CPU Design HOW-TO
Al Dev (Alavoor Vasudevan) alavoor@yahoo.com
v9.0, 08 Jan 2001
CPU is the "brain" of computer and is a very vital component of com�
puter system and is like a "cousin brother" of operating system (Linux
or Unix). This document helps companies, businesses, universities and
research institutes to design, build and manufacture CPUs. Also the
information will be useful for university students of U.S.A and Canada
who are studying computer science/engineering. The document has URL
links which helps students understand how a CPU is designed and manu�
factured. Perhaps in near future there will GNU/GPLed CPU running
Linux, Unix, Microsoft Windows, Apple Mac and BeOS operating systems!!
______________________________________________________________________
Table of Contents
1. Introduction
2. What is IP ?
2.1 Free CPU List
2.2 Commercial CPU List
3. CPU Museum and Silicon Zoo
3.1 How Transistors work
3.2 How a Transistors handles information
3.3 Displaying binary information
3.4 What is a Semi-conductor?
3.4.1 Anatomy of Transistor
3.4.2 A Working Transistor
3.4.3 Impact of Transistors
4. CPU Design and Architecture
4.1 CPU Design
4.2 Online Textbooks on CPU Architecture
4.3 University Lecture notes on CPU Architecture
4.4 CPU Architecture
4.5 Usenet Newsgroups for CPU design
5. Fabrication, Manufacturing CPUs
5.1 Foundry Business is in Billions of dollars!!
5.2 Fabrication of CPU
6. Super Computer Architecture
6.1 Main Architectural Classes
6.2 SISD machines
6.3 SIMD machines
6.4 MISD machines
6.5 MIMD machines
6.5.1 Shared memory systems
6.5.2 Distributed memory systems
6.6 Distributed Processing Systems
6.7 ccNUMA machines
7. Neural Network Processors
8. Related URLs
9. Other Formats of this Document
10. Copyright
______________________________________________________________________
1. Introduction
This document provides you comprehensive list of URLs for CPU Design
and fabrication. Using this information students, companies,
universities or businesses can make new CPUs which can run Linux/Unix
operating systems.
In olden days, chip vendors were also the IP developers and the EDA
tools developers. Nowadays, we have specialized fab companies (TSMC
<http://www.tsmc.com>), IP companies (ARM <http://www.arm.com>, MIPS
<http://www.mips.com>, Gray Research LLC
<http://cnets.sourceforge.net/grllc.html> ), and tools companies (
Mentor <http://www.mentor.com>, Cadence <http://www.cadence.com>,
etc.), and combinations of these (Intel). You can buy IP bundled with
hardware (Intel), bundled with your tools (EDA companies), or
separately (IP providers).
Enter the FPGA vendors (Xilinx <http://www.xilinx.com>, Altera
<http://www.altera.com>). They have an opportunity to seize upon a
unique business model.
VA Linux systems <http://www.valinux.com> builds the entire system
and perhaps in future will design and build CPUs for Linux.
Visit the following CPU design sites:
� FPGA CPU Links <http://www.fpgacpu.org/links.html>
� FPGA Main site <http://www.fpgacpu.org>
� OpenRISC 1000 Free Open-source 32-bit RISC processor IP core
competing with proprietary ARM and MIPS is at
<http://www.opencores.org>
� Open IP org <http://www.openip.org>
� Free IP org - ASIC and FPGA cores for masses <http://www.free-
ip.com>
2. What is IP ?
What is IP ? IP is short for Intellectual Property. More specifically,
it is a block of logic that can be used in making ASIC's and FPGA's.
Examples of "IP Cores" are, UART's, CPU's, Ethernet Controllers, PCI
Interfaces, etc. In the past, quality cores of this nature could cost
anywhere from US$5,000 to more than US$350,000. This is way too high
for the average company or individual to even contemplate using --
Hence, the Free-IP project.
Initially the Free-IP project will focus on the more complex cores,
like CPU's and Ethernet controllers. Less complex cores might follow.
The Free-IP project is an effort to make quality IP available to
anyone.
