Schaum's outline of introduction to computer science Schaum's outline series. Material. Type. Book. Language English. Title. Schaum's outline of introduction to . SCHAUM'S OUTLINE OFPrinciples ofCOMPUTER SCIENCE CARL REYNOLDS Introduction to Computer Science WHAT IS COMPUTER SCIENCE?. Placement Computer Science / Introduction to Computer Animation - Computer Associate Professor of Computer Science SCHAUM'S OUTLINE SERIES .. In this case it is the identification of the selected manual item that counts and.
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Schaum's Outline of Introduction to Computer Science by Ramon A. Mata-Toledo, , available at Book Depository with free delivery worldwide. Overview (cf Schaum Chapter 1). Basic computing science is about using computers to do things for us. These things amount by Carl Reynolds and Paul Tymann, Schaum's Outline Series, MacGraw-Hill, The following. Schaum's Outline of Introduction to Computer Science [Pauline Cushman, Ramon Mata-Toledo] on wm-greece.info *FREE* shipping on qualifying offers.
Atanasoff, a professor of physics and mathematics at Iowa State, in Atanasoff set out to build a machine that would help his graduate students solve systems of partial differential equations.
By , he and graduate student Clifford Berry had succeeded in building a machine that could solve 29 simultaneous equations with 29 unknowns. However, the machine was not programmable, and was more of an electronic calculator. A second early electronic machine was Colossus, designed by Alan Turning for the British military in Turnings 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.
The existence of Colossus was kept secret until long after the war ended, and the credit due to Turning and his colleagues for designing one of the first working electronic computers was slow in coming. Presper Eckert and John V. Mauchly at the University of Pennysylvania. The machine wasnt completed until , but then it was used extensively for calculations during the design of the hydrogen bomb.
By the time it was decommissioned in it had been used for research on the design of wind tunnels, random number generators, and weather prediction.
There is some controversy over who deserves the credit for this idea, but no one knows how important the idea was to the future of general purpose computers. ENIAC was controlled by a set of external switches and dials; to change the program required physically altering the settings on these controls.
These controls also limited the speed of the internal electronic operations. Through the use of a memory that was large enough to hold both instructions and data, and using the program stored in memory to control the order of arithmetic operations, EDVAC was able to run orders of magnitude faster than ENIAC.
By storing instructions in the same medium as data, designers could concentrate on improving the internal structure of the machine without worrying about matching it to the speed of an external control.
Regardless of who deserves the credit for the stored program idea, the EDVAC project is significant as an example of the power of interdisciplinary projects that characterize modern computational science. By recognizing that functions, in the form of a sequence of instructions for a computer, can be encoded as numbers, the EDVAC group knew the instructions could be stored in the computers memory a long with numerical data.
The notion of using numbers to represent functions was a key step used by Goedel in his incompleteness theorem in , work which Von Neumann, as a logician, was quite familiar with. Von Neumanns background in logic, combined with Eckert and Mauchlys electrical engineering skills, formed a very powerful interdisciplinary team. Software technology during this period was very primitive. The first programs were written out in machine code, i. By the s programmers were using a symbolic notation, known as assembly language, then hand25 translating the symbolic notation into machine code.
Later programs known as assemblers performed the translation task. As primitive as they were, these first electronic machines were quite useful in applied science and engineering. Atanasoff estimated that it would take eight hours to solve a set of equations with eight unknowns using a Marchant calculator, and hours to solve 29 equations for 29 unknowns.
The Atanasoff-Berry computer was able to complete the task in under an hour. The first problem run on the ENIAC, a numerical simulation used in the design of the hydrogen bomb, required 20 seconds, as opposed to forty hours using mechanical calculators.
Electronic switches in this era were based on discrete diode and transistor technology with a switching time of approximately 0. 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. Important commercial machines of this era include the IBM and 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 s deserve this title. 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 , 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 devices per chip. Multilayered printed circuits were developed and core memory was replaced by faster, solid state memories.
In , Seymour Cray developed the CDC , 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 was able to attain a computation rate of 1 million floating point operations per second 1 Mflops.
The CDC , with its pipelined functional units, is considered to be the first vector processor and was capable of executing at 10 Mflops. It employed instruction look ahead, separate floating point and integer functional units and pipelined instruction stream. Gate delays dropped to about Ins 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.
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.
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