parallel (c49b1)
Parallel Implementation of CHARMM
to be run on multi-machines using a replicated data model. This
version, though employing a full communication scheme, uses an efficient
divide-and-conquer algorithm for global sums and broadcasts.
Curently the following hardware platforms are supported:
1. Cray T3D/T3E 7. Intel Paragon machine
2. Cray C90, J90 8. Thinking Machines CM-5
3. SGI Power Challenge 9. IBM SP1/SP2 machines
4. Convex SPP-1000 Exemplar 10. Parallel Virtual Machine (PVM)
5. Intel iPSC/860 gamma 11. Workstation clusters (SOCKET)
6. Intel Delta machine 12. Alpha Servers (SMP machines, PVMC)
13. TERRA 2000 14. HP SMP machines
15. Convex SPP-2000 16. SGI Origin
17. LoBoS (any Beowulf) 18. IBM Power4 using GNU/Linux system
* Syntax | Syntax for PARAllel command
* Installation | Installing CHARMM on parallel systems
* Running | Running CHARMM on parallel systems
* PARAllel | Command PARAllel controls parallel communication
* Status | Parallel Code Status (as of September 1998)
* Using PVM | Parallel Code implemented with PVM
* Implementation | Description of implementation of parallel code
to be run on multi-machines using a replicated data model. This
version, though employing a full communication scheme, uses an efficient
divide-and-conquer algorithm for global sums and broadcasts.
Curently the following hardware platforms are supported:
1. Cray T3D/T3E 7. Intel Paragon machine
2. Cray C90, J90 8. Thinking Machines CM-5
3. SGI Power Challenge 9. IBM SP1/SP2 machines
4. Convex SPP-1000 Exemplar 10. Parallel Virtual Machine (PVM)
5. Intel iPSC/860 gamma 11. Workstation clusters (SOCKET)
6. Intel Delta machine 12. Alpha Servers (SMP machines, PVMC)
13. TERRA 2000 14. HP SMP machines
15. Convex SPP-2000 16. SGI Origin
17. LoBoS (any Beowulf) 18. IBM Power4 using GNU/Linux system
* Syntax | Syntax for PARAllel command
* Installation | Installing CHARMM on parallel systems
* Running | Running CHARMM on parallel systems
* PARAllel | Command PARAllel controls parallel communication
* Status | Parallel Code Status (as of September 1998)
* Using PVM | Parallel Code implemented with PVM
* Implementation | Description of implementation of parallel code
Top
PARAllel command parser for controlling parallel execution
Syntax:
PARAllel CONCurrent <int> ...
CONCurrent <int> specify how many concurrent jobs
to run in the system
PARAllel FIFO <int> specify FIFO scheduler in LoBoS with
static priority <int>
PARAllel BUFF <int> specify buffer size for send/receive
calls. <int> is in REAL*8 units
PARAllel INFO Prints the hostname information for each process
Also fills arrays PARHOST, PARHLEN in parallel.fcm
PARAllel command parser for controlling parallel execution
Syntax:
PARAllel CONCurrent <int> ...
CONCurrent <int> specify how many concurrent jobs
to run in the system
PARAllel FIFO <int> specify FIFO scheduler in LoBoS with
static priority <int>
PARAllel BUFF <int> specify buffer size for send/receive
calls. <int> is in REAL*8 units
PARAllel INFO Prints the hostname information for each process
Also fills arrays PARHOST, PARHLEN in parallel.fcm
Top
For support of many parallel comunication libraries the CMPI keyword
was added. In order to get the old communication routines always
specify CMPI otherwise MPI is the default choice (see recommended
keyword combination for each specific platform). On some platforms
recommended preflx directives prepare the code which does the
communication much faster, eg on 128 nodes T3E CMPI is 4 times faster
than MPI. For spatial decomposition method PARAFULL or PARASCAL must
be replaced by SPACDEC pref.dat keyword
This is a complete list of supported combinations for message passing
libraries implemented in the parallel CHARMM
Combinations of pref.dat keywords for MPI library (can be specified on
any platform that support MPI):
1. < no extra keywords > (Calls to MPI collective routines)
2. CMPI MPI (non-blocking cube topology using send/receive from MPI)
3. CMPI MPI GENCOMM (non-blocking ring topology, MPI send/receive)
4. CMPI MPI SYNCHRON (blocking cube topology, MPI send/receive)
5. CMPI MPI GENCOMM SYNCHRON (blocking ring topology, MPI send/receive)
NOTE: using GENCOMM is slower then without it. GENCOMM is mostly used
for QM/MM replica path method where the scaling is almost
perfect anyway.
Additionally there is a pref.dat keyword PARINFNTY, which simulates
the infinitively fast network. In other words there is no communication
involved during the dynamics after the parallel run is setup. Needles
to say the results of such calculations are meaningless. Also in order
to get a few 1000 of steps of dynamics one need to use very small
timesteps, eg 0.000001. The purpose of this keyword is for testing
setups. It works in combination with CMPI keyword. For example one
should specify CMPI MPI PARAFULL PARINFNTY.
Native library options
6. CMPI DELTA (for Intel Paragon)
7. CMPI IBMSP (for IBM SP2)
8. TERRA (for TERRA 2000)
9. CMPI CM5 (For CM5)
10. CSPP (Convex version of MPI)
Workstation clusters using SOCKET
11. CMPI SOCKET SYNCRON (blocking cube topology)
12. CMPI SOCKET SYNCRON GENCOMM (blocking ring topology)
PVM library
13. CMPI PVMC SYNCHRON (blocking cube, PVM send/receive)
14. CMPI PVMC GENCOMM SYNCHRON (blocking ring, PVM send/receive)
Combination 1., 8. and 10. are currently implemented in
machdep/paral1.src so there is no need for paral2.src and paral3.src
files, which will eventually become unnecessary. Efficiency of
different topologies also varies with the number of nodes.
Also on some platforms EXPAND keyword is recommended in the combination
of the fastest FAST option in the CHARMM input script, eg for IBMSP:
EXPAND (fast parvect)
The configure script now installs a default configuration for MPI
parallel platforms. Run
$ ./configure --help
for a current set of options.
If the correct MPI binaries
occur first in your PATH, then to compile using the configure script,
you usually do not need to add extra command line options to enable MPI.
Use the normal procedure given your compilers (» cmake ).
-----
The following keywords in pref.dat are used for parallel CHARMM:
Machine independent keywords:
PARALLEL Needed for parallel version
SOCKET If TCP/IP sockets
PVM If using PVM library
PVMC If using PVM library on some platforms (see below).
PARAFULL Currently the only one which works
(must be specified)
PARASCAL For force decomposition scheme
(not ready for general use yet.)
SPACDEC For spatial decomposition scheme
based on BYCC (BYCC must be specified in nonbond
options)
SYNCHRON Most of the machines don't do
receive and send at the same time
GENCOMM Different communication arcitecture.
