Parallel Virtual Machine

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Parallel Virtual Machine

Rama Vykunta
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Introduction

• PVM provides a unified frame work for developing
  parallel programs with the existing
  infrastructure
• PVM enables a collection of heterogeneous
  computer systems as a single parallel virtual
  machine
• Transparent to the user

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Introduction

• A simple computing model based on tasks is used
  which is given by a set of well defined function
  calls
• An application is written as a set of
  co-operating tasks
• Processes communicate/synchronize with other
  processes

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Introduction

• Process management, machine configuration and
  support for input/output is possible
• User can configure the hosts according to the
  demand. He can position certain tasks on the most
  appropriate machines
• Unit of parallelism in PVM is a task

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• All tasks on PVM cooperate by sending and
  receiving messages from one another
• PVM supports functional and data parallelism
• A well defined library of PVM interface routines
  are used for programming

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Details

• PVM system is composed of two parts
• Daemon(pvmd) that resides on all computers
  making the virtual machine
• The second part of the system is a library of
  PVM interface routines
• All PVM tasks are identified by an integer task
  identifier (TID)
• A task can join or leave any group any time
  without having to inform any other task in the
  affected groups

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Details

• User can write programs in C, C or Fortran
  which contain embedded calls to the PVM library
• Starting PVM
• pvm
• pvmgtadd hostname
• pvmgtdelete hostname
• pvmgtconf
• pvmgtps -a
• pvmgthalt

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Details

• To compile use architecture independent aimk
  which automatically determines the architecture
  and links any OS specific libraries to the
  application
• PVM supports use of multiple consoles, it is
  possible to run a console on any host and also to
  run multiple consoles on the same machine

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Details

• PVM supports two models of computation namely
  crowd computing and tree computing.
• Crowd computing is a collection of closely
  related processes, typically executing the same
  code
• Tree computing in which processes are spawned
  dynamically as the computation progresses

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Example

• main()
• int cc, tid, msgtag
• char buf100
• printf(Im tx\n, pvm_mytid())
• cc pvm_spawn(hello_other, (char)0, 0, ,
  1, tid)
• if(cc 1)
• msgtag 1
• pvm_recv(tid, msgtag)
• pvm_upkstr(buf)
• printf(from tx s\n, tid, buf)
• else
• printf(cant start hello_other\n)
• pvm_exit()

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Example

• include pvm3.h
• main()
• int ptid, msgtag
• char buf100
• ptid pvm_parent()
• strcpy(buf, hello, world from)
• gethostname(buf strlen(buf), 64)
• msgtag 1
• pvm_initsend(PvmDataDefault)
• pvm_upkstr(buf)
• pvm_send(ptid, msgtag)
• pvm_exit()

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Example

• After printing the task ID it initiates the copy
  of the other program called hello_other using
  pvm_spawn() function.
• The main program recieves the message using
  pvm_recv() function and the buffer is exracted by
  pvm_upkstr()
• The final pvm_exit() call dissociates the
  program from the PVM system

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XPVM

• XPVM is a GUI tool for analyzing the parallel
  programs in PVM
• XPVM is can be used as a trace monitor and a
  call-level debugger extension to the PVM
• XPVM is based on PVM, TCL and TK
• XPVM can be used to view task utilization,
  network view, space-time view and message-queue
  view.

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XPVM

• Hosts can be added and removed form the virtual
  machine
• Using the task menu, tasks can be spawned, killed
  or signaled
• Each host is connected to the network by a link
  and a color is used to indicate the state of the
  host
• Green Actively running the tasks
• White Host is idling
• Yellow Host is not busy collecting information

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XPVM

• Space - Time view displays the status of the
  tasks and hosts during a program execution
• Utilization view shows the overall computing
  state during a given instance
• Trace view prints the tasks during each instance
  of activity
• Event History view contains all the trace events
  in the trace file

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References

• PVM Parallel Virtual Machine A Users' Guide and
  Tutorial for Networked Parallel Computing
• MIT Press Scientific and Engineering
  Computation