All replica exchange variants are options of the {\tt mdrun}
program. It will only work when MPI is installed, due to the inherent
parallelism in the algorithm. For efficiency each replica can run on a
-separate node. See the manual page of {\tt mdrun} on how to use these
+separate rank. See the manual page of {\tt mdrun} on how to use these
multinode features.
% \ifthenelse{\equal{\gmxlite}{1}}{}{
\section{Parallelization\index{parallelization}}
The CPU time required for a simulation can be reduced by running the simulation
-in parallel over more than one processor or processor core.
-Ideally one would want to have linear scaling: running on $N$ processors/cores
+in parallel over more than one core.
+Ideally, one would want to have linear scaling: running on $N$ cores
makes the simulation $N$ times faster. In practice this can only be
-achieved for a small number of processors. The scaling will depend
+achieved for a small number of cores. The scaling will depend
a lot on the algorithms used. Also, different algorithms can have different
restrictions on the interaction ranges between atoms.
\section{Domain decomposition\index{domain decomposition}}
Since most interactions in molecular simulations are local,
domain decomposition is a natural way to decompose the system.
-In domain decomposition, a spatial domain is assigned to each processor,
+In domain decomposition, a spatial domain is assigned to each rank,
which will then integrate the equations of motion for the particles
that currently reside in its local domain. With domain decomposition,
there are two choices that have to be made: the division of the unit cell
-into domains and the assignment of the forces to processors.
+into domains and the assignment of the forces to domains.
Most molecular simulation packages use the half-shell method for assigning
the forces. But there are two methods that always require less communication:
the eighth shell~\cite{Liem1991} and the midpoint~\cite{Shaw2006} method.
In the most general case of a triclinic unit cell,
the space in divided with a 1-, 2-, or 3-D grid in parallelepipeds
that we call domain decomposition cells.
-Each cell is assigned to a processor.
-The system is partitioned over the processors at the beginning
+Each cell is assigned to a particle-particle rank.
+The system is partitioned over the ranks at the beginning
of each MD step in which neighbor searching is performed.
Since the neighbor searching is based on charge groups, charge groups
are also the units for the domain decomposition.
then one in $y$ and then one in $z$. The forces are communicated by
reversing this procedure. See the {\gromacs} 4 paper~\cite{Hess2008b}
for details on determining which non-bonded and bonded forces
-should be calculated on which node.
+should be calculated on which rank.
\subsection{Dynamic load balancing\swapindexquiet{dynamic}{load balancing}}
-When different processors have a different computational load
-(load imbalance), all processors will have to wait for the one
+When different ranks have a different computational load
+(load imbalance), all ranks will have to wait for the one
that takes the most time. One would like to avoid such a situation.
Load imbalance can occur due to three reasons:
\begin{itemize}
\begin{figure}
\centerline{\includegraphics[width=7cm]{plots/dd-tric}}
\caption{
-The zones to communicate to the processor of zone 0,
+The zones to communicate to the rank of zone 0,
see the text for details. $r_c$ and $r_b$ are the non-bonded
and bonded cut-off radii respectively, $d$ is an example
of a distance between following, staggered boundaries of cells.
\subsection{Constraints in parallel\index{constraints}}
\label{subsec:plincs}
Since with domain decomposition parts of molecules can reside
-on different processors, bond constraints can cross cell boundaries.
+on different ranks, bond constraints can cross cell boundaries.
Therefore a parallel constraint algorithm is required.
{\gromacs} uses the \normindex{P-LINCS} algorithm~\cite{Hess2008a},
which is the parallel version of the \normindex{LINCS} algorithm~\cite{Hess97}
scaling with domain decomposition.
To reduce the effect of this problem, we have come up with
a Multiple-Program, Multiple-Data approach~\cite{Hess2008b}.
-Here, some processors are selected to do only the PME mesh calculation,
-while the other processors, called particle-particle (PP) nodes,
+Here, some ranks are selected to do only the PME mesh calculation,
+while the other ranks, called particle-particle (PP) ranks,
do all the rest of the work.
