Due to advances in integrated circuit technology, multiprocessor systems with more than two Central Processing Units are becoming economically feasible. For this reason, the study of such systems with the aim of developing more efficient hardware and software structures is gaining interest. One type of multiprocessor structure which has recently received some attention is the dynamically microprogrammable multiprocessor system. This paper investigates the problems of efficiently allocating the processors of such a system among the system's workload. A collection of algorithms and scheduling procedures is developed which may be used for processor allocation in dynamically microprogrammable multiprocessor systems with an arbitrary number of processors. Proofs that these algorithms produce configurations which optimise certain measures are given. The algorithms are practical in the sense that the computation required increases linearly with respect to the number of processors to be allocated. Finally, a simulation study has shown that in many circumstances the use of these algorithms can be expected to yield a significant improvement in system performance over an allocation scheme previously proposed.

Two distinct algorithms for computing the generalised factorial function defined by Cooper (1966) are written in a FORTRAN-like language and then, without use of the principle of recursion induction (McCarthy, 1962) are proved equivalent.

Most large time-sharing computers require some sort of a data concentrator or multiplexor to accept inputs from a large number of low-speed remote terminals. Two major disadvantages of most of these concentrators are that they are nonprogrammable and relatively expensive. This paper describes the use of a small microprogrammed computer with a special instruction wired into the READ-ONLY memory to perform the multiplexing action. This approach has resulted in a programmable terminal controller which will handle up to 32 remotes, and provides enough processing capability to do code conversion and editing. This not only relieves the main computer of these routine tasks, but also reduces the amount and complexity of system modification within the main computer.