-
-What is IP ? IP is short for
-
-What is IP ? IP is short for
+
+What is IP ? IP is short for
+Here is the list of Free CPUs available or curently under development -
+
+
+
+
+
+
+
+This chapter gives very basics of CPU technology.
+If you have good technical background then you can skip this entire chapter.
+
+
+CPU Museum is at
+
+ Microprocessors are essential to many of the products we use every day such as TVs, cars, radios, home appliances and of course, computers. Transistors are the main components of microprocessors.
+ At their most basic level, transistors may seem simple. But their development actually required many years of painstaking research. Before transistors, computers relied on slow, inefficient vacuum tubes and mechanical switches to process information. In 1958, engineers (one of them Intel founder Robert Noyce) managed to put two transistors onto a silicon crystal and create the first integrated circuit that led to the microprocessor.
+
+ Transistors are miniature electronic switches. They are the building blocks of the microprocessor which is the brain of the computer.
+ Similar to a basic light switch, transistors have two operating positions, on and off. This on/off, or binary functionality of transistors enables the processing of information in a computer.
+
+
+ The only information computers understand are electrical signals that are switched on and off. To comprehend transistors, it is necessary to have an understanding of how a switched electronic circuit works.
+ Switched electronic circuits consist of several parts. One is the circuit pathway where the electrical current flows - typically through a wire. Another is the switch, a device that starts and stops the flow of electrical current by either completing or breaking the circuit's pathway.
+ Transistors have no moving parts and are turned on and off by electrical signals. The on/off switching of transistors facilitates the work performed by microprocessors.
+
+
+ Something that has only two states, like a transistor, can be referred to as binary. The transistor's on state is represented by a 1 and the off state is represented by a 0. Specific sequences and patterns of 1's and 0's generated by multiple transistors can represent letters, numbers, colors and graphics. This is known as binary notation
+
+
+
+ Each character of the alphabet has a binary equivalent. Below is the name JOHN and its equivalent in binary.
+
+Conductors and insulators :
+
+ Many materials, such as most metals, allow electrical current to flow through them. These are known as conductors. Materials that do not allow electrical current to flow through them are called insulators. Pure silicon, the base material of most transistors, is considered a semiconductor because its conductivity can be modulated by the introduction of impurities.
+
+
+Semiconductors and flow of electricity
+
+ Adding certain types of impurities to the silicon in a transistor changes its crystalline structure and enhances its ability to conduct electricity. Silicon containing boron impurities is called p-type silicon - p for positive or lacking electrons. Silicon containing phosphorus impurities is called n-type silicon - n for negative or having a majority of free electrons
+
+
+A Working transistor - The On/Off state of Transistor
+
+ Transistors consist of three terminals; the source, the gate and the drain.
+
+ In the n-type transistor, both the source and the drain are negatively-charged and sit on a positively-charged well of p-silicon.
+
+ When positive voltage is applied to the gate, electrons in the p-silicon are attracted to the area under the gate forming an electron channel between the source and the drain.
+
+ When positive voltage is applied to the drain, the electrons are pulled from the source to the drain. In this state the transistor is on.
+
+ If the voltage at the gate is removed, electrons aren't attracted to the area between the source and drain. The pathway is broken and the transistor is turned off.
+
+
+The Impact of Transistors - How microprocessors affect our lives.
+
+ The binary function of transistors gives micro- processors the ability to perform many tasks; from simple word processing to video editing. Micro- processors have evolved to a point where transistors can execute hundreds of millions of instructions per second on a single chip.
+ Automobiles, medical devices, televisions, computers and even the Space Shuttle use microprocessors. They all rely on the flow of binary information made possible by the transistor.
+
+
+
+
+Visit the following links for information on CPU Design.
+
+
+
+
+
+
+Visit the following links for information on CPU architecture
+
+
+After doing the design and testing of CPU, your company may want to mass produce
+the CPUs. There are many "semi-conductor foundries" in the world who will do
+that for you for a nominal competetive cost. There are companies in USA,
+Germany, UK, Japan, Taiwan, Korea and China.
