A Brief History of Computer
Technology
A complete history of computing would include a multitude of diverse devices such as the ancient Chinese abacus, the Jacquard loom (1805) and Charles Babbage's ``analytical engine'' (1834). It would also include discussion of mechanical, analog and digital computing architectures. As late as the 1960s, mechanical devices, such as the Merchant calculator, still found widespread application in science and engineering. During the early days of electronic computing devices, there was much discussion about the relative merits of analog vs. digital computers. In fact, as late as the 1960s, analog computers were routinely used to solve systems of finite difference equations arising in oil reservoir modeling. In the end, digital computing devices proved to have the power, economics and scalability necessary to deal with large scale computations. Digital computers now dominate the computing world in all areas ranging from the hand calculator to the supercomputer and are pervasive throughout society. Therefore, this brief sketch of the development of scientific computing is limited to the area of digital, electronic computers.
The evolution of digital computing is often divided into generations. Each generation is characterized by dramatic improvements over the previous generation in the technology used to build computers, the internal organization of computer systems, and programming languages. The following history has been organized using these widely recognized generations as mileposts.
The Mechanical Era (1623-1945)
The idea of using machines to solve mathematical problems can be traced at least as far as the early 17th century. Mathematicians who designed and implemented calculators that were capable of addition, subtraction, multiplication, and division.
The ABACUS emerged about 5,000 years ago as the earliest form of the Computer. This math tool allows user to make computation using a system of sliding beads arranged on the rack. It evolved from a simple need to account numbers. Merchants trading goods not only needed a way to count goods, but also to quickly calculate the prices of those goods.
In 1642, Blaise Pascal (1623-1662), the 18-year-old son of French tax collector, invented what he called a numerical wheel calculator to help his father with his duties.
This brass rectangular box, also called a Pascaline, used eight movable dials to add sums up to eight figures long.
In 1694, a German mathematical and philosopher, Gottfried Willhem von Leibniz (1646-1716), improved the Pascaline by creating a machine that could also multiply.
Charles Xavier Thomas de Colmar, a Frenchman, invented a machine that could perform the four basic arithmetic functions.
Colmar’s mechanical calculator, the ARITHOMETER or ARITHMOMETER, presented a more practical approach to computing because it could add, subtract, multiply, and divide.
The Computers as we know them today began with an English mathematics professor, Charles Babbage (1791-1871). He was called the father of Computer.
Babbage’s first attempt at solving this problem was in 1822 when he proposed a machine to perform different equations, called a Difference Engine.After working on the Difference Engine for 10 years, Babbage was suddenly inspired to begin work on the first general-purpose computer, which he called the Analytical Engine.
Augusta Ada King, Countess of Lovelace, daughter to English Poet lord Byron, and Babbage’s assistance, was instrumental in the Machine’s design. She helped revise plans and secure funding from the British government. She is noted as the first computer programmer. The Analytical engine never worked but his plans embodied the basic elements of modern computers: Input, output, store, process, and control.
In 1889, an American inventor, Herman Hollerith (1860-1929), Also applied the Jacquard loom concept to computing. His first task was to find a faster way to compute the U.S census. Hollerith brought his PUNCH CARD READER into the business world, founding Tabulating Machine Company in 1896, later to become International Business Machine (IBM) in 1924.
Electromechanical Accounting Machine
The EAM (Electromechanical Accounting Machine) ushered a new age of inventions through the use of electromechanical devices or components such as electric relays switches. Together with this, the punched-card technology improved.
ABC (Atanasoff-Berry Computer)
John V. Atanasoff, the inventor of the electronic digital computer together with Clifford Berry, built the prototype of an electromechanical digital computer in 1939 featuring the first known use of electronic vacuum tubes for computation. It was known as the ABC (Atanasoff-Berry Computer).
When World War II started on 7 December 1941, the work on the computer came to a halt.
