group value.
+Sharing can be different for bias 1, 2, etc. (although there are
+few use cases where this is useful). Technically there are no restrictions
+on sharing, apart from that biases that are shared need to have the same
+number of grid points and the update intervals should match.
+Note that biases can not be shared within a simulation.
+The latter could be useful, especially for multimeric proteins, but this
+is more difficult to implement.
+
.. _awhreweight:
Reweighting and combining biased data
.. mdp-value:: positive
- Share the bias and PMF estimates within and/or between simulations.
- Within a simulation, the bias will be shared between biases that have the
- same :mdp:`awh1-share-group` index (note that the current code does not support this).
- With :mdp-value:`awh-share-multisim=yes` and
- :ref:`gmx mdrun` option ``-multidir`` the bias will also be shared across simulations.
+ Share the bias and PMF estimates between simulations. This currently
+ only works between biases with the same index. Note that currently
+ sharing within a single simulation is not supported.
+ The bias will be shared across simulations that specify the same
+ value for :mdp:`awh1-share-group`. To enable this, use
+ :mdp-value:`awh-share-multisim=yes` and the :ref:`gmx mdrun` option
+ ``-multidir``.
Sharing may increase convergence initially, although the starting configurations
can be critical, especially when sharing between many biases.
- Currently, the share value should increase with increasing bias index
- (or be 0).
.. mdp:: awh1-ndim
#endif // GMX_MPI
}
-void BiasSharing::sumOverMasterRanks(ArrayRef<int> data, const int biasIndex) const
+void BiasSharing::sumOverSharingMasterRanks(ArrayRef<int> data, const int biasIndex) const
{
sumOverSimulations(data, multiSimCommPerBias_[biasIndex], false, commRecord_);
}
-void BiasSharing::sumOverMasterRanks(ArrayRef<long> data, const int biasIndex) const
+void BiasSharing::sumOverSharingMasterRanks(ArrayRef<long> data, const int biasIndex) const
{
sumOverSimulations(data, multiSimCommPerBias_[biasIndex], false, commRecord_);
}
-void BiasSharing::sum(ArrayRef<int> data, const int biasIndex) const
+void BiasSharing::sumOverSharingSimulations(ArrayRef<int> data, const int biasIndex) const
{
sumOverSimulations(data, multiSimCommPerBias_[biasIndex], true, commRecord_);
}
-void BiasSharing::sum(ArrayRef<double> data, const int biasIndex) const
+void BiasSharing::sumOverSharingSimulations(ArrayRef<double> data, const int biasIndex) const
{
sumOverSimulations(data, multiSimCommPerBias_[biasIndex], true, commRecord_);
}
std::vector<int> intervals(numSim * 2);
intervals[numSim * 0 + simIndex] = awhParams.nstSampleCoord();
intervals[numSim * 1 + simIndex] = awhParams.numSamplesUpdateFreeEnergy();
- biasSharing.sumOverMasterRanks(intervals, b);
+ biasSharing.sumOverSharingMasterRanks(intervals, b);
for (int sim = 1; sim < numSim; sim++)
{
if (intervals[sim] != intervals[0])
std::vector<long> pointSizes(numSim);
pointSizes[simIndex] = pointSize[b];
- biasSharing.sumOverMasterRanks(pointSizes, b);
+ biasSharing.sumOverSharingMasterRanks(pointSizes, b);
for (int sim = 1; sim < numSim; sim++)
{
if (pointSizes[sim] != pointSizes[0])
//! Returns the index of our simulation in the simulations sharing bias \p biasIndex
int sharingSimulationIndex(int biasIndex) const { return sharingSimulationIndices_[biasIndex]; }
- //! Sums data over the master ranks of all simulations sharing bias \p biasIndex
- void sumOverMasterRanks(ArrayRef<int> data, int biasIndex) const;
+ //! Sums data of type int over the master ranks of all simulations sharing bias \p biasIndex
+ void sumOverSharingMasterRanks(ArrayRef<int> data, int biasIndex) const;
- //! Sums data over the master ranks of all simulations sharing bias \p biasIndex
- void sumOverMasterRanks(ArrayRef<long> data, int biasIndex) const;
+ //! Sums data of type long over the master ranks of all simulations sharing bias \p biasIndex
+ void sumOverSharingMasterRanks(ArrayRef<long> data, int biasIndex) const;
- //! Sums data over all simulations sharing bias \p biasIndex and broadcasts to all ranks within the simulation
- void sum(ArrayRef<int> data, int biasIndex) const;
+ /*! \brief Sums data of type int over all simulations sharing bias \p biasIndex
+ *
+ * The summing is performed over the master ranks of the simulations sharing bias \p biasIndex
+ * and the result is broadcasted to the other ranks within each simulation.