Visit the following sites for IP cores -
� Open IP org <http://www.openip.org>
� Free IP org - ASIC and FPGA cores for masses <http://www.free-
ip.com>
� FPGA Main site <http://www.fpgacpu.org>
2.1. Free CPU List
Here is the list of Free CPUs available or curently under development
-
� F-CPU 64-bit Freedom CPU <http://www.f-cpu.org> mirror site at
<http://www.f-cpu.de>
� European Space Agency - SPARC architecture LEON CPU
<http://www.estec.esa.nl/wsmwww/leon>
� European Space Agency - ERC32 SPARC V7 CPU
<http://www.estec.esa.nl/wsmwww/erc32>
� Atmel ERC32 SPARC part # TSC695E <http://www.atmel-
wm.com/products> click on Aerospace=>Space=>Processors
� Sayuri at
<http://www.morphyplanning.co.jp/Products/FreeCPU/freecpu-e.html>
and manufactured by Morphy Planning Ltd at
<http://www.morphyone.org> and feature list at
<http://ds.dial.pipex.com/town/plaza/aj93/waggy/hp/features/morphyone.htm>
and in Japanese language at <http://www.morphyplanning.or.jp>
� OpenRISC 1000 Free 32-bit processor IP core competing with
proprietary ARM and MIPS is at
<http://www.opencores.org/cores/or1k>
� OpenRISC 2000 is at <http://www.opencores.org>
� Green Mountain - GM HC11 CPU Core is at
<http://www.gmvhdl.com/hc11core.html>
2.2. Commercial CPU List
� ARC CPUs : <http://www.arccores.com>
� QED RISC 64-bit and MIPS cpus : <http://www.qedinc.com/about.htm>
� Origin 2000 CPU -
<http://techpubs.sgi.com/library/manuals/3000/007-3511-001/html/O2000Tuning.1.html>
� Hitachi SH4,3,2,1 CPUs <http://semiconductor.hitachi.com/superh>
� NVAX CPUs <http://www.digital.com/info/DTJ700>
� Univ. of Mich High-perf. GaAs Microprocessor Project
<http://www.eecs.umich.edu/UMichMP>
� Hyperstone E1-32 RISC/DSP processor
<http://bwrc.eecs.berkeley.edu/CIC/tech/hyperstone>
� PSC1000 32-bit RISC processor
<http://www.ptsc.com/psc1000/index.html>
� IDT R/RV4640 and R/RV4650 64-bit CPU w/DSP Capability
<http://www.idt.com/products/pages/Processors-
PL100_Sub205_Dev128.html>
� CPU Info center - List of CPUs sparc, arm etc..
<http://bwrc.eecs.berkeley.edu/CIC/tech>
3. CPU Museum and Silicon Zoo
CPU Museum is at
� Intel CPU Museum <http://www.intel.com/intel/intelis/museum>
� Intel - History of Microprocessors
<http://www.intel.com/intel/museum/25anniv>
� Virtual Museum of Computing
<http://www.museums.reading.ac.uk/vmoc>
� Silicon Zoo <http://micro.magnet.fsu.edu/creatures/index.html>
� Intel - How the Microprocessors work
<http://www.intel.com/education/mpuworks>
� Simple course in Microprocessors
<http://www.hkrmicro.com/course/micro.html>
3.1. How Transistors work
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.
How a simple electronic switch works:
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.
3.2. How a Transistors handles information
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
3.3. Displaying binary information
Spell your name in Binary:
Each character of the alphabet has a binary equivalent. Below is the
name JOHN and its equivalent in binary.
______________________________________________________________________
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.
Character Binary Character
______________________________________________________
A 0100 0001 N
B 0100 0010 O
C 0100 0011 P
D 0100 0100 Q
E 0100 0101 R
F 0100 0110 S
G 0100 0111 T
H 0100 1000 U
I 0100 1001 V
J 0100 1010 W
K 0100 1011 X
L 0100 1100 Y
M 0100 1101 Z
Binary Chart for Alphabets
3.4. What is a Semi-conductor?
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.