ASCC or Harvard Mark I
Howard Aiken developed the ASCC computer (Automatic Sequence Controlled Calculators) which could carry out of operations, additions, subtraction, multiplication, divisions and reference to previous results. Aiken was much influenced in his ideas by Babbage’s writing and he saw the project to build the ASCC computer as completing the task, which Babbage had set out on but failed to complete. Having completed constructions of ASCC in 1943. it was decided to move the computer to Harvard University where it began to be used from May 1944. Grace Hopper worked with Aiken from 1944 on the ASCC Computer which had been renamed the Harvard Mark1 and given b IBM to Harvard University
The First “Computer Bug”
Moth founded trapped between points at Relay # 70, Panel F, of the Mark II Aiken Relay Calculator while it was being tested at Harvard University, 9 September 1945. The operations affixed the moth to the computer log, with the entry: “First actual case of bug being found”. They put out the word that they had “debugged” the machine, thus introducing the term “debugging” a computer program”.
Alan Turing - A second early electronic machine was Colossus, designed for the British military in 1943. This machine played an important role in breaking codes used by the German army in World War II. Turing's main contribution to the field of computer science was the idea of the Turing machine, a mathematical formalism widely used in the study of computable functions.
src="http://pagead2.googlesyndication.com/pagead/show_ads.js">
First Generation Electronic Computers (1937-1953) – Vacuum Tubes
Three machines have been promoted at various times as the first electronic computers. These machines used electronic switches, in the form of vacuum tubes, instead of electromechanical relays. Electronic components had one major benefit, however: they could ``open'' and ``close'' about 1,000 times faster than mechanical switches.
ENIAC( Electronic Numerical Integrator and Calculator) was the first all purpose, all electronics digital computer. I was built by John Presper Eckert, Jr. and John W Mauchy. ENIAC introduced us to what is commonly referred to as the First Generations of Computers. The ENIAC, being over 1,000 times faster than its electromechanical predecessors, could execute up to 5,000 basic arithmetic operations per second.
Its successor, Electronics Discrete Variable Automatic Computer, or EDVAC treated Instructions as numerical data and stored them electronically in the computer’s Memory. This led to the development of Self-modifying programs.
UNIVAC (Universal Automatic Computer)
Was the first digital computer to handle Both numerical and alphabetical Information with equal ease. first commercially successful computer.
Second Generation (1954-1962) - Transistors
The second generation saw several important developments at all levels of computer system design, from the technology used to build the basic circuits to the programming languages used to write scientific applications. Electronic switches in this era were based on discrete diode and transistor technology with a switching time of approximately 0.3 microseconds. The first machines to be built with this technology include TRADIC at Bell Laboratories in 1954 and TX-0 at MIT's Lincoln Laboratory. Memory technology was based on magnetic cores which could be accessed in random order, as opposed to mercury delay lines, in which data was stored as an acoustic wave that passed sequentially through the medium and could be accessed only when the data moved by the I/O interface.
Important innovations in computer architecture included index registers for controlling loops and floating point units for calculations based on real numbers. Prior to this accessing successive elements in an array was quite tedious and often involved writing self-modifying code (programs which modified themselves as they ran; at the time viewed as a powerful application of the principle that programs and data were fundamentally the same, this practice is now frowned upon as extremely hard to debug and is impossible in most high level languages). Floating point operations were performed by libraries of software routines in early computers, but were done in hardware in second generation machines.
During this second generation many high level programming languages were introduced, including FORTRAN (1956), ALGOL (1958), and COBOL (1959). Important commercial machines of this era include the IBM 704 and its successors, the 709 and 7094. The latter introduced I/O processors for better throughput between I/O devices and main memory.
The second generation also saw the first two supercomputers designed specifically for numeric processing in scientific applications. The term ``supercomputer'' is generally reserved for a machine that is an order of magnitude more powerful than other machines of its era. Two machines of the 1950s deserve this title. The Livermore Atomic Research Computer (LARC) and the IBM 7030 (aka Stretch) were early examples of machines that overlapped memory operations with processor operations and had primitive forms of parallel processing.
Third Generation (1963-1972) – Integrated Circuits
The third generation brought huge gains in computational power. Innovations in this era include the use of integrated circuits, or ICs (semiconductor devices with several transistors built into one physical component), semiconductor memories starting to be used instead of magnetic cores, microprogramming as a technique for efficiently designing complex processors, the coming of age of pipelining and other forms of parallel processing (described in detail in Chapter CA), and the introduction of operating systems and time-sharing.
