  Linux Cluster HOWTO
  Ram Samudrala (me@ram.org)
  v0.3,  August 21, 2001

  How to set up high-performance Linux computing clusters.
  ______________________________________________________________________

  Table of Contents


  1. Introduction

  2. Hardware

     2.1 Node hardware
     2.2 Server hardware
     2.3 Desktop hardware
     2.4 Putting-it-all-together hardware
     2.5 Costs

  3. Software

     3.1 Linux, of course!
     3.2 Costs

  4. Set up and configuration

     4.1 Disk configuration
     4.2 Package configuration
     4.3 Operating system installation
        4.3.1 Cloning
        4.3.2 DHCP vs. hard-coded IP addresses

  5. Performing tasks on the cluster

  6. Acknowledgements

  7. Bibliography



  ______________________________________________________________________

  1.  Introduction

  This document describes how I set up my Linux computing clusters for
  high-performance computing which I need for my research.

  Use the information below at your own risk.  I disclaim all
  responsibility for anything you may do after reading this HOWTO. The
  latest version of this HOWTO will always be available at
  http://www.ram.org/computing/linux/linux_cluster.html.

  Unlike other documentation that talks about setting up clusters in a
  general way, this is a specific description of how our lab is setup
  and includes not only details the compute aspects, but also the
  desktop, laptop, and public server aspects.  This is done mainly for
  local use, but I put it up on the web since I received several e-mail
  messages based on my newsgroup query requesting the same information.
  The main use as it stands is that it's a report on what kind of
  hardware works well with Linux and what kind of hardware doesn't.

  2.  Hardware

  This section covers the hardware choices I've made. Unless noted,
  assume that everything works really well.
  Hardware installation is also fairly straight-forward unless otherwise
  noted, with most of the details covered by the manuals.

  2.1.  Node hardware

  32 machines have the following setup each:


    2 Pentium III 1 GHz Intel CPUs

    Supermicro 370 DLE Dual PIII-FCPGA motherboard

    2 256 MB 168-pin PC133 Registered ECC Micron RAM

    1 20 GB Maxtor ATA/66 5400 RPM HD

    1 40 GB Maxtor UDMA/100 7200 RPM HD

    Asus CD-S500 50x CDROM

    1.4 MB floppy drive

    ATI Expert 98 8 MB PCI video card

    Mid-tower case

  2.2.  Server hardware

  1 external server with the following setup:


    2 Pentium III 1 GHz Intel CPUs

    Supermicro 370 DLE Dual PIII-FCPGA motherboard

    2 256 MB 168-pin PC133 Registered ECC Micron RAM

    1 20 GB Maxtor ATA/66 5400 RPM HD

    2 40 GB Maxtor UDMA/100 7200 RPM HD

    Asus CD-S500 50x CDROM

    1.4 MB floppy drive

    ATI Expert 98 8 MB PCI video card

    Full-tower case

  2.3.  Desktop hardware

  4 desktops with the following setup:


    2 Pentium III 1 GHz Intel CPUs

    Supermicro 370 DE6 Dual PIII-FCPGA motherboard

    4 256 MB 168-pin PC133 Registered ECC Micron RAM

    3 40 GB Maxtor UDMA/100 7200 RPM HD

    Ricoh 32x12x10 CDRW/DVD Combo EIDE

    1.4 MB floppy drive

    Asus V7700 64mb GeForce2-GTS AGP video card

    Creative SB Live Platinum 5.1 sound card

    Microsoft Natural Keyboard

    Microsoft Intellimouse Explorer

    Full-tower case

  2 desktops with the following setup:


    2 Pentium III 1 GHz Intel CPUs

    Supermicro 370 DLE Dual PIII-FCPGA motherboard

    4 256 MB 168-pin PC133 Registered ECC Micron RAM

    3 40 GB Maxtor UDMA/100 7200 RPM HD

    Mitsumi 8x/4x/32x CDRW

    1.4 MB floppy drive

    Jaton Nvidia TNT2 32mb PCI

    Creative SB LIVE Value PCI

    Microsoft Natural Keyboard

    Microsoft Intellimouse Explorer

    Full-tower case


  2 desktops with the following setup:


    2 Pentium III 1 GHz Intel CPUs

    Supermicro 370 DLE Dual PIII-FCPGA motherboard

    4 256 MB 168-pin PC133 Registered ECC Micron RAM

    3 40 GB Maxtor UDMA/100 7200 RPM HD

    Asus CD-S500 50x CDROM

    1.4 MB floppy drive

    Jaton Nvidia TNT2 32mb PCI

    Creative SB LIVE Value PCI

    Microsoft Natural Keyboard

    Microsoft Intellimouse Explorer

    Full-tower case


  Backup:



    2 Sony 20/40 GB DSS4 SE LVD DAT

  Monitors:


    4 21" Sony CPD-G500 .24mm monitor

    2 18" Viewsonic VP-181 TFT-LCD monitor

  2.4.  Putting-it-all-together hardware

  We use KVM switches with a cheap monitor to connect up and "look" at
  all the machines:


    15" .28dp XLN CTL Monitor

    3 Belkin Omniview 16-Port Pro Switches

    40 KVM cables

  While this is a nice solution, I think it's kind of needless. What we
  need is a small hand held monitor that can plug into the back of the
  PC (operated with a stylus, like the Palm). I don't plan to use more
  monitor switches/KVM cables.