3.4.1. Anatomy of Transistor
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
3.4.2. A Working Transistor
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.
3.4.3. Impact of Transistors
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.
4. CPU Design and Architecture
4.1. CPU Design
Visit the following links for information on CPU Design.
� Hamburg University VHDL archive <http://tech-www.informatik.uni-
hamburg.de/vhdl>
� Kachina Design tools <http://SAL.KachinaTech.COM/Z/1/index.shtml>
� List of FPGA-based Computing Machines
<http://www.io.com/~guccione/HW_list.html>
� SPARC International <http://www.sparc.com>
� Design your own processor <http://www.spacetimepro.com>
� Teaching Computer Design with FPGAs <http://www.fpgacpu.org>
� Technical Committee on Computer Architecture
<http://www.computer.org/tab/tcca>
� Frequently Asked Questions FAQ on VHDL
<http://www.vhdl.org/vi/comp.lang.vhdl> or it is at
<http://www.vhdl.org/comp.lang.vhdl>
� Comp arch FAQ <http://www.esacademy.com/automation/faq.htm>
� Comp arch FAQ <ftp://rtfm.mit.edu/pub/usenet-by-
hierarchy/comp/arch>
� VME Bus FAQ <http://www.hitex.com/automation/FAQ/vmefaq>
� Homepage of SPEC
<http://performance.netlib.org/performance/html/spec.html>
� Linux benchmarks <http://www.silkroad.com/linux-bm.html>
4.2. Online Textbooks on CPU Architecture
� Online HTML book
<http://odin.ee.uwa.edu.au/~morris/CA406/CA_ToC.html>
� Univ of Texas Comp arch :
<http://www.cs.panam.edu/~meng/Course/CS4335/Notes/master/master.html>
� Number systems and Logic circuits :
<http://www.tpub.com/neets/book13/index.htm>
� Digital Logic: <http://www.play-hookey.com/digital>
� FlipFlops:
<http://www.ece.utexas.edu/~cjackson/FlipFlops/web_pages/Publish/FlipFlops.html>
� Instruction Execution cycle: <http://cq-
pan.cqu.edu.au/students/timp1/exec.html>
� Truth Table constructor:
<http://pirate.shu.edu/~borowsbr/Truth/Truth.html>
� Overview of Shared Memory:
<http://www.sics.se/cna/mp_overview.html>
� Simulaneous Multi-threading in processors :
<http://www.cs.washington.edu/research/smt>
� Study Web : <http://www.studyweb.com/links/277.html>
� Univ notes:
<http://www.ece.msstate.edu/~linder/Courses/EE4713/notes>
� Advice: An Adaptable and Extensible Distributed Virtual Memory
Architecture <http://www.gsyc.inf.uc3m.es/~nemo/export/adv-
pdcs96/adv-pdcs96.html>
� Univ of Utah Avalanche Scalable Parallel Processor Project
<http://www.cs.utah.edu/avalanche/avalanche-publications.html>
� Distributed computing :
<http://www.geocities.com/SiliconValley/Vista/4015/pdcindex.html>
� Pisma Memory architecture:
<http://aiolos.cti.gr/en/pisma/pisma.html>
� Shared Mem Arch: <http://www.ncsa.uiuc.edu/General/Exemplar/ARPA>
� Textbooks on Comp Arch:
<http://www.rdrop.com/~cary/html/computer_architecture.html#book>
and VLSI design <http://www.rdrop.com/~cary/html/vlsi.html>
� Comp Arch Conference and Journals
<http://www.handshake.de/user/kroening/conferences.html>
� WWW Comp arch page <http://www.cs.wisc.edu/~arch/www>
4.3. University Lecture notes on CPU Architecture
� Advanced Computer Architecture
<http://www.cs.utexas.edu/users/dahlin/Classes/GradArch>
� Computer architecture - Course level 415
<http://www.diku.dk/teaching/2000f/f00.415>
� MIT: <http://www.csg.lcs.mit.edu/6.823>
� UBC CPU slides :
