CHARMM c30b1 parallel.doc

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                Parallel Implementation of CHARMM


CHARMM has been modified to allow computationally intensive simulations
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)

* Menu:


* 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


File: Parallel ]-[ Node: Installation
Next: Running -=- Previous: Top -=- Up: Top\n


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.

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)

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 installation script now installs default configuration for any
parallel platform. If one of X,G,P,M,1,2,64,Q,S is specified size
keyword must be specified too. Run install.com without parameters
for current set of options.

Installation command for parallel machines with relevant options:

1. Cray T3E

install.com t3e [size] [Q] [P] or [M]

2. Cray T3D

install.com t3d [size] [Q] [P] or [M]

3. Cray C90, J90

install.com t3d [size] 

4. SGI Power Origin

install.com sgi64 size M [Q] [X] 

uname -a : IRIX64 icpsg1 6.2 03131016 IP25

5. SGI Power Chellenge

install.com sgi size P 64 [Q] [X] 

uname -a : IRIX64 icpsg1 6.2 03131016 IP25

4a. SGI Origin

install.com sgi64 size M 64
/usr/include
/usr/lib64 

uname -a : IRIX64 atlas 6.5 04131233 IP27

6. Convex SPP-1000 or SPP-2000

install.com cspp size P or M [Q]

7. Intel Paragon machine

install.com intel

uname -a : Paragon OSF/1 timewarp 1.0.4 R1_4 paragon

8. IBM SP1/SP2 machines

install.com ibmsp size [Q]

uname -a: AIX f1n3 1 4 000104697000

8a. IBM SP3 machines

install.com ibmsp3 size [Q]


9. Generic Parallel Virtual Machine (PVM)

install.com machine size P

10. TERRA 2000

install.com terra size

11. Workstation clusters

install.com machine size S [Q] [X]

12. Alpha Servers (SMP)

install.com alphamp size M

13. Cluster of PCs using GNU/Linux OS - Beowulf class of machines


A. Using RedHat-6.0:
   =================
   Get and instal the official LAM MPI rpm package from
   rpm -i http://www.mpi.nd.edu/downloads/lam/lam-6.31b1-tcp.1.i386.rpm

   install.com gnu size M [Q] [X] # this asks 2 question - answers are:
   /usr/local/lam-6.3-b1/include
   /usr/local/lam-6.3-b1/lib

B. Using Debian-potato:
   ====================
   One can use g77 with either lam or mpich (preferred)

   install.com gnu size M [Q] [X] # this asks 2 question - answers are:
   /usr/include/lam
   /usr/lib/lam/lib

   or

   install.com gnu size M mpich [Q] [X] # this asks 2 question - answers are:
   /usr/lib/mpich/build/LINUX/ch_p4/include
   /usr/lib/mpich/build/LINUX/ch_p4/lib

This small performance table executed on a single processor Pentium
II/450MHz machine might help you to decide which system/compiler is
best for your needs:

B1 = 50 steps of MbCO dynamcs + water with spherical cutoffs
B2 = 25 steps of MbCO dynamcs + water with PM Ewald
B3 = 10 steps of minimization of QM/MM for alanine

All timing in seconds of elapsed time on empty machines using the
above install procedure. (This table was made July 31, 99).

Benchmark  |  g77/RH-6.0 | g77*/Debian| f2c/Debian | pgf77   | f77/Absoft
=========================================================================
    B1     |    290.6 s  |   197.6 s  |  211.1 s   | 189.5 s |  196.0 s 
-------------------------------------------------------------------------
    B2     |    223.3 s  |   193.7 s  |  234.6 s   | 199.2 s |  211.3 s
-------------------------------------------------------------------------
    B3     |     70.5 s  |    64.3 s  |   74.3 s   |  59.8 s |not working
=========================================================================

g77*/Debian is the newest g77-2.95 compiler from July 31, 1999. pgf77
and f77/Absoft are also the most recent versions.

[NOTE: pgf77 and MPI don't work out of the box. One has to recompile
MPI library with explicit pgf77 support. Also, these are the findings
running testcases (July 1999):

       
       compiler   |  f2c  | g77  | pgf77 
       ---------------------------------
       NORMAL T.  |  152  | 152  |  133 
       ---------------------------------
       ABNORMAL T.|   26  |  26  |   23 
       ---------------------------------
       segm. fault|    4  |   4  |   23 
       ---------------------------------
       total #    |  186  | 186  |  186 
       ---------------------------------

The difference between the total and the sum of other numbers is in
the problems of CHARMM testcases suite.
]

                     -----


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.)
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.

Machine specific keywords:

TERRA
CM5
CSPP
DELTA
INTEL
PARAGON
SHMEM
CSPPMPI
T3D
T3E
IBMSP
ALPHAMP
SGIMP



File: Parallel ]-[ Node: Running
Next: PARAllel -=- Previous: Installation Top -=- Up: Top\n

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 see *note 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.




File: Parallel ]-[ Node: PARAllel
Next: Status -=- Previous: Running -=- Up: Top\n

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





File: Parallel ]-[ Node: Status
Previous: PARAllel -=- Up: Top -=- Next: Using PVM\n

Parallel Code Status (as of September 1998)

NOTE: c27a1 test directory contains 161 testcases. Out of them
10 didn't pass because the code was not compiled. The other 58 failed
to give the same results when run as parallel job compared with single
CPU run. The rest 90 passed OK. [CHANGE THE NUMBERS!!!!] 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

     EEF1

     IMCUBES (bycb)
     RCFFT
     FSSHK   (fast non-vector shake)
     GENBORN
     GBBLOCK
     GRID
     HMCM
     RCFFT
     BYCC
     TSM
     TMD     

-----------------------------------------------------

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

     HBONds

     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  ++

     HQBM

-----------------------------------------------------

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
     
     
-----------------------------------------------------

Untested Features (we don't know if it works or not):
     ANALysis

     MOLVIB  (No testcase for this code?)

     PRESsure (the command)

     RMSD

     MBOND

     MMFF

     SHAPES

     CLUSTER




File: Parallel ]-[ Node: Using PVM
Previous: Status -=- Up: Top -=- Next: Implementation\n


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.



File: Parallel ]-[ Node: Implementation
Previous: Using PVM -=- Up: Top -=- Next: Top\n

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
CHARMM implementation of MPI chosen by CMPI preflx keyword in pref.dat
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 PARALLEL
      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


CHARMM .doc Homepage


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