-For rectangular boxes the optimal PP to PME node ratio is usually 3:1,
+For rectangular boxes the optimal PP to PME rank ratio is usually 3:1,
for rhombic dodecahedra usually 2:1.
-When the number of PME nodes is reduced by a factor of 4, the number
+When the number of PME ranks is reduced by a factor of 4, the number
of communication calls is reduced by about a factor of 16.
-Or put differently, we can now scale to 4 times more nodes.
+Or put differently, we can now scale to 4 times more ranks.
In addition, for modern 4 or 8 core machines in a network,
the effective network bandwidth for PME is quadrupled,
since only a quarter of the cores will be using the network connection
\begin{figure}
\centerline{\includegraphics[width=12cm]{plots/mpmd-pme}}
\caption{
-Example of 8 nodes without (left) and with (right) MPMD.
+Example of 8 ranks without (left) and with (right) MPMD.
The PME communication (red arrows) is much higher on the left
than on the right. For MPMD additional PP - PME coordinate
and force communication (blue arrows) is required,
}
\end{figure}
-{\tt mdrun} will by default interleave the PP and PME nodes.
-If the processors are not number consecutively inside the machines,
+{\tt mdrun} will by default interleave the PP and PME ranks.
+If the ranks are not number consecutively inside the machines,
one might want to use {\tt mdrun -ddorder pp_pme}.
For machines with a real 3-D torus and proper communication software
-that assigns the processors accordingly one should use
+that assigns the ranks accordingly one should use
{\tt mdrun -ddorder cartesian}.
To optimize the performance one should usually set up the cut-offs
and the PME grid such that the PME load is 25 to 33\% of the total
calculation load. {\tt grompp} will print an estimate for this load
at the end and also {\tt mdrun} calculates the same estimate
-to determine the optimal number of PME nodes to use.
+to determine the optimal number of PME ranks to use.
For high parallelization it might be worthwhile to optimize
the PME load with the {\tt mdp} settings and/or the number
-of PME nodes with the {\tt -npme} option of {\tt mdrun}.
+of PME ranks with the {\tt -npme} option of {\tt mdrun}.
For changing the electrostatics settings it is useful to know
the accuracy of the electrostatics remains nearly constant
when the Coulomb cut-off and the PME grid spacing are scaled
by the same factor.
{\bf Note} that it is usually better to overestimate than to underestimate
-the number of PME nodes, since the number of PME nodes is smaller
-than the number of PP nodes, which leads to less total waiting time.
+the number of PME ranks, since the number of PME ranks is smaller
+than the number of PP ranks, which leads to less total waiting time.
The PME domain decomposition can be 1-D or 2-D along the $x$ and/or
$y$ axis. 2-D decomposition is also known as \normindex{pencil decomposition} because of
the PP decomposition has only 1 domain along $x$. 2-D PME decomposition
has to have the number of domains along $x$ equal to the number of
the PP decomposition. {\tt mdrun} automatically chooses 1-D or 2-D
-PME decomposition (when possible with the total given number of nodes),
+PME decomposition (when possible with the total given number of ranks),
based on the minimum amount of communication for the coordinate redistribution
in PME plus the communication for the grid overlap and transposes.
To avoid superfluous communication of coordinates and forces
-between the PP and PME nodes, the number of DD cells in the $x$
+between the PP and PME ranks, the number of DD cells in the $x$
direction should ideally be the same or a multiple of the number
-of PME nodes. By default, {\tt mdrun} takes care of this issue.
+of PME ranks. By default, {\tt mdrun} takes care of this issue.
\subsection{Domain decomposition flow chart}
In \figref{dd_flow} a flow chart is shown for domain decomposition
\caption{
Flow chart showing the algorithms and communication (arrows)
for a standard MD simulation with virtual sites, constraints
-and separate PME-mesh nodes.
+and separate PME-mesh ranks.
\label{fig:dd_flow}
}
\end{figure}
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