+ */
+ void sumOverSharingSimulations(ArrayRef<int> data, int biasIndex) const;
- //! Sums data over all simulations sharing bias \p biasIndex and broadcasts to all ranks within the simulation
- void sum(ArrayRef<double> data, int biasIndex) const;
+ /*! \brief Sums data of type long over all simulations sharing bias \p biasIndex
+ *
+ * The summing is performed over the master ranks of the simulations sharing bias \p biasIndex
+ * and the result is broadcasted to the other ranks within each simulation.
+ */
+ void sumOverSharingSimulations(ArrayRef<double> data, int biasIndex) const;
private:
//! The number of simulations sharing for each bias
buffer[i] = pointState[i].inTargetRegion() ? std::exp(pointState[i].logPmfSum()) : 0;
}
- biasSharing->sum(gmx::ArrayRef<double>(buffer), biasIndex);
+ biasSharing->sumOverSharingSimulations(gmx::ArrayRef<double>(buffer), biasIndex);
/* Take log again to get (non-normalized) PMF */
double normFac = 1.0 / numSharedUpdate;
}
/* Sum over the sims to get all the flagged points */
- biasSharing.sum(arrayRefFromArray(numUpdatesOfPoint.data(), numPoints), biasIndex);
+ biasSharing.sumOverSharingSimulations(arrayRefFromArray(numUpdatesOfPoint.data(), numPoints), biasIndex);
/* Collect the indices of the flagged points in place. The resulting array will be the merged update list.*/
updateList->clear();
coordVisits[localIndex] = ps.numVisitsIteration();
}
- biasSharing->sum(gmx::ArrayRef<double>(weightSum), biasIndex);
- biasSharing->sum(gmx::ArrayRef<double>(coordVisits), biasIndex);
+ biasSharing->sumOverSharingSimulations(gmx::ArrayRef<double>(weightSum), biasIndex);
+ biasSharing->sumOverSharingSimulations(gmx::ArrayRef<double>(coordVisits), biasIndex);
/* Transfer back the result */
for (size_t localIndex = 0; localIndex < localUpdateList.size(); localIndex++)
/* For multiple dimensions this may not be the best way to do it. */
for (int d = 0; d < grid.numDimensions(); d++)
{
- biasSharing_->sum(gmx::arrayRefFromArray(checkDim[d].covered.data(), grid.axis(d).numPoints()),
- params.biasIndex);
+ biasSharing_->sumOverSharingSimulations(
+ gmx::arrayRefFromArray(checkDim[d].covered.data(), grid.axis(d).numPoints()),
+ params.biasIndex);
}
}
const std::array<int, c_numRanks> input{ 1, 2, 4, 8 };
std::array<int, 1> buffer{ input[myRank] };
- biasSharing.sumOverMasterRanks(buffer, 0);
+ biasSharing.sumOverSharingMasterRanks(buffer, 0);
int expectedSum = 0;
for (int i = 0; i < c_numSharingBiases; i++)
{
biod.pnpi.spb.ru / alexxy / gromacs.git / commitdiff