The first ICs were based on small-scale integration (SSI) circuits, which had around 10 devices per circuit (or ``chip''), and evolved to the use of medium-scale integrated (MSI) circuits, which had up to 100 devices per chip. Multilayered printed circuits were developed and core memory was replaced by faster, solid state memories. Computer designers began to take advantage of parallelism by using multiple functional units, overlapping CPU and I/O operations, and pipelining (internal parallelism) in both the instruction stream and the data stream. In 1964, Seymour Cray developed the CDC 6600, which was the first architecture to use functional parallelism. By using 10 separate functional units that could operate simultaneously and 32 independent memory banks, the CDC 6600 was able to attain a computation rate of 1 million floating point operations per second (1 Mflops). Five years later CDC released the 7600, also developed by Seymour Cray. The CDC 7600, with its pipelined functional units, is considered to be the first vector processor and was capable of executing at 10 Mflops. The IBM 360/91, released during the same period, was roughly twice as fast as the CDC 660. It employed instruction look ahead, separate floating point and integer functional units and pipelined instruction stream. The IBM 360-195 was comparable to the CDC 7600, deriving much of its performance from a very fast cache memory. The SOLOMON computer, developed by Westinghouse Corporation, and the ILLIAC IV, jointly developed by Burroughs, the Department of Defense and the University of Illinois, were representative of the first parallel computers. The Texas Instrument Advanced Scientific Computer (TI-ASC) and the STAR-100 of CDC were pipelined vector processors that demonstrated the viability of that design and set the standards for subsequent vector processors.
Fourth Generation (1972-1984) - Microprocessor
The next generation of computer systems saw the use of large scale integration (LSI - 1000 devices per chip) and very large scale integration (VLSI - 100,000 devices per chip) in the construction of computing elements. At this scale entire processors will fit onto a single chip, and for simple systems the entire computer (processor, main memory, and I/O controllers) can fit on one chip. Gate delays dropped to about 1ns per gate.
Semiconductor memories replaced core memories as the main memory in most systems; until this time the use of semiconductor memory in most systems was limited to registers and cache. During this period, high speed vector processors, such as the CRAY 1, CRAY X-MP and CYBER 205 dominated the high performance computing scene. Computers with large main memory, such as the CRAY 2, began to emerge. A variety of parallel architectures began to appear; however, during this period the parallel computing efforts were of a mostly experimental nature and most computational science was carried out on vector processors. Microcomputers and workstations were introduced and saw wide use as alternatives to time-shared mainframe computers.
Developments in software include very high level languages such as FP (functional programming) and Prolog (programming in logic). These languages tend to use a declarative programming style as opposed to the imperative style of Pascal, C, FORTRAN, et al. In a declarative style, a programmer gives a mathematical specification of what should be computed, leaving many details of how it should be computed to the compiler and/or runtime system. These languages are not yet in wide use, but are very promising as notations for programs that will run on massively parallel computers (systems with over 1,000 processors). Compilers for established languages started to use sophisticated optimization techniques to improve code, and compilers for vector processors were able to vectorize simple loops (turn loops into single instructions that would initiate an operation over an entire vector).
Two important events marked the early part of the third generation: the development of the C programming language and the UNIX operating system, both at Bell Labs. In 1972, Dennis Ritchie, seeking to meet the design goals of CPL and generalize Thompson's B, developed the C language. Thompson and Ritchie then used C to write a version of UNIX for the DEC PDP-11. This C-based UNIX was soon ported to many different computers, relieving users from having to learn a new operating system each time they change computer hardware. UNIX or a derivative of UNIX is now a de facto standard on virtually every computer system.
Fifth Generation (1984-1990) – Parallel Processing
The development of the next generation of computer systems is characterized mainly by the acceptance of parallel processing. Until this time parallelism was limited to pipelining and vector processing, or at most to a few processors sharing jobs. The fifth generation saw the introduction of machines with hundreds of processors that could all be working on different parts of a single program. The scale of integration in semiconductors continued at an incredible pace - by 1990 it was possible to build chips with a million components - and semiconductor memories became standard on all computers.
