SECOND GENERATION COMPUTER

SECOND GENERATION COMPUTER (1954-1962)

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. By 1948, the invention greatly changed the computer's development. The transistor replaced the large, cumbersome vacuum tube in televisions, radio and computers. As a result, the size of electronic machinery has been shrinking ever science. The transistor was at work in the computer by 1956. Coupled with early advances in magnetic- core memory, transistors led to second generations computers that were smaller, faster more reliable and more energy efficient than their predecessors. The first large scale machines to take advantage of this transistor technology were early supercomputers, stretch by IBM and LARC by Sperry-Rand. These computers, for developed for atomic energy laboratories, could handle an enormous amount of data, a capability much in demand by atomic scientists. The machines were costly, however, and tended to be too powerful for the business sector's computing needs there by limiting their attractiveness.

During the second generation many high level programming languages were introduced, including FORTRAN (1956), ALGOL (1958), and GOBOL (1959) important. Commercial machines of this era include the IBM 704 and its successors, the 709 and 7094. The later introduced I/O processors for better Throughput between I/O ports and main memory. The second generations 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 were early examples of machines that overlapped memory operations with processor operations and had primitive forms of parallel processing.