Abstract
A multiprocessor system is a computer with two or more central processing units (CPUs) with each one sharing the common main memory as well as the peripherals. Multiprocessor system is either homogeneous or heterogeneous system. A homogeneous system is a cluster of processors joined to a high speed network for accomplishing the required task; also it is defined as parallel computing system. Homogeneous is a technique of parallel computing system. A heterogeneous system can be defined as the interconnection of a number of processors, having dissimilar computational speed. Load balance is a method of distributing work between the processors fairly in order to get optimal response time, resource utilization, and throughput. Load balancing is either static or dynamic. In static load balancing, work is distributed among all processors before the execution of the algorithm. In dynamic load balancing, work is distributed among all processors during execution of the algorithm. So problems arise when it cannot statistically divide the tasks among the processors. To use multiprocessor systems efficiently, several load balancing algorithms have been adopted widely. This paper proposes an efficient load balance algorithm which addresses common overheads that may decrease the efficiency of a multiprocessor system. Such overheads are synchronization, data communication, response time, and throughput.
Highlights
Parallel processing has emerged as a key enabling technology in modern computers, driven by the ever increasing demand for higher performance, lower costs and sustained productivity in real life applications
Parallel processing is an efficient form of information processing
Processor work states are defined in this phase, and are used to achieve a balanced load distribution in the multiprocessor system
Summary
Parallel processing has emerged as a key enabling technology in modern computers, driven by the ever increasing demand for higher performance, lower costs and sustained productivity in real life applications. Concurrent events are taking place in today’s high-performance computers due to the common practice of multiprogramming and multiprocessing [1]. Parallel processing is an efficient form of information processing. Parallel events may occur in multiple resources during the same interval. Parallel processing demands concurrent execution of many programs in the computer [2]. Multiprocessor management and scheduling has been a fertile source of interesting problems for researchers in the field of computer engineering. In its most general form, the problem involves the scheduling of a set of processes on a set of processors with arbitrary characteristics in order to optimize some objective function
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