Can run any number of nodes
MPI If using MPI parallel library.
(point-to-point routines only)
CMPI CHARMM implementation of the MPI library.
Enables all the old functionality plus some
combinations of libraries on the same platform.
ASYNC_MPI using CMPI library routines vs MPI in PME.
Machine specific keywords:
TERRA
CM5
CSPP
DELTA
INTEL
PARAGON
SHMEM
CSPPMPI
T3D
T3E
IBMSP
ALPHAMP
SGIMP
ALTIX_MPI ! also used in generic x86_64 compiles
For support of many parallel comunication libraries the CMPI keyword
was added. In order to get the old communication routines always
specify CMPI otherwise MPI is the default choice (see recommended
keyword combination for each specific platform). On some platforms
recommended preflx directives prepare the code which does the
communication much faster, eg on 128 nodes T3E CMPI is 4 times faster
than MPI. For spatial decomposition method PARAFULL or PARASCAL must
be replaced by SPACDEC pref.dat keyword
This is a complete list of supported combinations for message passing
libraries implemented in the parallel CHARMM
Combinations of pref.dat keywords for MPI library (can be specified on
any platform that support MPI):
1. < no extra keywords > (Calls to MPI collective routines)
2. CMPI MPI (non-blocking cube topology using send/receive from MPI)
3. CMPI MPI GENCOMM (non-blocking ring topology, MPI send/receive)
4. CMPI MPI SYNCHRON (blocking cube topology, MPI send/receive)
5. CMPI MPI GENCOMM SYNCHRON (blocking ring topology, MPI send/receive)
NOTE: using GENCOMM is slower then without it. GENCOMM is mostly used
for QM/MM replica path method where the scaling is almost
perfect anyway.
Additionally there is a pref.dat keyword PARINFNTY, which simulates
the infinitively fast network. In other words there is no communication
involved during the dynamics after the parallel run is setup. Needles
to say the results of such calculations are meaningless. Also in order
to get a few 1000 of steps of dynamics one need to use very small
timesteps, eg 0.000001. The purpose of this keyword is for testing
setups. It works in combination with CMPI keyword. For example one
should specify CMPI MPI PARAFULL PARINFNTY.
Native library options
6. CMPI DELTA (for Intel Paragon)
7. CMPI IBMSP (for IBM SP2)
8. TERRA (for TERRA 2000)
9. CMPI CM5 (For CM5)
10. CSPP (Convex version of MPI)
Workstation clusters using SOCKET
11. CMPI SOCKET SYNCRON (blocking cube topology)
12. CMPI SOCKET SYNCRON GENCOMM (blocking ring topology)
PVM library
13. CMPI PVMC SYNCHRON (blocking cube, PVM send/receive)
14. CMPI PVMC GENCOMM SYNCHRON (blocking ring, PVM send/receive)
Combination 1., 8. and 10. are currently implemented in
machdep/paral1.src so there is no need for paral2.src and paral3.src
files, which will eventually become unnecessary. Efficiency of
different topologies also varies with the number of nodes.
Also on some platforms EXPAND keyword is recommended in the combination
of the fastest FAST option in the CHARMM input script, eg for IBMSP:
EXPAND (fast parvect)
The configure script now installs a default configuration for MPI
parallel platforms. Run
$ ./configure --help
for a current set of options.
If the correct MPI binaries
occur first in your PATH, then to compile using the configure script,
you usually do not need to add extra command line options to enable MPI.
Use the normal procedure given your compilers (» cmake ).
-----
The following keywords in pref.dat are used for parallel CHARMM:
Machine independent keywords:
PARALLEL Needed for parallel version
SOCKET If TCP/IP sockets
PVM If using PVM library
PVMC If using PVM library on some platforms (see below).
PARAFULL Currently the only one which works
(must be specified)
PARASCAL For force decomposition scheme
(not ready for general use yet.)
SPACDEC For spatial decomposition scheme
based on BYCC (BYCC must be specified in nonbond
options)
SYNCHRON Most of the machines don't do
receive and send at the same time
GENCOMM Different communication arcitecture.
Can run any number of nodes
MPI If using MPI parallel library.
(point-to-point routines only)
CMPI CHARMM implementation of the MPI library.
Enables all the old functionality plus some
combinations of libraries on the same platform.
ASYNC_MPI using CMPI library routines vs MPI in PME.
Machine specific keywords:
TERRA
CM5
CSPP
DELTA
INTEL
PARAGON
SHMEM
CSPPMPI
T3D
T3E
IBMSP
ALPHAMP
SGIMP
ALTIX_MPI ! also used in generic x86_64 compiles
Top
Running CHARMM on parallel systems
General note for MPI systems.
Most MPI systems do not allow rewind of stdin which means charmm input files
containing "goto" statements would not work if invoked directly
(this example uses MPICH):
~charmm/exec/gnu/charmm -p4wd . -p4pg file < my.inp > my.out [charmm options]
The workaround is simple:
~charmm/exec/gnu/charmm -p4wd . -p4pg file < my.stdin > my.out ZZZ=my.inp [charmm options]
where the file my.stdin just streams to the real inputfile:
* Stream to real file given as ZZZ=filename on commandline. Note that the filename
* cannot consist of a mixture of upper- and lower-case letters.
stream @ZZZ
stop
1. Cray T3D (Cray-PVM)
~charmm/exec/t3d/charmm24 -npes 256 < input_file > output_file &
The same command may be used in a batch script but without `&'.
Example using batch:
#QSUB -lM 16Mw
#QSUB -lT 600:00
#QSUB -mb -me
#QSUB -l mpp_p=32
#QSUB -l mpp_t=600:00
#QSUB -q mpp
setenv MPP_NPES 32
~charmm/exec/t3d/charmm24 < Input_file > output_file
Preflx directives required: T3D UNIX PARALLEL PARAFULL
Additional preflx directives recommended: PVM or MPI
2. Cray T3E (Cray-PVM)
CHARMM can be run on either a single processor or in parallel on the T3E.
Single processor runs are useful for small analysis jobs and other tasks
that are not amenable to parallel processing. The syntax for a single
pe run is:
charmm24 < filename.inp >& filename.out [&]
Large CHARMM jobs should be run in parallel using the queue system.
The syntax for a parallel run is:
mpprun -n# charmm24 < filename.inp >& filename.out [&]
(here # is the desired number of pe's)
The same command may be used in a batch script but without `&'.
Example using batch:
#QSUB -lM 16Mw
#QSUB -lT 600:00
#QSUB -mb -me
#QSUB -l mpp_p=32
#QSUB -q mpp
mpprun -n 32 charmm24 < Input_file > output_file
Preflx directives required: T3E UNIX PARALLEL PARAFULL
Additional preflx directives recommended: EXPAND(fast off)
and either PVM or MPI
Optimization Notes:
T3E users should use the PBOUND command for simulations of periodic
systems. The pbound command optimizes non-bonded list-generation and
computations on parallel machines such as the T3E, giving significantly
better performance for parallel applications using simple perodic
boundary conditions. Note that the pbound command is currently
implemented only for scalar architectures such as the T3D and T3E.
