Scheduling is a decision-making process that is concerned with the allocation of limited resources to competing tasks (operations of jobs) over a time period with the goal of optimizing one or more objectives. In theory, the objective is usually to optimize some classical system performance measures such as makespan, tardiness/earliness and flowtime under deterministic and static assumptions. I...

Loop scheduling scheme plays a critical role in the efficient execution of programs, especially loop dominated applications. This paper presents KASS, a knowledge-based adaptive loop scheduling scheme. KASS consists of two phases: static partitioning and dynamic scheduling. To balance the workload, the knowledge of loop features and the capabilities of processors are both taken into account usi...

The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear types of archit...

Parallel jobs submitted to processors should be efficiently scheduled to achieve high performance. Early scheduling strategies for parallel jobs make use of either space-sharing approach or time-sharing approach. The scheduling strategy proposed in this work, makes use of both the policies for parallel jobs while scheduling under clusters. Static and dynamic scheduling algorithms were developed...

Runtime Incremental Parallel Scheduling (RIPS) is an alternative strategy to the commonly used dynamic scheduling. In this scheduling strategy, the system scheduling activity alternates with the underlying computation work. RIPS utilizes the advanced parallel scheduling technique to produce a low-overhead, high-quality load balancing, as well as adapting to irregular applications. This paper pr...

Applications such as image processing, uid mechanics, and geophysical data analysis are examples of problems that require the high computing performance provided by multi-processor systems. Such performance depends highly on the inter-processor communication time resulting from the allocating tasks to the individual processors. This research focuses on the development of techniques that reduce ...

In this paper, we consider the increased performance that can be obtained by using, in concert , three previously proposed enhancements. These enhancements are aggressive dynamic (run time) instruction scheduling, the reuse of decoded instructions, and trace scheduling (both aggressive dynamic instruction scheduling and decoded instruction reuse have been used in commercial systems). We show th...

Distributed arrival time control (DATC) is a highly distributed feedback control algorithm for the scheduling problems in heterarchical operation systems [V.V. Prabhu, Performance of real-time distributed arrival time control in heterarchical manufacturing systems, IIE Transactions 32 (2000) 323–331]. Although DATC has presented outstanding performance for the real-time scheduling problems in d...

Performance properties of list scheduling algorithms under various dynamic assumptions are analyzed. The focus is on bounds for scheduling directed acyclic graphs with arbitrary precedence constrains and arbitrary task processing times subject to minimizing the makespan. New performance bounds are derived and compared with known results. key words: list scheduling, worst case analysis, on-line ...