Linux Cluster HOWTO
Ram Samudrala (me@ram.org)
v0.92, April 8, 2002
How to set up high-performance Linux computing clusters.
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.
Even today, as I plan another 64-node cluster, I find there is a
dearth of information about exactly how to assemble components to form
a node that works reliably under Linux. 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.
Hardware
This section covers the hardware choices I've made. Unless noted
in the
section, 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. For
each section, the hardware is listed in the order of purchase (most
recent is listed first).
Node hardware
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
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
Server hardware
1 server for external use (dissemination of information) 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 with 300W PS
Desktop hardware
1 desktop with the following setup:
2 Intel Xeon 1.7 GHz 256K 400FS
Supermicro P4DCE Dual Xeon motherboard
4 256mb RAMBUS 184-Pin 800 MHz memory
2 120 GB Maxtor ATA/100 5400 RPM HD
1 60 GB Maxtor ATA/100 7200 RPM HD
52X Asus CD-A520 INT IDE CDROM
1.4 MB floppy drive
Leadtex 64 MB GF2 MX400 AGP
Creative SB LIVE Value PCI 5.1
Microsoft Natural Keyboard
Microsoft Intellimouse Explorer
Supermicro SC760 full-tower case with 400W PS
2 desktops with the following setup:
2 AMD K7 1.2g/266 MP Socket A CPU
Tyan S2462NG Dual Socket A motherboard
4 256mb PC2100 REG ECC DDR-266Mhz
3 40 GB Maxtor UDMA/100 7200 RPM HD
50X Asus CD-A520 INT IDE CDROM
1.4 MB floppy drive
Chaintech Geforce2 MX200 32mg AGP
Creative SB LIVE Value PCI
Microsoft Natural Keyboard
Microsoft Intellimouse Explorer
Full-tower case with 300W PS
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 with 300W PS
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 with 300W PS
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 with 300W PS
Miscellaneous/accessory hardware
Backup:
2 Sony 20/40 GB DSS4 SE LVD DAT
Monitors:
1 22" Viewsonic P220F 0.25-0.27m monitor
4 21" Sony CPD-G500 .24mm monitor
2 18" Viewsonic VP181 LCD monitor
1 17" Viewsonic VE170 LCD monitor
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 48 port network switch.
1 Netgear FS524 24 port network switch
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-$2000, including taxes. Generally, our goal is to keep each node to
below $2000.00 (which is what our desktop machines cost).
Software
Linux, of course!
We use Linux systems with a 2.4.9-7 kernel based on the KRUD 7.2
distribution, and 2.2.17-14 kernel based on the KRUD 7.0
distribution. 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.
We use our own software for parallelising applications
but have experimented with PVM and MPI. 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).
Costs
Linux is freely copiable.
Set up and configuration
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)
Package configuration
Install a minimal set of packages for the farm. Users are allowed
to configure desktops as they wish.
Operating system installation
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.
Rob Fantini
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.
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.
Known hardware issues
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.
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 queueing
system, but obviously that is highly dependent on the type of
applications you wish to run.
Rough benchmarks
For the single most important program we run (our ab initio
protein folding simulation program), using the Pentium 3 1 GHz
processor machine as a reference frame, the Athlon 1.2 GHz processor
machine is about 16% faster on average, the Pentium 4 1.7 GHz machine
is about 25-32% faster on average, and the Athlon 1.5 GHz processor is
about 80% faster on average (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!)).
Uptimes
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). Reboots have generally occurred
when a circuit breaker is tripped. The first machine I installed has
been up since its birth!
~ ram@fp1 % uptime
4:49am up 374 days, 2:47, 1 user, load average: 2.08, 2.02, 2.01
Acknowledgements
The following people have been helpful in getting this HOWTO
done:
Michael Levitt (Michael Levitt)
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
RAMP web page
Ram Samudrala's research page (which describes the kind of research done with these clusters)