3. Cray C90, J90 (Cray-PVM)
No info yet
4. SGI Power Challenge (PVM)
pvm
quit
setenv NTPVM 16 (or NTPVM=16 ; export NTPVM)
~charmm/exe/sgi/charmm24 <input_file >output_file &
Preflx directives required: SGI UNIX PARALLEL PARAFULL CMPI PVMC SGIMP
Additional preflx directives recommended: EXPAND(fast off)
Alternative, but not tested yet: SGI UNIX PARALLEL PARAFULL
[NOTE: This is old: MPI is preffered over this. Installation
similar to Linux, see above]
5. Convex SPP-1000 Exemplar
With PVM
(see below for information setting up a PVM Hostfile)
mpa -sc <name_of_subcomplex> /bin/csh
setenv PVM_ROOT /usr/convex/pvm
/usr/lib/pvm/pvm
quit
~/pvm3/bin/CSPP/charmm24 -n 16 <input_file >output_file &
~charmm/exe/cspp/charmm24 <input_file >output_file &
Which subcomplexes are available check with the scm utility.
(For information on how to set up a PVM hostfile 1: Using PVM.)
Preflx directives required: CSPP UNIX PARALLEL PARAFULL PVM HPUX
SYNCHRON (GENCOMM)
Note: The first time that you build CHARMM with PVM specify the P option
with install.com. You will be asked for the location of the PVM include
files and libraries. If these do not change and you do not reconstruct the
Makefiles, you do not have to specify this option each time you run
install.com.
With MPI
mpa -DATA -STACK -sc <name_of_subcomplex> \
~charmm/exe/cspp/charmm24 -np <n> <input_file >output_file &
Where <n> is the number of processors to use.
There are two environmanet variables that can be set:
setenv MPI_GLOBMEMSIZE <m>
where <m> is the size of the shared memory region on each hypernode
in bytes. The default is 16MB.
And:
setenv MPI_TOPOLOGY <i>,<j>,<k>,<l>,...
where <i>, <j>, <k>, <l>, ... are the number of tasks on each hypernode.
The sum must equal the number of processors specified with -np on the
command line. This is optional the default behavior is generally what
you want. If you are using a sub-complex with more than one hypernode,
use may want to include '-node 0' after mpa to keep the 0th process
on the 0th hypernode of the sub-complex.
Preflx directives required: CSPP UNIX PARALLEL PARAFULL HPUX
MPI CSPPMPI
The CSPPMPI directive specifies the use of extensions in the Convex
MPI implementation. This directive is optional. Use of the MPI
directive alone will result in a fully MPI Standard compliant program,
albeit with a loss of performance.
Note: The first time that you build CHARMM with MPI specify the M option
with install.com. You will be asked for the location of the MPI include
files and libraries. If these do not change and you do not reconstruct the
Makefiles, you do not have to specify this option each time you run
install.com.
6. Intel gamma
Because the fortran compiler on the Intel gamma does not know how
to rewind the redirected input file the program uses charmm.inp
file name from current working directory. The script for running
CHARMM should look like the following example:
cp input_file.inp charmm.inp
getcube -t128 > output_file
load ~charmm/exec/intel/charmm24
waitcube
Preflx directives required: INTEL UNIX PARALLEL PARAFULL
7. Intel Delta
mexec "-t(32,16)" ~charmm/exec/intel/charmm23<input_file>output_file&
Preflx directives required: INTEL UNIX DELTA PARALLEL PARAFULL
8. Intel Paragon
~charmm/exec/intel/charmm23 -sz 64 <input_file >output_file &
Preflx directives required: INTEL UNIX PARAGON PARALLEL PARAFULL
9. CM-5
~charmm/exec/cm5/charmm23 <input_file >output_file &
Preflx directives required:CM5 UNIX PARALLEL PARAFULL
10. IBM SP2 or SP1
setenv MP_RESD yes
setenv MP_PULSE 0
setenv MP_RMPOOL 1
setenv MP_EUILIB us
setenv MP_INFOLEVEL 0
poe ~charmm/exec/ibmsp/charmm24 -hfile nodes -procs 64 <input >output
See `man poe' for details.
Preflx directives required:IBMSP UNIX PARALLEL PARAFULL
Additional preflx directives recommended: EXPAND(fast parvect)
11. PVM
pvm
add host host1
add host host2
quit
setenv NTPVM 3
~/pvm3/bin/SGI5/charmm24 <input_file >output_file&
Preflx directives required: machine_type UNIX PARALLEL CMPI PVM
PARAFULL SYNCHRON
12. Linux clusters (Beowulf)
MPICH: (MPICH doesn't need to be installed on compute nodes)
~charmm/exec/gnu/charmm -p4wd . -p4pg file < input > output [charmm options]
where file is:
host1 0
host2 1 ~charmm/exec/gnu/charmm
host3 1 ~charmm/exec/gnu/charmm
etc.
[NOTE: host1 can be the same as host2, host3, etc. for
SMP]
LAM: (Every node has to have LAM installed!!)
lamboot -v hostfile
mpirun -O -c2c -w schema < input >output
where schema is a file:
~charmm/exec/gnu/charmm n0 -- [charmm options]
~charmm/exec/gnu/charmm n1 -- [charmm options]
~charmm/exec/gnu/charmm n2 -- [charmm options]
etc.
and hostfile is:
host1
host2
host3
etc.
13. PARALLEL VERSION OF CHARMM23 ON WORKSTATION CLUSTERS
Preflx directives required: machine_type UNIX PARALLEL CMPI SOCKET
PARAFULL SYNCHRON
Currently the code runs on HP, DEC alpha, and IBM RS/6000
machines. This has been tested. The rest of UNIX world should run
too without any changes as long as the following is true:
Assumptions for cluster environment:
Before you run CHARMM with SOCKET library you have to define some
environment variables. If you define nothing then CHARMM will
run in a scalar mode, i.e. default is one node run.
PWD
The program supports three shells: bash (Bourne Again SHell), ksh
(Korn Shell) and tcsh, which is available from anonymous ftp. The
only difference from csh on which CHARMM makes assumption is
definition of variable PWD. This variable is correctly defined in
all of the above three shells by default, while using csh it has
to be defined by the user. Variable PWD points to the current
working directory. If some other directory is requested the PWD
environment variable may be changed appropriately. The program
can figure out current working directory by itself but there are
problems in some NFS environments, because home directory names
can vary on different machines.( PWD is always defined correctly
by shell which supports it ) So csh may sometimes cause
problems. Using csh the cd command may be redefined so that it
always defines also PWD. This is done with something like: alias
cd 'chdir \!*; setenv PWD $cwd ' in the ~/.cshrc file.