+
+TMSC (Taiwan) is the
+Foundry companies invested very heavily in the infra-structure
+and building plants runs in several millions of dollars!
+Silicon foundry business will grow from $7 billion to $36
+billion by 2004 (414% increase!!).
+More integrated device manufacturers (IDMs) opt to outsource
+chip production verses adding wafer-processing capacity.
+
+Independent foundries currently produce about 12% of the semiconductors
+in the world, and by 2004, that share will more than double to 26%.
+
+The "Big Three" pure-play foundries in the whole world are:
+
+There are hundreds of foundries in the world (too numerous to list). Some of them are -
+
+For building Super computers, the trend that seems to emerge is
+that most new systems look as minor
+variations on the same theme: clusters of RISC-based Symmetric
+Multi-Processing (SMP) nodes which in turn are connected by a fast
+network. Consider this as a natural architectural evolution.
+The availability of relatively low-cost (RISC) processors and
+network products to connect these processors together with
+standardised communication software has stimulated the building
+of home-brew clusters computers as an alternative to complete
+systems offered by vendors.
+
+Visit the following sites for Super Computers -
+
+Before going on to the descriptions of the machines themselves, it is
+important to consider some mechanisms that are or have been used to
+increase the performance. The hardware structure or architecture
+determines to a large extent what the possibilities and impossibilities
+are in speeding up a computer system beyond the performance of a single
+CPU. Another important factor that is considered in combination with
+the hardware is the capability of compilers to generate efficient code
+to be executed on the given hardware platform. In many cases it is hard
+to distinguish between hardware and software influences and one has to be
+careful in the interpretation of results when ascribing certain effects
+to hardware or software peculiarities or both. In this chapter we will
+give most emphasis to the hardware architecture. For a description of
+machines that can be considered to be classified as "high-performance".
+
+Since many years the taxonomy of Flynn has proven to be useful for
+the classification of high-performance computers. This classification
+is based on the way of manipulating of instruction and data streams and
+comprises four main architectural classes. We will first briefly sketch
+these classes and afterwards fill in some details when each of the
+classes is described.
+
+
+These are the conventional systems that contain one CPU
+and hence can accommodate one instruction stream that is executed serially.
+Nowadays many large mainframes may have more than one CPU but each of
+these execute instruction streams that are unrelated. Therefore, such
+systems still should be regarded as (a couple of) SISD machines acting
+on different data spaces. Examples of SISD machines are for instance
+most workstations like those of DEC, Hewlett-Packard, and Sun
+Microsystems. The definition of SISD machines is given here for
+completeness' sake. We will not discuss this type of machines
+in this report.
+
+
+Such systems often have a large number of processing
+units, ranging from 1,024 to 16,384 that all may execute the same
+instruction on different data in lock-step. So, a single instruction
+manipulates many data items in parallel. Examples of SIMD machines
+in this class are the CPP DAP Gamma II and the Alenia Quadrics.
+
+Another subclass of the SIMD systems are the vectorprocessors.
+Vectorprocessors act on arrays of similar data rather than on single
+data items using specially structured CPUs. When data can be manipulated
+by these vector units, results can be delivered with a rate of one,
+two and --- in special cases --- of three per clock cycle (a clock
+cycle being defined as the basic internal unit of time for the system).
+So, vector processors execute on their data in an almost parallel way
+but only when executing in vector mode. In this case they are several
+times faster than when executing in conventional scalar mode. For
+practical purposes vectorprocessors are therefore mostly regarded
+as SIMD machines. Examples of such systems is for instance
+the Hitachi S3600.
+
+
+Theoretically in these type of machines multiple
+instructions should act on a single stream of data. As yet no
+practical machine in this class has been constructed nor are
+such systems easily to conceive. We will disregard them in the
+following discussions.
+
+
+These machines execute several instruction
+streams in parallel on different data. The difference with the
+multi-processor SISD machines mentioned above lies in the fact that
+the instructions and data are related because they represent different
+parts of the same task to be executed. So, MIMD systems may run
+many sub-tasks in parallel in order to shorten the time-to-solution
+for the main task to be executed. There is a large variety of
+MIMD systems and especially in this class the Flynn taxonomy proves
+to be not fully adequate for the classification of systems. Systems
+that behave very differently like a four-processor NEC SX-5 and a
+thousand processor SGI/Cray T3E fall both in this class. In the
+following we will make another important distinction between classes
+of systems and treat them accordingly.
