  Linux Cluster HOWTO
  Ram Samudrala (me@ram.org)
  v1.5, September 5, 2005

  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 and terminal hardware
     2.4 Miscellaneous/accessory hardware
     2.5 Putting-it-all-together hardware
     2.6 Costs

  3. Software
     3.1 Operating system: Linux, of course!
     3.2 Networking software
     3.3 Parallel processing software
     3.4 Costs

  4. Set up, configuration, and maintenance
     4.1 Disk configuration
     4.2 Package configuration
     4.3 Operating system installation and maintenance
        4.3.1 Personal cloning strategy
        4.3.2 Cloning and maintenance packages
           4.3.2.1 FAI
           4.3.2.2 SystemImager
        4.3.3 DHCP vs. hard-coded IP addresses
     4.4 Known hardware issues
     4.5 Known software issues

  5. Performing tasks on the cluster
     5.1 Rough benchmarks
     5.2 Uptimes

  6. Acknowledgements
  7. Bibliography


  ______________________________________________________________________

  [1m1.  Introduction[0m

  This document describes how we set up our Linux computing clusters for
  high-performance computing which we need for our 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.
  Even today, as I plan another 64-node cluster, I find that there is a
  dearth of information about exactly how to assemble components to form
  a node that works reliably under Linux that includes information not
  only about the compute nodes, but about hardware that needs to work
  well with the nodes for productive research to happen.  The main use
  of this HOWTO 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.

  [1m2.  Hardware[0m

  This section covers the hardware choices I've made. Unless noted in
  the ``known hardware issues'' section, assume that everything works
  [4mreally[24m well.

  Hardware installation is also fairly straight-forward unless otherwise
  noted, with most of the details covered by the manuals. For each
  section, the hardware is listed in the order of purchase (most recent
  is listed first).

  [1m2.1.  Node hardware[0m

  32 machines have the following setup each:


  ·  2 XEON 2.66GHZ 533FSB CPUs

  ·  Supermicro 6013A-T 1u case and motherboard

  ·  2 512MB PC2100 DDR REG ECC RAM

  ·  1 80GB SEA 7200 SATA HD

  ·  1 250GB SEA 7200 SATA HD

  32 machines have the following setup each:


  ·  2 XEON 2.4GHZ 533FSB CPUs

  ·  Supermicro X5DPR-1G2 motherboard

  ·  2 512MB PC2100 DDR REG ECC RAM

  ·  1 40GB SEA 7200 HD

  ·  1 120GB SEA 7200 HD

  ·  Supermicro Slim 24X CDROM

  ·  CSE-812 400 C/B 1U case

  32 machines have the following setup each:


  ·  2 AMD Palamino MP XP 2000+ 1.67 GHz CPUs

  ·  Asus A7M266-D w/LAN Dual DDR motherboard

  ·  2 Kingston 512mb PC2100 DDR-266MHz REG ECC RAM

  ·  1 41 GB Maxtor 7200rpm ATA100 HD

  ·  1 120 GB Maxtor 5400rpm ATA100 HD

  ·  Asus CD-A520 52x CDROM

  ·  1.44mb floppy drive


  ·  ATI Expert 2000 Rage 128 32mb

  ·  IN-WIN P4 300ATX Mid Tower case

  ·  Enermax P4-430ATX power supply

  32 machines have the following setup each:


  ·  2 AMD Palamino MP XP 1800+ 1.53 GHz CPUs

  ·  Tyan S2460 Dual Socket-A/MP motherboard

  ·  Kingston 512mb PC2100 DDR-266MHz REG ECC RAM

  ·  1 20 GB Maxtor UDMA/100 7200rpm HD

  ·  1 120 GB Maxtor 5400rpm ATA100 HD

  ·  Asus CD-A520 52x CDROM

  ·  1.44mb floppy drive

  ·  ATI Expert 98 8mb AGP video card

  ·  IN-WIN P4 300ATX Mid Tower case

  ·  Intel PCI PRO-100 10/100Mbps network card

  ·  Enermax P4-430ATX power supply

  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

  ·  IN-WIN P4 300ATX Mid Tower case

  [1m2.2.  Server hardware[0m

  Two servers for external use (dissemination of information) with the
  following setups:


  ·  2 AMD Opteron 240 1.4 GHz CPUs

  ·  RIOWORKS HDAMB DUAL OPTERON motherboard

  ·  4 KINGSTON 512MB PC3200 REG ECC RAM

  ·  80GB MAX 7200 UDMA 133 HD

  ·  6 200GB WD 7200 8MB HD

  ·  ASUS 52X CD-A520 CDROM

  ·  1.44mb floppy drive

  ·  Antec 4U22ATX550EPS 4u case


  ·  2 AMD Palamino MP XP 2000+ 1.67 GHz CPUs

  ·  Asus A7M266-D w/LAN Dual DDR

  ·  4 Kingston 512mb PC2100 DDR-266MHz REG ECC RAM

  ·  Asus CD-A520 52x CDROM

  ·  1 41 GB Maxtor 7200rpm ATA100 HD

  ·  6 120 GB Maxtor 5400rpm ATA100 HD

  ·  1.44mb floppy drive

  ·  ATI Expert 2000 Rage 128 32mb

  ·  IN-WIN P4 300ATX mid tower case

  ·  Enermax P4-430ATX power supply

  [1m2.3.  Desktop and terminal hardware[0m

  We have identified at least two kinds of users of our cluster: those
  that need (i.e., take advantage of) permanent local processing power
  and disk space in conjunction with the cluster to speed up processing,
  and those that just need only the cluster processing power. The former
  are assigned "desktops" which are essentially high-performance
  machines, and the latter are assigned dumb "terminals". Our desktops
  are usually dual or quad processor machines with the current high-end
  CPU being a 1.6 GHz Opteron, having as much as 10 GB of RAM, and over
  1 TB of local disk space. Our terminals are essentially machines where
  a user can log in and then run jobs on our farm.  In this setup,
  people may also use laptops as dumb terminals.

  [1m2.4.  Miscellaneous/accessory hardware[0m

  We generally use/prefer Viewsonic monitors, Microsoft Intellimouse
  mice, and Microsoft Natural keyboards. These generally have worked
  quite reliably for us.

  [1m2.5.  Putting-it-all-together hardware[0m

  For visual access to the nodes, we initially used to use KVM switches
  with a cheap monitor to connect up and "look" at all the machines.
  While this was a nice solution, it did not scale. We currently wheel a
  small monitor around and hook up cables as needed.  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).

  For networking, we generally use Netgear and Cisco switches.

  [1m2.6.  Costs[0m

  Our vendor is Hard Drives Northwest (http://www.hdnw.com). For each
  compute node in our cluster (containing two processors), we paid about
  $1500-$2000, including taxes. Generally, our goal is to keep the cost
  of each processor to below $1000 (including housing it).
  [1m3.  Software[0m

  [1m3.1.  Operating system: Linux, of course![0m

  The following kernels and distributions are what are being used:


  ·  Kernel 2.2.16-22, distribution KRUD 7.0

  ·  Kernel 2.4.9-7, distribution KRUD 7.2

  ·  Kernel 2.4.18-10, distribution KRUD 7.3

  ·  Kernel 2.4.20-13.9, distribution KRUD 9.0

  ·  Kernel 2.4.22-1.2188, distribution KRUD 2004-05

  These distributions work very well for us since updates are sent to us
  on CD and there's no reliance on an external network connection for
  updates. They also seem "cleaner" than the regular Red Hat
  distributions, and the setup is extremely stable.

  [1m3.2.  Networking software[0m

  We use Shorewall 1.3.14a ((http://www.shorewall.net) for the firewall.

  [1m3.3.  Parallel processing software[0m

  We use our own software for parallelising applications but have
  experimented with PVM <http://www.csm.ornl.gov/pvm/pvm_home.html> and
  MPI <http://www-unix.mcs.anl.gov/mpi/mpich/>. In my view, the overhead
  for these pre-packaged programs is too high.  I recommend writing
  application-specific code for the tasks you perform (that's one
  person's view).

  [1m3.4.  Costs[0m

  Linux and most software that run on Linux are freely copiable.

  [1m4.  Set up, configuration, and maintenance[0m

  [1m4.1.  Disk configuration[0m

  This section describes disk partitioning strategies. Our goal is to
  keep the virtual structures of the machines organised such that they
  are all logical. We're finding that the physical mappings to the
  logical structures are not sustainable as hardware and software
  (operating system) change. Currently, our strategy is as follows:



  farm/cluster machines:

  partition 1 on system disk     - swap  (2 * RAM)
  partition 2 on system disk     - /     (remaining disk space)
  partition 1 on additional disk - /maxa (total disk)

  servers:

  partition 1 on system disk        - swap  (2 * RAM)
  partition 2 on system disk        - /     (4-8 GB)
  partition 3 on system disk        - /home (remaining disk space)
  partition 1 on additional disk 1  - /maxa (total disk)
  partition 1 on additional disk 2  - /maxb (total disk)
  partition 1 on additional disk 3  - /maxc (total disk)
  partition 1 on additional disk 4  - /maxd (total disk)
  partition 1 on additional disk 5  - /maxe (total disk)
  partition 1 on additional disk 6  - /maxf (total disk)
  partition 1 on additional disk(s) - /maxg (total disk space)

  desktops:

  partition 1 on system disk        - swap   (2 * RAM)
  partition 2 on system disk        - /      (4-8 GB)
  partition 3 on system disk        - /spare (remaining disk space)
  partition 1 on additional disk 1  - /maxa  (total disk)
  partition 1 on additional disk(s) - /maxb  (total disk space)



  Note that in the case of servers and desktops, maxg and maxb can be a
  single disk or a conglomeration of disks.