If you get an error which looks something like nonexistent
directory then define PWD variable directly.
[NIH specific (for HPUX):
If you want to use tcsh as your login shell you may run the
following command:
runall chsh username /usr/local/bin/tcsh
runall is a script which runs the command on the whole cluster of
machines it is on /usr/local/bin at NIH. ]
NODEx
In order to run CHARMM on more then one node environment variables
NODE0, NODE1, ..., NODEn have to be defined.
Example for a 4 node run:
setenv NODE0 par0
setenv NODE1 par1
setenv NODE2 par2
setenv NODE3 par4
charmm < input_file > output_file 1:parameter1 2:parameter2 ...
"par0,par1,par2,.." are the names of the machines in the local
network. There is no requirement that all machines should be of
the same type. There is nothing in the program to adjust for
unequal load balance so all nodes will follow the slowest one. In
near future we may implement dynamic load balance method based on
actual time required.
The assumption here is that the node from where CHARMM program is
started is always NODE0!
Setup for your login environment
In order to run CHARMM in parallel you have to be able to rlogin to
any of the nodes defined in NODEx environment variables. Before you
run CHARMM check this out:
rlogin $NODE1
if it doesn't ask you for Password then you are OK. If it asks for
Password then put a line like this:
machine_name user_name
in your ~/.rhosts file, with 600 permission.
[NIH specific:
How to submit job to HP.
Currently we have assigned machines par0, par1, par2, and par4 to
work in parallel. You may use script
/usr/local/bin/charmm23.parallel and submit it to par0. Example:
submit par0 charmm23.parallel <input_file >output_file ^D
To construct your own parallel scripts look at
/usr/local/bin/charmm23.parallel ]
In the input scripts
Everything should work, but avoid usage of IOLEV and PRNLEV in your
parallel scripts.
Running CHARMM on parallel systems
General note for MPI systems.
Most MPI systems do not allow rewind of stdin which means charmm input files
containing "goto" statements would not work if invoked directly
(this example uses MPICH):
~charmm/exec/gnu/charmm -p4wd . -p4pg file < my.inp > my.out [charmm options]
The workaround is simple:
~charmm/exec/gnu/charmm -p4wd . -p4pg file < my.stdin > my.out ZZZ=my.inp [charmm options]
where the file my.stdin just streams to the real inputfile:
* Stream to real file given as ZZZ=filename on commandline. Note that the filename
* cannot consist of a mixture of upper- and lower-case letters.
stream @ZZZ
stop
1. Cray T3D (Cray-PVM)
~charmm/exec/t3d/charmm24 -npes 256 < input_file > output_file &
The same command may be used in a batch script but without `&'.
Example using batch:
#QSUB -lM 16Mw
#QSUB -lT 600:00
#QSUB -mb -me
#QSUB -l mpp_p=32
#QSUB -l mpp_t=600:00
#QSUB -q mpp
setenv MPP_NPES 32
~charmm/exec/t3d/charmm24 < Input_file > output_file
Preflx directives required: T3D UNIX PARALLEL PARAFULL
Additional preflx directives recommended: PVM or MPI
2. Cray T3E (Cray-PVM)
CHARMM can be run on either a single processor or in parallel on the T3E.
Single processor runs are useful for small analysis jobs and other tasks
that are not amenable to parallel processing. The syntax for a single
pe run is:
charmm24 < filename.inp >& filename.out [&]
Large CHARMM jobs should be run in parallel using the queue system.
The syntax for a parallel run is:
mpprun -n# charmm24 < filename.inp >& filename.out [&]
(here # is the desired number of pe's)
The same command may be used in a batch script but without `&'.
Example using batch:
#QSUB -lM 16Mw
#QSUB -lT 600:00
#QSUB -mb -me
#QSUB -l mpp_p=32
#QSUB -q mpp
mpprun -n 32 charmm24 < Input_file > output_file
Preflx directives required: T3E UNIX PARALLEL PARAFULL
Additional preflx directives recommended: EXPAND(fast off)
and either PVM or MPI
Optimization Notes:
T3E users should use the PBOUND command for simulations of periodic
systems. The pbound command optimizes non-bonded list-generation and
computations on parallel machines such as the T3E, giving significantly
better performance for parallel applications using simple perodic
boundary conditions. Note that the pbound command is currently
implemented only for scalar architectures such as the T3D and T3E.
3. Cray C90, J90 (Cray-PVM)
No info yet
4. SGI Power Challenge (PVM)
pvm
quit
setenv NTPVM 16 (or NTPVM=16 ; export NTPVM)
~charmm/exe/sgi/charmm24 <input_file >output_file &
Preflx directives required: SGI UNIX PARALLEL PARAFULL CMPI PVMC SGIMP
Additional preflx directives recommended: EXPAND(fast off)
Alternative, but not tested yet: SGI UNIX PARALLEL PARAFULL
[NOTE: This is old: MPI is preffered over this. Installation
similar to Linux, see above]
5. Convex SPP-1000 Exemplar
With PVM
(see below for information setting up a PVM Hostfile)
mpa -sc <name_of_subcomplex> /bin/csh
setenv PVM_ROOT /usr/convex/pvm
/usr/lib/pvm/pvm
quit
~/pvm3/bin/CSPP/charmm24 -n 16 <input_file >output_file &
~charmm/exe/cspp/charmm24 <input_file >output_file &
Which subcomplexes are available check with the scm utility.
(For information on how to set up a PVM hostfile 1: Using PVM.)
Preflx directives required: CSPP UNIX PARALLEL PARAFULL PVM HPUX
SYNCHRON (GENCOMM)
Note: The first time that you build CHARMM with PVM specify the P option
with install.com. You will be asked for the location of the PVM include
files and libraries. If these do not change and you do not reconstruct the
Makefiles, you do not have to specify this option each time you run
install.com.
With MPI
mpa -DATA -STACK -sc <name_of_subcomplex> \
~charmm/exe/cspp/charmm24 -np <n> <input_file >output_file &
Where <n> is the number of processors to use.
There are two environmanet variables that can be set:
setenv MPI_GLOBMEMSIZE <m>
where <m> is the size of the shared memory region on each hypernode
in bytes. The default is 16MB.
And:
setenv MPI_TOPOLOGY <i>,<j>,<k>,<l>,...
where <i>, <j>, <k>, <l>, ... are the number of tasks on each hypernode.
The sum must equal the number of processors specified with -np on the
command line. This is optional the default behavior is generally what
you want. If you are using a sub-complex with more than one hypernode,
use may want to include '-node 0' after mpa to keep the 0th process
on the 0th hypernode of the sub-complex.
Preflx directives required: CSPP UNIX PARALLEL PARAFULL HPUX
MPI CSPPMPI
The CSPPMPI directive specifies the use of extensions in the Convex
MPI implementation. This directive is optional. Use of the MPI
directive alone will result in a fully MPI Standard compliant program,
albeit with a loss of performance.