+
+
+Shared memory systems have multiple CPUs all
+of which share the same address space. This means that the knowledge
+of where data is stored is of no concern to the user as there is only
+one memory accessed by all CPUs on an equal basis. Shared memory
+systems can be both SIMD or MIMD. Single-CPU vector processors can be
+regarded as an example of the former, while the multi-CPU models of
+these machines are examples of the latter. We will sometimes use the
+abbreviations SM-SIMD and SM-MIMD for the two subclasses.
+
+
+In this case each CPU has its own
+associated memory. The CPUs are connected by some network and may
+exchange data between their respective memories when required. In
+contrast to shared memory machines the user must be aware of the
+location of the data in the local memories and will have to move
+or distribute these data explicitly when needed. Again, distributed
+memory systems may be either SIMD or MIMD. The first class of
+SIMD systems mentioned which operate in lock step, all have distributed
+memories associated to the processors. As we will see,
+distributed-memory MIMD systems exhibit a large variety in the
+topology of their connecting network. The details of this topology
+are largely hidden from the user which is quite helpful with
+respect to portability of applications. For the distributed-memory
+systems we will sometimes use DM-SIMD and DM-MIMD to indicate
+the two subclasses.
+Although the difference between shared- and distributed memory
+machines seems clear cut, this is not always entirely the case
+from user's point of view. For instance, the late Kendall
+Square Research systems employed the idea of "virtual shared memory"
+on a hardware level. Virtual shared memory can also be simulated
+at the programming level: A specification of High Performance
+Fortran (HPF) was published in 1993 which by means of
+compiler directives distributes the data over the
+available processors. Therefore, the system on which HPF is
+implemented in this case will look like a shared memory machine
+to the user. Other vendors of Massively Parallel Processing
+systems (sometimes called MPP systems), like HP
+and SGI/Cray,
+also are able to support proprietary virtual shared-memory programming models due to
+the fact that these physically distributed memory systems are able to address
+the whole collective address space. So, for
+the user such systems have one global address space spanning all of
+the memory in
+the system. We will say a little more about
+the structure of such systems in
+the ccNUMA section. In addition, packages like TreadMarks
+provide a virtual shared memory environment for networks of workstations.
+
+
+Another trend that has came up in
+the last few years is distributed processing. This takes
+the DM-MIMD concept one step further: instead
+of many integrated processors in one or several boxes,
+workstations, mainframes, etc., are connected by (Gigabit) Ethernet, FDDI, or otherwise
+and set to work concurrently on tasks in
+the same program. Conceptually, this is not different from DM-MIMD computing, but
+the communication between processors is often orders
+of magnitude slower. Many packages to realise distributed
+computing are available. Examples of
+these are PVM (st
+anding for Parallel Virtual Machine),
+and MPI (Message Passing Interface). This style
+of programming, called
+the "message passing" model has becomes so much accepted that PVM
+and MPI have been adopted by virtually all major vendors
+of distributed-memory MIMD systems
+and even on shared-memory MIMD systems for compatibility reasons. In addition
+there is a tendency to cluster shared-memory systems,
+for instance by HiPPI channels, to obtain systems
+with a very high computational power. E.g.,
+the NEC SX-5,
+and
+the SGI/Cray SV1 have this structure. So, within
+the clustered nodes a shared-memory programming style can be
+used while between clusters message-passing should be used.
+
+
+As already mentioned in the introduction, a trend can be
+observed to build systems that have a rather small (up to 16)
+number of RISC processors that are tightly integrated in
+a cluster, a Symmetric Multi-Processing (SMP) node. The
+processors in such a node are virtually always connected
+by a 1-stage crossbar while these clusters are connected by a
+less costly network.