<http://www.cs.ubc.ca/spider/neufeld/courses/cs218/chapter8/index.htm>
� Purdue Univ slides:
<http://www.ece.purdue.edu/~gba/ee565/Sessions/S03HTML/index.htm>
� Rutgers Univ - Principles of Comp Arch :
<http://www.cs.rutgers.edu/~murdocca/POCA/Chapter02.html>
� Brown Univ -
<http://www.engin.brown.edu/faculty/daniels/DDZO/cmparc.html>
� Univ of Sydney - Intro Digital Systems :
<http://www.eelab.usyd.edu.au/digital_tutorial/part3>
� Bournemouth Univ, UK Principles of Computer Systems :
<http://ncca.bournemouth.ac.uk/CourseInfo/BAVisAn/Year1/CompSys>
� Parallel Virtual machine:
<http://www.netlib.org/pvm3/book/node1.html>
� univ center: <http://www.eecs.lehigh.edu/~mschulte/ece401-99>
� univ course: <http://www.cs.utexas.edu/users/fussell/cs352>
� Examples of working VLSI circuits(in Greek)
<http://students.ceid.upatras.gr/~gef/projects/vlsi>
4.4. CPU Architecture
Visit the following links for information on CPU architecture
� Comp architecture:
<http://www.rdrop.com/~cary/html/computer_architecture.html> and
VLSI design <http://www.rdrop.com/~cary/html/vlsi.html>
� Beyond RISC - The Post-RISC Architecture
<http://www.cps.msu.edu/~crs/cps920>
� Beyond RISC - PostRISC :
<http://www.ceng.metu.edu.tr/~e106170/postrisc.html>
� List of CPUS
<http://einstein.et.tudelft.nl/~offerman/cl.contents2.html>
� PowerPC Arch
<http://www.mactech.com/articles/mactech/Vol.10/10.08/PowerPcArchitecture>
� CPU Info center - List of CPUs sparc, arm etc..
<http://bwrc.eecs.berkeley.edu/CIC/tech>
� cpu arch intel IA 64 <http://developer.intel.com/design/ia-64>
� Intel 386 CPU architecture
<http://www.delorie.com/djgpp/doc/ug/asm/about-386.html>
� Freedom CPU architecture <http://f-
cpu.tux.org/original/Freedom.php3>
� Z80 CPU architecture
<http://www.geocities.com/SiliconValley/Peaks/3938/z80arki.htm>
� CRIMSEN OS and teaching-aid CPU
<http://www.dcs.gla.ac.uk/~ian/project3/node1.html>
� Assembly Language concepts
<http://www.cs.uaf.edu/~cs301/notes/Chapter1/node1.html>
� Alpha CPU architecture
<http://www.linux3d.net/cpu/CPU/alpha/index.shtml>
� <http://hugsvr.kaist.ac.kr/~exit/cpu.html>
� Tron CPU architecture <http://tronweb.super-
nova.co.jp/tronvlsicpu.html>
4.5. Usenet Newsgroups for CPU design
� Newsgroup computer architecture <news:comp.arch>
� Newsgroup FPGA <news:comp.arch.fpga>
� Newsgroup Arithmetic <news:comp.arch.arithmetic>
� Newsgroup Bus <news:comp.arch.bus>
� Newsgroup VME Bus <news:comp.arch.vmebus>
� Newsgroup embedded <news:comp.arch.embedded>
� Newsgroup embedded piclist <news:comp.arch.embedded.piclist>
� Newsgroup storage <news:comp.arch.storage>
� Newsgroup VHDL <news:comp.lang.vhdl>
� Newsgroup Computer Benchmarks <news:comp.benchmarks>
5. Fabrication, Manufacturing CPUs
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 "largest independent foundry" in the world. You
may want to shop around and you will get the best rate for a very high
volume production (greater than 100,000 CPU units).
5.1. Foundry Business is in Billions of dollars!!
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 are -- Taiwan Semiconductor
Manufacturing Co. (TSMC), United Microelectronics Corp. (UMC), and
Chartered Semiconductor Manufacturing Ltd. Pte.--collectively account
for 69% of today's silicon foundry volume, but their share is expected
to grow to 88% by 2004.