Note: The first time that you build CHARMM with MPI specify the M option
with install.com. You will be asked for the location of the MPI include
files and libraries. If these do not change and you do not reconstruct the
Makefiles, you do not have to specify this option each time you run
install.com.
6. Intel gamma
Because the fortran compiler on the Intel gamma does not know how
to rewind the redirected input file the program uses charmm.inp
file name from current working directory. The script for running
CHARMM should look like the following example:
cp input_file.inp charmm.inp
getcube -t128 > output_file
load ~charmm/exec/intel/charmm24
waitcube
Preflx directives required: INTEL UNIX PARALLEL PARAFULL
7. Intel Delta
mexec "-t(32,16)" ~charmm/exec/intel/charmm23<input_file>output_file&
Preflx directives required: INTEL UNIX DELTA PARALLEL PARAFULL
8. Intel Paragon
~charmm/exec/intel/charmm23 -sz 64 <input_file >output_file &
Preflx directives required: INTEL UNIX PARAGON PARALLEL PARAFULL
9. CM-5
~charmm/exec/cm5/charmm23 <input_file >output_file &
Preflx directives required:CM5 UNIX PARALLEL PARAFULL
10. IBM SP2 or SP1
setenv MP_RESD yes
setenv MP_PULSE 0
setenv MP_RMPOOL 1
setenv MP_EUILIB us
setenv MP_INFOLEVEL 0
poe ~charmm/exec/ibmsp/charmm24 -hfile nodes -procs 64 <input >output
See `man poe' for details.
Preflx directives required:IBMSP UNIX PARALLEL PARAFULL
Additional preflx directives recommended: EXPAND(fast parvect)
11. PVM
pvm
add host host1
add host host2
quit
setenv NTPVM 3
~/pvm3/bin/SGI5/charmm24 <input_file >output_file&
Preflx directives required: machine_type UNIX PARALLEL CMPI PVM
PARAFULL SYNCHRON
12. Linux clusters (Beowulf)
MPICH: (MPICH doesn't need to be installed on compute nodes)
~charmm/exec/gnu/charmm -p4wd . -p4pg file < input > output [charmm options]
where file is:
host1 0
host2 1 ~charmm/exec/gnu/charmm
host3 1 ~charmm/exec/gnu/charmm
etc.
[NOTE: host1 can be the same as host2, host3, etc. for
SMP]
LAM: (Every node has to have LAM installed!!)
lamboot -v hostfile
mpirun -O -c2c -w schema < input >output
where schema is a file:
~charmm/exec/gnu/charmm n0 -- [charmm options]
~charmm/exec/gnu/charmm n1 -- [charmm options]
~charmm/exec/gnu/charmm n2 -- [charmm options]
etc.
and hostfile is:
host1
host2
host3
etc.
13. PARALLEL VERSION OF CHARMM23 ON WORKSTATION CLUSTERS
Preflx directives required: machine_type UNIX PARALLEL CMPI SOCKET
PARAFULL SYNCHRON
Currently the code runs on HP, DEC alpha, and IBM RS/6000
machines. This has been tested. The rest of UNIX world should run
too without any changes as long as the following is true:
Assumptions for cluster environment:
Before you run CHARMM with SOCKET library you have to define some
environment variables. If you define nothing then CHARMM will
run in a scalar mode, i.e. default is one node run.
PWD
The program supports three shells: bash (Bourne Again SHell), ksh
(Korn Shell) and tcsh, which is available from anonymous ftp. The
only difference from csh on which CHARMM makes assumption is
definition of variable PWD. This variable is correctly defined in
all of the above three shells by default, while using csh it has
to be defined by the user. Variable PWD points to the current
working directory. If some other directory is requested the PWD
environment variable may be changed appropriately. The program
can figure out current working directory by itself but there are
problems in some NFS environments, because home directory names
can vary on different machines.( PWD is always defined correctly
by shell which supports it ) So csh may sometimes cause
problems. Using csh the cd command may be redefined so that it
always defines also PWD. This is done with something like: alias
cd 'chdir \!*; setenv PWD $cwd ' in the ~/.cshrc file.
If you get an error which looks something like nonexistent
directory then define PWD variable directly.
[NIH specific (for HPUX):
If you want to use tcsh as your login shell you may run the
following command:
runall chsh username /usr/local/bin/tcsh
runall is a script which runs the command on the whole cluster of
machines it is on /usr/local/bin at NIH. ]
NODEx
In order to run CHARMM on more then one node environment variables
NODE0, NODE1, ..., NODEn have to be defined.
Example for a 4 node run:
setenv NODE0 par0
setenv NODE1 par1
setenv NODE2 par2
setenv NODE3 par4
charmm < input_file > output_file 1:parameter1 2:parameter2 ...
"par0,par1,par2,.." are the names of the machines in the local
network. There is no requirement that all machines should be of
the same type. There is nothing in the program to adjust for
unequal load balance so all nodes will follow the slowest one. In
near future we may implement dynamic load balance method based on
actual time required.
The assumption here is that the node from where CHARMM program is
started is always NODE0!
Setup for your login environment
In order to run CHARMM in parallel you have to be able to rlogin to
any of the nodes defined in NODEx environment variables. Before you
run CHARMM check this out:
rlogin $NODE1
if it doesn't ask you for Password then you are OK. If it asks for
Password then put a line like this:
machine_name user_name
in your ~/.rhosts file, with 600 permission.
[NIH specific:
How to submit job to HP.
Currently we have assigned machines par0, par1, par2, and par4 to
work in parallel. You may use script
/usr/local/bin/charmm23.parallel and submit it to par0. Example:
submit par0 charmm23.parallel <input_file >output_file ^D
To construct your own parallel scripts look at
/usr/local/bin/charmm23.parallel ]
In the input scripts
Everything should work, but avoid usage of IOLEV and PRNLEV in your
parallel scripts.
Top
Syntax:
PARAllel { FIFO int }
{ BUFFer int }
{ CONCurrent int [ COUNT int MAXI int ] }
Description:
FIFO specifies priority for the Linux kernel FIFO scheduling
scheme. Larger number means higher priority. Zero is for the default
scheduling scheme.
BUFFer specifies the size of the sending and receiving buffer for the
MPI send/receive calls. It is in Real*8 units.
CONCurrent specifies the number of independent CHARMM jobs within a
single parallel run. If COUNt=0 it turns on the interleaving
communication between the 2 groups, ie one group is performing
communication while the other is doing calculation at the same
time. Interleaving stops after MAXI steps of dynamics.
Example:
The following example performs interleaving between 2 jobs. The total
number of nodes allocated has to be even. The input for job 1 has to
be in the file with the name 1.input and for job 2 in 2.input.