  [1m4.2.  Package configuration[0m

  Install a minimal set of packages for the farm. Users are allowed to
  configure desktops as they wish, provided the virtual structure is
  kept the same described above is kept the same.

  [1m4.3.  Operating system installation and maintenance[0m

  [1m4.3.1.  Personal cloning strategy[0m

  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 bootable 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 a script called go that takes a machine number as its argument
  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 use Martin Purschke's Custom Rescue Disk
  (http://www.phenix.bnl.gov/~purschke/RescueCD/) to create a bootable
  CD image containing the .tgz file representing the cloned system, as
  well as the go script and other associated files.  This is burned onto
  a CD-ROM.

  There are several documents that describe how to create your own
  custom bootable CD, including the Linux Bootdisk HOWTO
  (http://www.linuxdoc.org/HOWTO/Bootdisk-HOWTO/), which also contains
  links to other pre-made boot/root disks.

  Thus you have 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. In my system, I specify the IP
  address by specifying the number of the machine, but this could be
  completely automated through the use of DHCP.

  Rob Fantini (rob@fantinibakery.com) has contributed modifications of
  the scripts above that he used for cloning a Mandrake 8.2 system
  accessible at
  http://www.ram.org/computing/linux/cluster/fantini_contribution.tgz.

  [1m4.3.2.  Cloning and maintenance packages[0m

  [1m4.3.2.1.  FAI[0m

  FAI (http://www.informatik.uni-koeln.de/fai/) is an automated system
  to install a Debian GNU/Linux operating system on a PC cluster. You
  can take one or more virgin PCs, turn on the power and after a few
  minutes Linux is installed, configured and running on the whole
  cluster, without any interaction necessary.


  [1m4.3.2.2.  SystemImager[0m

  SystemImager (http://systemimager.org) is software that automates
  Linux installs, software distribution, and production deployment.

  [1m4.3.3.  DHCP vs. hard-coded IP addresses[0m

  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.

  [1m4.4.  Known hardware issues[0m

  The hardware in general has worked really well for us. Specific issues
  are listed below:

  The AMD dual 1.2 GHz machines run really hot. Two of them in a room
  increase the temperature significantly. Thus while they might be okay
  as desktops, the cooling and power consumption when using them as part
  of a large cluster is a consideration. The AMD Palmino configuration
  described previously seems to work really well, but I definitely
  recommend getting two fans in the case--this solved all our
  instability problems.

  [1m4.5.  Known software issues[0m

  Some tar executables apparently don't create a tar file the nice way
  they're supposed to (especially in terms of referencing and de-
  referencing symbolic links). The solution to this I've found is to use
  a tar executable that does, like the one from RedHat 7.0.

  [1m5.  Performing tasks on the cluster[0m

  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 technique
  that operates on a single gene/protein, each processor can work on one
  gene/protein at a time independent of all the other processors).

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

  [1m5.1.  Rough benchmarks[0m

  For the single most important program we run (our [4mab[24m [4minitio[24m protein
  folding simulation program), using the Pentium 3 1 GHz processor
  machine as a frame of reference, on average:



       Xeon    1.7 GHz processor is about 22% slower
       Athlon  1.2 GHz processor is about 36% faster
       Athlon  1.5 GHz processor is about 50% faster
       Athlon  1.7 GHz processor is about 63% faster
       Xeon    2.4 GHz processor is about 45% faster
       Xeon    2.7 GHz processor is about 80% faster
       Opteron 1.4 GHz processor is about 70% faster
       Opteron 1.6 GHz processor is about 88% faster



  Yes, the Athlon 1.5 GHz is faster than the Xeon 1.7 GHz since the Xeon
  executes only six instructions per clock (IPC) whereas the Athlon
  executes nine IPC (you do the math!). This is however an highly non-
  rigourous comparison since the executables were each compiled on the
  machines (so the quality of the math libraries for example will have
  an impact) and the supporting hardware is different.

  [1m5.2.  Uptimes[0m

  These machines are incredibly stable both in terms of hardware and
  software once they have been debugged (usually some in a new batch of
  machines have hardware problems), running constantly under very heavy
  loads.  One common example is given below. Reboots have generally
  occurred when a circuit breaker is tripped.



         2:29pm  up 495 days,  1:04,  2 users,  load average: 4.85, 7.15, 7.72



  [1m6.  Acknowledgements[0m

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


  ·  Michal Guerquin (Michal Guerquin)

  ·  Michael Levitt (Michael Levitt)

  [1m7.  Bibliography[0m

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


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

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

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