5.2. Fabrication of CPU
There are hundreds of foundries in the world (too numerous to list).
Some of them are -
� TSMC (Taiwan Semi-conductor Manufacturing Co)
<http://www.tsmc.com>, about co
<http://www.tsmc.com/about/index.html>
� Chartered Semiconductor Manufacturing, Singapore
<http://www.csminc.com>
� United Microelectronics Corp. (UMC)
<http://www.umc.com/index.html>
� Advanced BGA Packing <http://www.abpac.com>
� Amcor, Arizona <http://www.amkor.com>
� Elume, USA <http://www.elume.com>
� X-Fab, Gesellschaft zur Fertigung von Wafern mbH, Erfurt, Germany
<http://www.xfab.com>
� IBM corporation, (Semi-conductor foundry div) <http://www.ibm.com>
� National Semi-conductor Co, Santa Clara, USA
<http://www.natioanl.com>
� Intel corporation (Semi-conductor foundries), USA
<http://www.intel.com>
� Hitachi Semi-conductor Co, Japan <http://www.hitachi.com>
� Fujitsu Semi-conductor Co, Japan
� Mitsubhishi Semi-conductor Co, Japan
� Hyandai Semi-conductor, Korea <http://www.hea.com>
� Samsumg Semi-conductor, Korea
� Atmel, France <http://www.atmel-wm.com>
If you know any major foundries, let me know I will add to list.
List of CHIP foundry companies
� Chip directory
<http://www.xs4all.nl/~ganswijk/chipdir/make/foundry.htm>
� Chip makers
<http://www.xs4all.nl/~ganswijk/chipdir/make/index.htm>
� IC manufacturers <http://www.xs4all.nl/~ganswijk/chipdir/c/a.htm>
6. Super Computer Architecture
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 -
� Top 500 super computers <http://www.top500.org/ORSC/2000>
� National Computing Facilities Foundation
<http://www.nwo.nl/ncf/indexeng.htm>
� Linux Super Computer Beowulf cluster
<http://www.linuxdoc.org/HOWTO/Beowulf-HOWTO.html>
� Extreme machines - beowulf cluster <http://www.xtreme-
machines.com>
� System architecture description of the Hitachi SR2201
<http://www.hitachi.co.jp/Prod/comp/hpc/eng/sr1.html>
� Personal Parallel Supercomputers
<http://www.checs.net/checs_98/papers/super>
6.1. Main Architectural Classes
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.
6.2. SISD machines
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.
6.3. SIMD machines
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.
6.4. MISD machines
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.
6.5. MIMD machines
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.
6.5.1. Shared memory systems
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.
6.5.2. Distributed memory systems
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.
6.6. Distributed Processing Systems
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.
6.7. ccNUMA machines
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.
7. Neural Network Processors
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:
� According to the DARPA Neural Network Study : A neural network is a
system composed of many simple processing elements operating in
parallel whose function is determined by network structure,
connection strengths, and the processing performed at computing
elements or nodes.
� According to Haykin: A neural network is a massively parallel
distributed processor that has a natural propensity for storing
experiential knowledge and making it available for use. It
resembles the brain in two respects:
� Knowledge is acquired by the network through a learning process.
� Interneuron connection strengths known as synaptic weights are used
to store the knowledge.
� According to Nigrin: A neural network is a circuit composed of a
very large number of simple processing elements that are neurally
based. Each element operates only on local information.
Furthermore each element operates asynchronously; thus there is no
overall system clock.
� According to Zurada: Artificial neural systems, or neural networks,
are physical cellular systems which can acquire, store, and utilize
experiential knowledge.