* This input script runs 2 separate jobs
paral conc 2 count 0 maxi 102 ! 1.input & 2.input are currently
! hardwired into paral1.src
Syntax:
PARAllel { FIFO int }
{ BUFFer int }
{ CONCurrent int [ COUNT int MAXI int ] }
Description:
FIFO specifies priority for the Linux kernel FIFO scheduling
scheme. Larger number means higher priority. Zero is for the default
scheduling scheme.
BUFFer specifies the size of the sending and receiving buffer for the
MPI send/receive calls. It is in Real*8 units.
CONCurrent specifies the number of independent CHARMM jobs within a
single parallel run. If COUNt=0 it turns on the interleaving
communication between the 2 groups, ie one group is performing
communication while the other is doing calculation at the same
time. Interleaving stops after MAXI steps of dynamics.
Example:
The following example performs interleaving between 2 jobs. The total
number of nodes allocated has to be even. The input for job 1 has to
be in the file with the name 1.input and for job 2 in 2.input.
* This input script runs 2 separate jobs
paral conc 2 count 0 maxi 102 ! 1.input & 2.input are currently
! hardwired into paral1.src
Top
Parallel Code Status (as of July 2003)
NOTE: c31a1 test directory contains 276 testcases. Out of these 22
cannot stop the execution by themself. 8 tests end with the ABNORMAL
termination and 246 with NORMAL termination, which of course this
doesn't guarantee that the method is working in parallel.
The following table is the result of this testing.
The symbol ++ indicates that parallel code development is underway.
-----------------------------------------------------
Fully parallel and functional features:
Energy evaluation
ENERgy, GETE, SKIPE, ENERgy ACE
MINImization (CONJ,NRPH,ABNR,POWEL,TN)
DYNAmics (leap frog integrator)
HBOND
BLOCK
CRYSTAL (all)
IMAGES
INTEraction energy
CONStraints (SHAKE,HARM,IC,DIHEdral,FIX,NOE,RESD,LONEPAIR)
ANAL (energy partition)
NBONds (generic)
EWALD
PME
PERT
GAMESS (ab initio part)
TEST FIRST, SECOND
REPLICA
TREK
EEF1
IMCUBES (bycb)
FSSHK (fast non-vector shake)
GENBORN
GBBLOCK
GRID
HMCM
BYCC
TSM
TMD
GRAPE
HQBM
ADUMB
MTS
SSBP
DRUDE
VV2
LONEPAIR
QCHEM
GAMESSUK
RPATH
QUB
FACTS
-----------------------------------------------------
Functional, but nonparallel code in the parallel version (no speedup):
( ** indicates that these can be very computationally intensive and are
not recommended on parallel systems)
VIBRAN **
CORREL **(Except for the energy time series evaluation, which is
parallel)
READ, WRITE, and PRINT (I/O in general)
NOTE:
always protect prnlev ...
with
if ?mynode .eq. 0 then prnlev ...
CORMAN commands
COPY, ORIENT, CONVERT, SURFACE,
CONTACT, VOLUME, LSQP, RGYR
HBUIld **
IC (internal coordinate commands)
SCALar commands
CONStraints (setup, DROPlet, SBOUnd)
Miscellaneous commands
GENErate, PATCh, DELEte, JOIN, RENAme, IMPAtch (all PSF
modification commands)
MERGE
QUANtum ** ++
QUICk
REWInd (not fully supported on the Intel)
SOLANA
SELECT
DEFINE
MONITOR
TEST
CMDPAR and flow control
PATH
RXNCOR
Commandline parameters (where supported by compiler)
RISM
ZMAT
AUTOGEN
CALC
BOUND
HELIX
WHAM
GRAPHICS
UMBRELLA
SBOUNDARY
PBEQ ++
GSBP
-----------------------------------------------------
Nonfunctional code in parallel version:
ANAL (table generation)
DYNAmics (old integrator, NOSE integrator, 4D)
MMFP
TRAVEL
VIBRAN (quasi, crystal)
BLOCK FREE
COOR COVARIANCE
ST2 waters
NMR
DIMB
ECONT
PULL
CFTI
LUP
GALGOR
BYCU
MC
4D DYNA
SCPISM
-----------------------------------------------------
Untested Features (we don't know if it works or not):
ANALysis
MOLVIB (minor problems with I/O - hangs the job)
PRESsure (the command)
RMSD
MBOND
MMFF
SHAPES
CLUSTER
Parallel Code Status (as of July 2003)
NOTE: c31a1 test directory contains 276 testcases. Out of these 22
cannot stop the execution by themself. 8 tests end with the ABNORMAL
termination and 246 with NORMAL termination, which of course this
doesn't guarantee that the method is working in parallel.
The following table is the result of this testing.
The symbol ++ indicates that parallel code development is underway.
-----------------------------------------------------
Fully parallel and functional features:
Energy evaluation
ENERgy, GETE, SKIPE, ENERgy ACE
MINImization (CONJ,NRPH,ABNR,POWEL,TN)
DYNAmics (leap frog integrator)
HBOND
BLOCK
CRYSTAL (all)
IMAGES
INTEraction energy
CONStraints (SHAKE,HARM,IC,DIHEdral,FIX,NOE,RESD,LONEPAIR)
ANAL (energy partition)
NBONds (generic)
EWALD
PME
PERT
GAMESS (ab initio part)
TEST FIRST, SECOND
REPLICA
TREK
EEF1
IMCUBES (bycb)
FSSHK (fast non-vector shake)
GENBORN
GBBLOCK
GRID
HMCM
BYCC
TSM
TMD
GRAPE
HQBM
ADUMB
MTS
SSBP
DRUDE
VV2
LONEPAIR
QCHEM
GAMESSUK
RPATH
QUB
FACTS
-----------------------------------------------------
Functional, but nonparallel code in the parallel version (no speedup):
( ** indicates that these can be very computationally intensive and are
not recommended on parallel systems)
VIBRAN **
CORREL **(Except for the energy time series evaluation, which is
parallel)
READ, WRITE, and PRINT (I/O in general)
NOTE:
always protect prnlev ...
with
if ?mynode .eq. 0 then prnlev ...
CORMAN commands
COPY, ORIENT, CONVERT, SURFACE,
CONTACT, VOLUME, LSQP, RGYR
HBUIld **
IC (internal coordinate commands)
SCALar commands
CONStraints (setup, DROPlet, SBOUnd)
Miscellaneous commands
GENErate, PATCh, DELEte, JOIN, RENAme, IMPAtch (all PSF
modification commands)
MERGE
QUANtum ** ++
QUICk
REWInd (not fully supported on the Intel)
SOLANA
SELECT
DEFINE
MONITOR
TEST
CMDPAR and flow control
PATH
RXNCOR
Commandline parameters (where supported by compiler)
RISM
ZMAT
AUTOGEN
CALC
BOUND
HELIX
WHAM
GRAPHICS
UMBRELLA
SBOUNDARY
PBEQ ++
GSBP
-----------------------------------------------------
Nonfunctional code in parallel version:
ANAL (table generation)
DYNAmics (old integrator, NOSE integrator, 4D)
MMFP
TRAVEL
VIBRAN (quasi, crystal)
BLOCK FREE
COOR COVARIANCE
ST2 waters
NMR
DIMB
ECONT
PULL
CFTI
LUP
GALGOR
BYCU
MC
4D DYNA
SCPISM
-----------------------------------------------------
Untested Features (we don't know if it works or not):
ANALysis
MOLVIB (minor problems with I/O - hangs the job)
PRESsure (the command)
RMSD
MBOND
MMFF
SHAPES
CLUSTER
Top
Note: Currently one should specify the absolute path to the pvm include
files and the pvm library files. This is done because PVM installation
is not currently standard. During installation, through use of
install.com, you are asked to specify these paths.