+
+This is similar to the policy mentioned for large
+vectorprocessor ensembles mentioned above but with the important
+difference that all of the processors can access all of the
+address space. Therefore, such systems can be considered as
+SM-MIMD machines. On the other hand, because the memory is
+physically distributed, it cannot be guaranteed that a
+data access operation always will be satisfied within the same
+time. Therefore such machines are called ccNUMA
+systems where ccNUMA stands for Cache Coherent Non-Uniform Memory
+Access. The term "Cache Coherent" refers
+to the fact that for all CPUs any variable that is to be used
+must have a consistent value. Therefore, is must be assured
+that the caches that provide these variables are also consistent
+in this respect. There are various ways to ensure that the
+caches of the CPUs are coherent. One is the snoopy bus
+protocol in which the caches listen in on transport of variables to
+any of the CPUs and update their own copies of these
+variables if they have them. Another way is the directory memory,
+a special part of memory which enables to keep track of the all
+copies of variables and of their validness.
+
+For all practical purposes we can classify these systems as
+being SM-MIMD machines also because special assisting
+hardware/software (such as a directory memory) has been
+incorporated to establish a single system image although
+the memory is physically distributed.
+
+
+
+
+
+Supercomputers traditionally have been expensive, highly customized designs purchased by a select group of customers, but the industry is being overhauled by comparatively mainstream technologies such as Intel processors,
+
+Imagine your garage filled with dozens of computers all linked together in a super-powerful Linux cluster. You still have to supply your own hardware, but the geek equivalent of a Mustang GT will become easier to set up and maintain, thanks to new software to be demonstrated at LinuxWorld next week.
+
+The Open Source Cluster Applications Resources (OSCAR) software, being developed by the
+
+NNs are models of biological neural networks and some are not, but
+historically, much of the inspiration for the field of
+NNs came from the desire to produce artificial systems capable
+of sophisticated, perhaps "intelligent", computations similar to
+those that the human brain routinely performs, and thereby
+possibly to enhance our understanding of the human brain.
+
+Most NNs have some sort of "training" rule whereby the weights
+of connections are adjusted on the basis of data. In other
+words, NNs "learn" from examples (as children learn to
+recognize dogs from examples of dogs) and exhibit some capability for
+generalization beyond the training data.
+
+NNs normally have great potential for parallelism, since the computations
+of the components are largely independent of each
+other. Some people regard massive parallelism and high connectivity to
+be defining characteristics of NNs, but such
+requirements rule out various simple models, such as simple
+linear regression (a minimal feedforward net with only two units
+plus bias), which are usefully regarded as special cases of NNs.
+
+Some definitions of Neural Network (NN) are as follows:
+
+Visit following locators which are related -
+
+This document is published in 14 different formats namely - DVI, Postscript,
+Latex, Adobe Acrobat PDF,
+LyX, GNU-info, HTML, RTF(Rich Text Format), Plain-text, Unix man pages, single
+HTML file, SGML (Linuxdoc format), SGML (Docbook format), MS WinHelp format.
+
+This howto document is located at -
+
+
+ Single HTML file can be created with command (see man sgml2html) -
+sgml2html -split 0 xxxxhowto.sgml
+
+
+PDF file can be generated from postscript file using
+either acrobat
+This document is written in linuxdoc SGML format. The Docbook SGML format
+supercedes the linuxdoc format and has lot more features than linuxdoc.
+The linuxdoc is very simple and is easy to use. To convert linuxdoc SGML
+file to Docbook SGML use the program
+You can convert the SGML howto document to Microsoft Windows Help file,
+first convert the sgml to html using:
+
+In order to view the document in dvi format, use the xdvi program. The xdvi
+program is located in tetex-xdvi*.rpm package in Redhat Linux which can be
+located through ControlPanel | Applications | Publishing | TeX menu buttons.
+ To read dvi document give the command -
+
+Copyright policy is GNU/GPL as per LDP (Linux Documentation project).
+LDP is a GNU/GPL project.
+Additional restrictions are - you must retain the author's name, email address
+and this copyright notice on all the copies. If you make any changes
+or additions to this document then you should
+intimate all the authors of this document.