Visit the following sites for more info on Neural Network Processors
� Omers Neural Network pointers
<http://www.cs.cf.ac.uk/User/O.F.Rana/neural.html>
� FAQ site <ftp://ftp.sas.com/pub/neural/FAQ.html>
� Automation corp Neural Network Processor <http://www.accurate-
automation.com/Products/NNP.HTM> hardware
8. Related URLs
Visit following locators which are related -
� Color Vim editor <http://metalab.unc.edu/LDP/HOWTO/Vim-HOWTO.html>
� Source code control system <http://metalab.unc.edu/LDP/HOWTO/CVS-
HOWTO.html>
� Linux goodies main site <http://www.aldev.8m.com>
� Linux goodies mirror site <http://aldev.webjump.com>
� Linux goodies mirror site <http://aldev.50megs.com>
9. Other Formats of this Document
This document is published in 12 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 and SGML.
� You can get this HOWTO document as a single file tar ball in HTML,
DVI, Postscript or SGML formats from -
<ftp://sunsite.unc.edu/pub/Linux/docs/HOWTO/other-formats/>
� Plain text format is in:
<ftp://sunsite.unc.edu/pub/Linux/docs/HOWTO>
� Translations to other languages like French, German, Spanish,
Chinese, Japanese are in
<ftp://sunsite.unc.edu/pub/Linux/docs/HOWTO> Any help from you to
translate to other languages is welcome.
The document is written using a tool called "SGML-Tools" which can
be got from - <http://www.sgmltools.org> Compiling the source you
will get the following commands like
� sgml2html CPU-Design-HOWTO.sgml (to generate html file)
� sgml2rtf CPU-Design-HOWTO.sgml (to generate RTF file)
� sgml2latex CPU-Design-HOWTO.sgml (to generate latex file)
LaTeX documents may be converted into PDF files simply by producing a
Postscript output using sgml2latex ( and dvips) and running the output
through the Acrobat distill ( <http://www.adobe.com>) command as
follows:
______________________________________________________________________
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 ps2pdf. ps2pdf is a work-alike for
nearly all the functionality of Adobe's Acrobat Distiller product: it
converts PostScript files to Portable Document Format (PDF) files.
ps2pdf is implemented as a very small command script (batch file) that
invokes Ghostscript, selecting a special "output device" called
pdfwrite. In order to use ps2pdf, the pdfwrite device must be included
in the makefile when Ghostscript was compiled; see the documentation
on building Ghostscript for details.
This howto document is located at -
� <http://sunsite.unc.edu/LDP/HOWTO/CPU-Design-HOWTO.html>
Also you can find this document at the following mirrors sites -
� <http://www.caldera.com/LDP/HOWTO/CPU-Design-HOWTO.html>
� <http://www.WGS.com/LDP/HOWTO/CPU-Design-HOWTO.html>
� <http://www.cc.gatech.edu/linux/LDP/HOWTO/CPU-Design-HOWTO.html>
� <http://www.redhat.com/linux-info/ldp/HOWTO/CPU-Design-HOWTO.html>
� Other mirror sites near you (network-address-wise) can be found at
<http://sunsite.unc.edu/LDP/hmirrors.html> select a site and go to
directory /LDP/HOWTO/CPU-Design-HOWTO.html
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 -
xdvi -geometry 80x90 howto.dvi
man xdvi
And resize the window with mouse. To navigate use Arrow keys, Page
Up, Page Down keys, also you can use 'f', 'd', 'u', 'c', 'l', 'r',
'p', 'n' letter keys to move up, down, center, next page, previous
page etc. To turn off expert menu press 'x'.
You can read postscript file using the program 'gv' (ghostview) or The
ghostscript program is in ghostscript*.rpm package and gv program is
in gv*.rpm package in Redhat Linux which can be located through
ControlPanel | Applications | Graphics menu buttons. The gv program is
much more user friendly than ghostscript. Also ghostscript and gv are
available on other platforms like OS/2, Windows 95 and NT, you view
this document even on those platforms.
� Get ghostscript for Windows 95, OS/2, and for all OSes from
<http://www.cs.wisc.edu/~ghost>
To read postscript document give the command -
gv howto.ps
ghostscript howto.ps
You can read HTML format document using Netscape Navigator, Microsoft
Internet explorer, Redhat Baron Web browser or any of the 10 other web
browsers.
You can read the latex, LyX output using LyX a X-Windows front end to
latex.
10. Copyright
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.