Convex PVM
This version runs using PVM (Parallel Virtual Machine) versions 3.2.6 and
higher. To run:
1. create hostfile - as in the example below:
#host file
puma0 dx=/usr/lib/pvm/pvmd3 ep=/chem/sfleisch/c24a2/exec/cspp
The first field (puma0) is the hostname of the machine. The dx= field
is the absolute path to the PVM daemon, pvmd3. This includes the
filename, pvmd3. The last field, ep= is the search path for find the
executable when the tasks are spawned. This can be a colon (:) separated
string for searching multiple directories. The PVM system can be
monitored using the console program, pvm. It has some useful commands:
conf list machines in the virtual machine.
ps -a list the tasks that are running.
help list the commands.
quit exit the console program without killing the daemon.
halt kill everything that is running and the daemon and exit
the console program.
2. Run the PVM daemon, pvmd3:
pvmd3 hostfile &
3. Run the program e.g.:
/chem/sfleisch/c24a2/exec/cspp/charmm -n <ncpu> <input_file >output_file
where -n <ncpu> indicates how many pvm controlled processes to run
4. Halt the daemon. See above.
The Convex Exemplar PVM implementation uses shared memory via the System V
IPC routines, shmget and shemat.
Generic PARALLEL PVM version for workstation clusters
Preflx directives required: <MACHTYPE> UNIX SCALAR CMPI PVM PARALLEL
PARAFULL SYNCHRON
Where <MACHTYPE> is the workstation you are compiling on, e.g.,
HPUX, ALPHA, etc.
Note: Currently one must specify the absolute path to the pvm include
files and the pvm library files. This is done because PVM installation
is not currently standard. During installation, through use of
install.com, you are asked to spceify these paths.
This version runs using PVM (Parallel Virtual Machine) versions 3.2.6 and
higher. To run:
1. create hostfile - as in the example below:
#host file
boa0 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa1 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa2 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa3 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
The first field (boa0, etc) is the hostname of the machine. The dx= field
is the absolute path to the PVM daemon, pvmd3. This includes the
filename, pvmd3. The last field, ep= is the search path for find the
executable when the tasks are spawned. This can be a colon (:) separated
string for searching multiple directories. The PVM system can be
monitored using the console program, pvm. It has some useful commands:
conf list machines in the virtual machine.
ps -a list the tasks that are running.
help list the commands.
quit exit the console program without killing the daemon.
halt kill everything that is running and the daemon and exit
the console program.
2. Run the PVM daemon, pvmd3:
pvmd3 hostfile &
3. Run the program e.g.:
/cb/manet1/c24a2/exec/hpux/charmm -n <ncpu> <input_file >output_file &
where -n <ncpu> indicates how many pvm controlled processes to run
4. Halt the daemon. See above.
Note: Currently one should specify the absolute path to the pvm include
files and the pvm library files. This is done because PVM installation
is not currently standard. During installation, through use of
install.com, you are asked to specify these paths.
Convex PVM
This version runs using PVM (Parallel Virtual Machine) versions 3.2.6 and
higher. To run:
1. create hostfile - as in the example below:
#host file
puma0 dx=/usr/lib/pvm/pvmd3 ep=/chem/sfleisch/c24a2/exec/cspp
The first field (puma0) is the hostname of the machine. The dx= field
is the absolute path to the PVM daemon, pvmd3. This includes the
filename, pvmd3. The last field, ep= is the search path for find the
executable when the tasks are spawned. This can be a colon (:) separated
string for searching multiple directories. The PVM system can be
monitored using the console program, pvm. It has some useful commands:
conf list machines in the virtual machine.
ps -a list the tasks that are running.
help list the commands.
quit exit the console program without killing the daemon.
halt kill everything that is running and the daemon and exit
the console program.
2. Run the PVM daemon, pvmd3:
pvmd3 hostfile &
3. Run the program e.g.:
/chem/sfleisch/c24a2/exec/cspp/charmm -n <ncpu> <input_file >output_file
where -n <ncpu> indicates how many pvm controlled processes to run
4. Halt the daemon. See above.
The Convex Exemplar PVM implementation uses shared memory via the System V
IPC routines, shmget and shemat.
Generic PARALLEL PVM version for workstation clusters
Preflx directives required: <MACHTYPE> UNIX SCALAR CMPI PVM PARALLEL
PARAFULL SYNCHRON
Where <MACHTYPE> is the workstation you are compiling on, e.g.,
HPUX, ALPHA, etc.
Note: Currently one must specify the absolute path to the pvm include
files and the pvm library files. This is done because PVM installation
is not currently standard. During installation, through use of
install.com, you are asked to spceify these paths.
This version runs using PVM (Parallel Virtual Machine) versions 3.2.6 and
higher. To run:
1. create hostfile - as in the example below:
#host file
boa0 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa1 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa2 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
boa3 dx=/usr/lib/pvm/pvmd3 ep=/cb/manet1/c24a2/exec/hpux
The first field (boa0, etc) is the hostname of the machine. The dx= field
is the absolute path to the PVM daemon, pvmd3. This includes the
filename, pvmd3. The last field, ep= is the search path for find the
executable when the tasks are spawned. This can be a colon (:) separated
string for searching multiple directories. The PVM system can be
monitored using the console program, pvm. It has some useful commands:
conf list machines in the virtual machine.
ps -a list the tasks that are running.
help list the commands.
quit exit the console program without killing the daemon.
halt kill everything that is running and the daemon and exit
the console program.
2. Run the PVM daemon, pvmd3:
pvmd3 hostfile &
3. Run the program e.g.:
/cb/manet1/c24a2/exec/hpux/charmm -n <ncpu> <input_file >output_file &
where -n <ncpu> indicates how many pvm controlled processes to run
4. Halt the daemon. See above.
Top
Implementation notes.