+
+
+ J 0100 1010
+ O 0100 1111
+ H 0100 1000
+ N 0100 1110
+
+ More complex information can be created such as graphics, audio and video using the binary, or on/off action of transistors.
+
+ Scroll down to the Binary Chart below to see the complete alphabet in binary.
+
+
+
+
+
+
+*Copy PCQLinux RPMs to /tftpboot/rpm
+*For creating the image, OSCAR will look for the PCQLinux RPMs in the
+directory /tftpboot/rpm. Create a directory /tftpboot and a subdirectory
+named rpm within it
+
+mkdir /tftpboot
+mkdir /tftpboot/rpm
+
+Next, copy all the PCQLinux RPMs from both the CDs to /tftpboot/rpm
+directory. Insert CD 1 (PCQLinux CD 1, given with our July 2001 issue)
+and issue the following commands:
+
+mount /mnt/cdrom
+cd /mnt/cdrom/RedHat/RPMS
+cp *.rpm /tftpboot/ rpm
+cd
+umount /mnt/cdrom
+
+Insert CD 2 (given with the July 2001 issue) and issue the above
+commands again.
+
+Note. If you are tight at the disk space, you don't need to copy all the
+RPMs to /tftpboot/rpm. You can copy only the RPMs listed in
+sample.rpmlist file. Copy only the required RPMs.
+
+*Copy required RPMs
+*Type the following in a Linux text editor and save the file as copyrpms.sh
+
+#!/bin/bash
+rpms_path="/mnt/cdrom/RedHat/RPMS/"
+rpms_list="/root/oscar-1.2.1/oscarsamples/sample.rpmlist"
+mount /mnt/cdrom
+while read line
+do file="$rpms_path$line.i386.rpm"
+if [ -f $file ]
+then
+cp $file /tftpboot/rpm
+else file="$rpms_path$line.noarch.rpm"
+if [ -f $file ]
+then
+cp $file /tftpboot/rpm
+else file="$rpms_path$line.i586.rpm"
+if [ -f $file ]
+then
+cp $file /tftpboot/rpm
+else file="$rpms_path$line.i686.rpm"
+if [ -f $file ]
+then
+cp $file /tftpboot/rpm
+fi
+fi
+fi
+fi
+done < $rpms_list
+eject
+
+Give executable permissions to the file as:
+
+chmod +x copyrpms.sh
+
+Assuming that you have created the directory /tftpboot/rpm, insert
+PCQLinux CD 1 (don't mount it) and issue:
+./copyrpms
+
+When all the RPMs from the CD are copied, the CD drive will eject. Next,
+insert CD 2 and issue ./copyrpms again.
+
+*Fix glitch in PCQLinux
+*On this month's CD we have carried the zlib
+rpm 'zlib-1.1.3-22.i386.rpm' which you can find in the directory
+system/cdrom/ unltdlinux/linux on the CD. (We had given this on our July
+CD as well, but the file was corrupt.) Install the RPM as:
+
+rpm -ivh zlib-1.1.3-22.i386.rpm
+
+Copy this file to /tftpboot/rpm directory. This will prompt you to
+overwrite the corrupted zlib RPM, already in the directory. Go for it.
+
+*Set up networking
+*Linux names network cards or interfaces as eth0, eth1, eth2. In our
+case eth0 is the internal interface and eth1 is the external interface.
+We assign eth0, an IP address of 172.16.0.1. Since we are running a DHCP
+server on the PCQ Labs network, we will set eth1 to obtain IP address
+from the DHCP server. If you are using a single network card for the
+cluster network, skip setting up the second card.
+
+Launch X Window. Launch a terminal window within GNOME or KDE and issue
+the command netcfg. This will pop up a graphical network configurator.
+Click on the Interfaces tab. To set up the internal interface, click on
+eth0 and then on edit. For IP address, enter 172.16.0.1 and for the
+netmask enter 255.255.255.0. Click on 'Activate interface at boot time'.
+For 'Interface configuration protocol' select 'none' from the drop-down
+list.
