Implications of Job Loading and Scheduling Structures on Machine Memory Effectiveness

Abstract

The reliable parameter for the determining the effectiveness of processing elements (such as memory and processors) is the number of cycles per instructions (CPI), execution speedups, and frequency. Job loading and scheduling techniques target instructions processing in a manner to support the underlying hardware requirements. One of the earliest methods of scheduling jobs for machines involves arrangements of instruction sets in serial order known as pipelining. Another technique uses the principle of overlapping for instruction sets in order to allow current processing and executions which is introduced in this paper. Again, there is job scheduling technique that requires enlargement of processing elements known as static approach as in the case of Intel Itanium. But, there is a great concern about the most appropriate means of scheduling and loading jobs entirely composed of dependent and branched instructions. The cooperative processing nature of present-day computation has expanded the need to allow users to be involved in multiple problems solving environments. In addition, the paper investigates the implications of these job loading and scheduling approaches on speedup and performance of memory systems. The paper found that overlapping of instruction sets during execution was most effective technique for speedups and memory elements performance. In future works, there is need to focus on parallelism exploitations among diverse machines cooperating in instruction processing and execution.