=====================
Currently the support for parallel machines in CHARMM is implemented
in three levels. The topmost level is the collection of subroutines
which are called from CHARMM itself. These subroutines are implemented
in paral1.src. They are:
VDGSUM - vector distributed global sum [MPI_REDUCE_SCATTER]
VDGBR - vector distributed global broadcast [MPI_ALLGATHERV]
GCOMB - Global combine (sum) [MPI_ALLREDUCE]
VDGBRE - vector distributed global broadcast (one vector only) [MPI_ALLGATHERV]
PSNDC - Broadcast character array from node 0. [MPI_BROADCAST]
PSND4 - Broadcast integer array from node 0. [MPI_BROADCAST]
PSND8 - Broadcast real*8 array from node 0. [MPI_BROADCAST]
PSYNC - Barrier [MPI_BARRIER]
PARFIN - Close the parallel setup [MPI_Finalize]
PARSTRT - Start and setup for parallel
PARCMD - PARAllel command parser
The above routines then by default call the MPI equivalents as
indicated above. Since the current status of MPI implementations is
not efficient on most of the parallel platforms we still maintain the
file. Besides the choice of standard MPI library and CMPI there are
other choices available in paral1.src for the vendor specific
libraries which have similar functionality as MPI library. Currently
these are CSPP and TERRA options. So in short paral1.src is a place
where one decides which library will be used for global parallel
communication, such as global sum and others. It may also decide on
machine specific libraries if they differ from MPI, but provide the
same functionality (TERRA example).
For the users of MPI library there are always two possibilities:
1. Don't specify anything except PARALLEL PARAFULL in pref.dat and use
global communication as implemented in MPI.
2. Specify PARALLEL PARAFULL CMPI MPI and use the efficient global
communication algorithms implemented the paral2.src and paral3.src,
where only two primitive MPI calls are used: send and recieve. This
choice is currently the preferred one on most of the systems
especially for users of MPICH and its derivatives.
Once CMPI keyword is specified the routines in paral1.src call
another set of routines implemented in the paral2.src source file. The
purpose of routines in this layer is to decide on which topology will
be chosen for a given parallel system. Possible choices are:
1. recursive halving sutable for hypercube or switched networks. This
is the default selection.
2. ring topology suitable for ring networks or any other where non
power of two number of processors is selected. This is selected at
compile time with the keyword GENCOMM in pref.dat.
3. mesh topology for two dimensional mesh network connection, also
sometimes works the best with FAT tree topology. Selected by
DELTA in pref.dat.
4. Each of the topology is by default implemented using send/receive
routine which is capable of receiving data from the other processor
while sending to it at the same time. If this is not supported by
the hardware one can choose SYNCHRON keyword in pref.dat.
All of the above topologies are then implemented in paral3.src file
for a variety of parallel systems.
I/O requirements for the new code
=================================
Each fortran WRITE statement has to be protected by PRNLEV, for
example:
IF(PRNLEV.GT.2) WRITE(OUTU,55) CALLNAME,N,INBLOX(NATOM)
instead of just simply:
WRITE(OUTU,55) CALLNAME,N,INBLOX(NATOM)
READ statements are a little bit more complicated and they are
controled by IOLEV. Example:
IF(IOLEV.GT.0) THEN
READ(UNIT)(X(I),Y(I),Z(I),I=1,NATOM)
ENDIF
#if KEY_PARALLEL==1
CALL PSEND8(X,NATOM)
CALL PSEND8(Y,NATOM)
CALL PSEND8(Z,NATOM)
#endif
Any further information can be obtained from milan@cmm.ki.si.
See also the current parallel performance table at:
http://arg.cmm.ki.si/parallel/summary.html
Implementation notes.
=====================
Currently the support for parallel machines in CHARMM is implemented
in three levels. The topmost level is the collection of subroutines
which are called from CHARMM itself. These subroutines are implemented
in paral1.src. They are:
VDGSUM - vector distributed global sum [MPI_REDUCE_SCATTER]
VDGBR - vector distributed global broadcast [MPI_ALLGATHERV]
GCOMB - Global combine (sum) [MPI_ALLREDUCE]
VDGBRE - vector distributed global broadcast (one vector only) [MPI_ALLGATHERV]
PSNDC - Broadcast character array from node 0. [MPI_BROADCAST]
PSND4 - Broadcast integer array from node 0. [MPI_BROADCAST]
PSND8 - Broadcast real*8 array from node 0. [MPI_BROADCAST]
PSYNC - Barrier [MPI_BARRIER]
PARFIN - Close the parallel setup [MPI_Finalize]
PARSTRT - Start and setup for parallel
PARCMD - PARAllel command parser
The above routines then by default call the MPI equivalents as
indicated above. Since the current status of MPI implementations is
not efficient on most of the parallel platforms we still maintain the
file. Besides the choice of standard MPI library and CMPI there are
other choices available in paral1.src for the vendor specific
libraries which have similar functionality as MPI library. Currently
these are CSPP and TERRA options. So in short paral1.src is a place
where one decides which library will be used for global parallel
communication, such as global sum and others. It may also decide on
machine specific libraries if they differ from MPI, but provide the
same functionality (TERRA example).
For the users of MPI library there are always two possibilities:
1. Don't specify anything except PARALLEL PARAFULL in pref.dat and use
global communication as implemented in MPI.
2. Specify PARALLEL PARAFULL CMPI MPI and use the efficient global
communication algorithms implemented the paral2.src and paral3.src,
where only two primitive MPI calls are used: send and recieve. This
choice is currently the preferred one on most of the systems
especially for users of MPICH and its derivatives.
Once CMPI keyword is specified the routines in paral1.src call
another set of routines implemented in the paral2.src source file. The
purpose of routines in this layer is to decide on which topology will
be chosen for a given parallel system. Possible choices are:
1. recursive halving sutable for hypercube or switched networks. This
is the default selection.
2. ring topology suitable for ring networks or any other where non
power of two number of processors is selected. This is selected at
compile time with the keyword GENCOMM in pref.dat.
3. mesh topology for two dimensional mesh network connection, also
sometimes works the best with FAT tree topology. Selected by
DELTA in pref.dat.
4. Each of the topology is by default implemented using send/receive
routine which is capable of receiving data from the other processor
while sending to it at the same time. If this is not supported by
the hardware one can choose SYNCHRON keyword in pref.dat.
All of the above topologies are then implemented in paral3.src file
for a variety of parallel systems.
I/O requirements for the new code
=================================
Each fortran WRITE statement has to be protected by PRNLEV, for
example:
IF(PRNLEV.GT.2) WRITE(OUTU,55) CALLNAME,N,INBLOX(NATOM)
instead of just simply:
WRITE(OUTU,55) CALLNAME,N,INBLOX(NATOM)
READ statements are a little bit more complicated and they are
controled by IOLEV. Example:
IF(IOLEV.GT.0) THEN
READ(UNIT)(X(I),Y(I),Z(I),I=1,NATOM)
ENDIF
#if KEY_PARALLEL==1
CALL PSEND8(X,NATOM)
CALL PSEND8(Y,NATOM)
CALL PSEND8(Z,NATOM)
#endif
Any further information can be obtained from milan@cmm.ki.si.
See also the current parallel performance table at:
http://arg.cmm.ki.si/parallel/summary.html