+
+To set up the external interface, select eth1 and click on edit. If you
+are running a DHCP server, select dhcp from the drop down list. Else,
+enter a free IP address (say, 192.168.1.23), the associated netmask
+(say, 255.255.255.0) and select none from the drop-down list. In either
+case, make sure to click on 'Activate interface at boot time'.
+
+Highlight eth0 and click on the button 'Activate'. Do the same for eth1.
+Finally, click on save and quit the configurator.
+
+Issue the command, ifconfig to check whether the network interfaces are
+up and have been given the correct IP addresses.
+You are now ready to start Oscar.
+
+*Run OSCAR
+*In the terminal window, change to oscar-1.2.2 directory and issue the
+command:
+
+./install_cluster eth0
+
+Replace eth0 with the name of the internal interface in your case. You
+will see text flowing in the window. After a couple of minutes, the
+graphical wizard of OSCAR will pop up. OSCAR installation calls cluster
+nodes as clients
+
+*Build image from RPMs
+*Click on 'Build Oscar Client Image'. We assume that all the node
+machines will have IDE hard disks. If you are using SCSI hard disk in
+the nodes, you need to change the Disk Partition File. Refer to the
+OSCAR installation documentation on the CD. When finished, a message
+'Successfully created image oscarimage' will pop up.
+
+*Tell OSCAR about the nodes
+*Click on the button 'Define OSCAR clients'. Here you should see the
+domain name, starting IP and subnet mast, pre-filled with cluster.net,
+172.16.0.2 and 255.255. 255.0. With 'Number of hosts' you specify the
+number of nodes. As per the OSCAR documentation, OSCAR supports up to
+100 nodes or may be more. But it hasn't been experimented with arbitrary
+large number of nodes. In our case we fill in two. If you are
+experimenting with two machines, one server and the other the node, then
+fill in one.
+
+In OSCAR once you define the number of nodes you cannot change it after
+the cluster is installed. You need to again start from the beginning,
+ie, from the step when we issued 'install_cluster'
+
+Note. If for any reason you need to start again, before issuing
+./install_cluster, execute the script named start_over located in the
+subdirectory scripts as:
+
+/root/oscar-1.2.1/script/start_over'
+
+Clicking on the 'Add clients' button will show 'Successfully created
+clients' after a couple of seconds.
+
+*Set up the nodes *
+Before carrying out the subsequent steps in OSCAR installation, connect
+the network cards of the node machines to the switch and set them up to
+boot from floppy from their BIOS.
+
+*Set up nodes to network
+*We come back to OSCAR installation wizard running on the server
+machine. Click on the button 'Set up Networking'. In the right frame you
+will see a tree-like structure as shown in the screenshot. In our case,
+the two nodes are given a hostname of oscarnode1.cluster.net and
+oscarnode2. cluster.net. They are assigned IP addresses 172.16.0.2 and
+172.16. 0.3 respectively. Next, we assign the MAC (Media Access Control)
+address of the nodes to the listed IP addresses. This can be done by
+booting the nodes using a floppy created by OSCAR or by networking
+booting them. For the latter refer to the OSCAR documentation given on
+the CD.
+
+Click on the button 'Build AutoInstall Floppy'. This will pop up a
+terminal window. Insert a blank floppy in the server and click 'y' to
+continue. After the terminal window disappears, click on the button
+'Collect MAC addresses' in the OSCAR window. Insert the floppy in one of
+the node machines and power it on. The machine will boot from the
+floppy. Press enter at the boot: prompt. After some time, the MAC
+address of the node will show up in the left frame. Suppose we want to
+assign the IP address 172.16.0.1 to this node. Click on the MAC address
+in the left and on the 'osacrnde1.cluster.net' in the right frame. Then,
+click on 'Assign MAC to node'.
+
+*Assign IP addresses to the nodes of the cluster
+*Switch off the node machine. Now boot the second node machine from the
+same floppy. As before, the MAC address of the second node will appear
+in the left frame. Assign it to oscarnode2. cluster.net.
+
+If you want to plug in more node machines, repeat the above process for
+them. When done, click on the button 'Stop collecting' on the OSCAR window.