Other new developments were the widespread use of computer networks and the increasing use of single-user workstations. Prior to 1985 large scale parallel processing was viewed as a research goal, but two systems introduced around this time are typical of the first commercial products to be based on parallel processing. The Sequent Balance 8000 connected up to 20 processors to a single shared memory module (but each processor had its own local cache). The machine was designed to compete with the DEC VAX-780 as a general purpose Unix system, with each processor working on a different user's job. However Sequent provided a library of subroutines that would allow programmers to write programs that would use more than one processor, and the machine was widely used to explore parallel algorithms and programming techniques.
The Intel iPSC-1, nicknamed ``the hypercube'', took a different approach. Instead of using one memory module, Intel connected each processor to its own memory and used a network interface to connect processors. This distributed memory architecture meant memory was no longer a bottleneck and large systems (using more processors) could be built. The largest iPSC-1 had 128 processors. Toward the end of this period a third type of parallel processor was introduced to the market. In this style of machine, known as a data-parallel or SIMD, there are several thousand very simple processors. All processors work under the direction of a single control unit; i.e. if the control unit says ``add a to b'' then all processors find their local copy of a and add it to their local copy of b. Machines in this class include the Connection Machine from Thinking Machines, Inc., and the MP-1 from MasPar, Inc.
Scientific computing in this period was still dominated by vector processing. Most manufacturers of vector processors introduced parallel models, but there were very few (two to eight) processors in this parallel machines. In the area of computer networking, both wide area network (WAN) and local area network (LAN) technology developed at a rapid pace, stimulating a transition from the traditional mainframe computing environment toward a distributed computing environment in which each user has their own workstation for relatively simple tasks (editing and compiling programs, reading mail) but sharing large, expensive resources such as file servers and supercomputers. RISC technology (a style of internal organization of the CPU) and plummeting costs for RAM brought tremendous gains in computational power of relatively low cost workstations and servers. This period also saw a marked increase in both the quality and quantity of scientific visualization.
Sixth Generation (1990 - )
Transitions between generations in computer technology are hard to define, especially as they are taking place. Some changes, such as the switch from vacuum tubes to transistors, are immediately apparent as fundamental changes, but others are clear only in retrospect. Many of the developments in computer systems since 1990 reflect gradual improvements over established systems, and thus it is hard to claim they represent a transition to a new ``generation'', but other developments will prove to be significant changes.
This generation is beginning with many gains in parallel computing, both in the hardware area and in improved understanding of how to develop algorithms to exploit diverse, massively parallel architectures. Parallel systems now compete with vector processors in terms of total computing power and most expect parallel systems to dominate the future. Combinations of parallel/vector architectures are well established, and one corporation (Fujitsu) has announced plans to build a system with over 200 of its high end vector processors. Manufacturers have set themselves the goal of achieving teraflops ( 10 arithmetic operations per second) performance by the middle of the decade, and it is clear this will be obtained only by a system with a thousand processors or more. Workstation technology has continued to improve, with processor designs now using a combination of RISC, pipelining, and parallel processing. As a result it is now possible to purchase a desktop workstation for about $30,000 that has the same overall computing power (100 megaflops) as fourth generation supercomputers. This development has sparked an interest in heterogeneous computing: a program started on one workstation can find idle workstations elsewhere in the local network to run parallel subtasks.
One of the most dramatic changes in the sixth generation will be the explosive growth of wide area networking. Network bandwidth has expanded tremendously in the last few years and will continue to improve for the next several years. T1 transmission rates are now standard for regional networks, and the national ``backbone'' that interconnects regional networks uses T3. Networking technology is becoming more widespread than its original strong base in universities and government laboratories as it is rapidly finding application in K-12 education, community networks and private industry. A little over a decade after the warning voiced in the Lax report, the future of a strong computational science infrastructure is bright. The federal commitment to high performance computing has been further strengthened with the passage of two particularly significant pieces of legislation: the High Performance Computing Act of 1991, which established the High Performance Computing and Communication Program (HPCCP) and Sen. Gore's Information Infrastructure and Technology Act of 1992, which addresses a broad spectrum of issues ranging from high performance computing to expanded network access and the necessity to make leading edge technologies available to educators from kindergarten through graduate school.
In bringing this encapsulated survey of the development of a computational science infrastructure up to date, we observe that the President's FY 1993 budget contains $2.1 billion for mathematics, science, technology and science literacy educational programs, a 43% increase over FY 90 figures.