  Networking is important:


    1 Cisco Catalyst 3448 XL Enterprise Edition network switch.

  2.5.  Costs

  Our vendor is Hard Drives Northwest (http://www.hdnw.com). For each
  compute node in our cluster (containing two processors), we paid about
  $1500, including taxes. Generally, our goal is to keep each node to
  below $2000.00 (which is what our desktop machines cost).

  3.  Software

  3.1.  Linux, of course!

  Specfically we use 2.2.17-14 kernel based on the KRUD 7.0
  distribution. We use our own software for parallising applications but
  have experimented with PVM and MPI. In my view, the overhead for these
  pre-packaged programs is too high.

  3.2.  Costs

  Linux is freely copiable.

  4.  Set up and configuration

  4.1.  Disk configuration

  This section describes disk partitioning strategies.



  farm/cluster machines:

  hda1 - swap  (2 * RAM)
  hda2 - /     (remaining disk space)
  hdb1 - /maxa (total disk)

  desktops (without windows):

  hda1 - swap  (2 * RAM)
  hda2 - /     (4 GB)
  hda3 - /home (remaining disk space)
  hdb1 - /maxa (total disk)
  hdd1 - /maxb (total disk)

  desktops (with windows):

  hda1 - /win  (total disk)
  hdb1 - swap  (2 * RAM)
  hdb2 - /     (4 GB)
  hdb3 - /home (remaining disk space)
  hdd1 - /maxa (total disk)

  laptops (single disk):

  hda1 - /win  (half the total disk size)
  hda2 - swap  (2 * RAM)
  hda3 - /     (4 GB)
  hda4 - /home (remaining disk space)



  4.2.  Package configuration

  Install a minimal set of packages for the farm. Users are allowed to
  configure desktops as they wish.

  4.3.  Operating system installation

  4.3.1.  Cloning

  I believe in having a completely distributed system. This means each
  machine contains a copy of the operating system.  Installing the OS on
  each machine manually is cumbersome. To optimise this process, what I
  do is first set up and install one machine exactly the way I want to.
  I then create a tar and gzipped file of the entire system and place it
  on a CD-ROM which I then clone on each machine in my cluster.

  The commands I use to create the tar file are as follows:



       tar -czvlps --same-owner --atime-preserve -f /maxa/slash.tgz /



  I use have a script called go that takes a hostname and IP address as
  its arguments and untars the slash.tgz file on the CD-ROM and replaces
  the hostname and IP address in the appropriate locations. A version of
  the go script and the input files for it can be accessed at:
  http://www.ram.org/computing/linux/linux/cluster/. This script will
  have to be edited based on your cluster design.

  To make this work, I also use Tom's Root Boot package
  http://www.toms.net/rb/ to boot the machine and clone the system.  The
  go script can be placed on a CD-ROM or on the floppy containing Tom's
  Root Boot package (you need to delete a few programs from this package
  since the floppy disk is stretched to capacity).

  More conveniently, you could burn a bootable CD-ROM containing Tom's
  Root Boot package, including the go script, and the tgz file
  containing the system you wish to clone.  You can also edit Tom's Root
  Boot's init scripts so that it directly executes the go script (you
  will still have to set IP addresses if you don't use DHCP).

  Thus you can develop a system where all you have to do is insert a
  CDROM, turn on the machine, have a cup of coffee (or a can of coke)
  and come back to see a full clone. You then repeat this process for as
  many machines as you have. This procedure has worked extremely well
  for me and if you have someone else actually doing the work (of
  inserting and removing CD-ROMs) then it's ideal.

  4.3.2.  DHCP vs. hard-coded IP addresses

  If you have DHCP set up, then you don't need to reset the IP address
  and that part of it can be removed from the go script.

  DHCP has the advantage that you don't muck around with IP addresses at
  all provided the DHCP server is configured appropriately. It has the
  disadvantage that it relies on a centralised server (and like I said,
  I tend to distribute things as much as possible). Also, linking
  hardware ethernet addresses to IP addresses can make it inconvenient
  if you wish to replace machines or change hostnames routinely.

  5.  Performing tasks on the cluster

  This section is still being developed as the usage on my cluster
  evolves, but so far we tend to write our own sets of message passing
  routines to communicate between processes on different machines.

  Many applications, particularly in the computational genomics areas,
  are massively and trivially parallelisable, meaning that perfect
  distribution can be achieved by spreading tasks equally across the
  machines (for example, when analysing a whole genome using a single
  gene technique, each processor can work on one gene at a time
  independent of all the other processors).

  So far we have not found the need to use a professional queing system,
  but obviously that is highly dependent on the type of applications you
  wish to run.

  6.  Acknowledgements

  The following people have been helpful in getting this HOWTO done:


    Michael Levitt (Michael Levitt)

  7.  Bibliography

  The following documents may prove useful to you---they are links to
  sources that make use of high-performance computing clusters:


    RAMBIN web page <http://www.ram.org/computing/rambin/rambin.html>

    RAMP web page <http://www.ram.org/computing/ramp/ramp.html>

    Ram Samudrala's research page (which describes the kind of research
     done with these clusters)
     <http://www.ram.org/research/research.html>