+
+After shutting down all the node machines, click on the button
+'Configure DHCP Server'. Then click on the close button in the 'MAC
+address collection' window.
+
+*PCQLinux on the nodes
+*Next, boot the first node machine again from the floppy. This time the
+node machine will install PCQLinux 7.1 from the network. When done, a
+message, as following, will be shown:
+
+I have done for ' seconds. Reboot me already
+
+Take out the floppy and reboot the node machine. This time it should
+boot from the hard disk. If everything has gone well, you will boot into
+PCOLinux 7.1. While booting, PCQLinux will detect and prompt you to set
+up hardware like mouse, graphics card, sound card etc on the nodes.
+
+*Problem: No active partition
+*If you are shown an error during booting which says no active
+partition, then boot from a Windows bootable floppy or CD. Launch fdisk
+and select option2 (Set active partition). Set partition 1 of type
+non-dos and about 31 MB in size as active. This is the /boot partition
+from where the kernel boot image resides.
+
+*Test networking of nodes
+*On the server, open another terminal window and issue:
+
+/root/oscar-1.2.2/scripts/ping_clients
+
+If there is no problem with the networking, you will be shown 'All
+clients responded'. Else check whether all nodes are powered on, defects
+in network cables, hub/ switch ports etc. From now on, ideally, you
+don't need to work physically on the node machines. Hence you can plug
+off the monitor, keyboard, mouse, etc from the node machines. If the
+node machines need to be accessed and worked upon, you should use SSH
+(Secure Shell), similar to telnet but secure, to access them from the
+server.
+
+*All done
+*Click on 'Complete Cluster Setup' and then on 'Test cluster Setup'.
+This will pop up a terminal window and prompt you to enter a non-root
+username. Enter 'shekhar' (say). If the user account does not exist on
+the server machine, it will be created. In the latter case, you will be
+prompted for a password for the new account. Click on the 'Quit' button
+on the OSCAR window. Reboot the server machine.
+
+*Test the cluster
+*To test the cluster, log in as the user that you created above (shekhar
+in our case) and issue:
+
+cd OSCAR_test
+./text_cluster
+
+Enter the number of nodes when prompted (two in our case). For the
+number of processors on each client enter 1 (assuming uniprocessor
+machines). The test verifies the running of PBS and runs example
+programs coded using LAM, MPICH, PVM libraries by dispatching them
+through PBS to the nodes. You can see pbs_mom (see Understanding
+Clustering, page 42) running on the nodes by issuing the command 'ps 'e
+| grep pbs_mom' on the nodes.
+
+If there are no error messages in the output, congratulations, you have
+your supercomputer up and running. Our cluster setup qualifies to be
+called a Beowulf cluster because it has been built using easily
+available hardware, free and open-source software, the /home directory
+on the server is exported to all the nodes via NFS (you can check this
+by issuing the command 'mount' on the nodes), and finally the server and
+nodes can execute command and scripts remotely on each other via SSH.
+Using the libraries installed on the cluster, you can start developing
+or executing cluster-aware applications on the server. The compilers for
+them (like, gcc, g++) are same as with PCQLinux.
+
+Shekhar Govindarajan
+
+
+
+
+
+bash$ man sgml2latex
+bash$ sgml2latex filename.sgml
+bash$ man dvips
+bash$ dvips -o filename.ps filename.dvi
+bash$ distill filename.ps
+bash$ man ghostscript
+bash$ man ps2pdf
+bash$ ps2pdf input.ps output.pdf
+bash$ acroread output.pdf &
+
+Or you can use Ghostscript command
+ bash$ ld2db.sh file-linuxdoc.sgml db.sgml
+ bash$ cleanup.pl db.sgml > db_clean.sgml
+ bash$ gvim db_clean.sgml
+ bash$ docbook2html db.sgml
+
+And you may have to manually edit some of the minor errors after
+running the perl script. For e.g. you may need to put closing tag <
+/Para> for each <
+Listitem>
+
+
+ bash$ sgml2html xxxxhowto.sgml (to generate html file)
+ bash$ sgml2html -split 0 xxxxhowto.sgml (to generate a single page html file)
+
+Then use the tool