Performance Enhancement in Multiprocessing Systems
Dynamic Algorithms for Efficient Dependent Task Scheduling
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Parallel processing is an efficient form of information processing that emphasizes the concurrent manipulation of data elements belonging to one or more processes solving a single problem. It makes a tremendous impact on many areas of computer applications like computational simulations for scientific and engineering applications, commercial applications in data mining, transaction processing etc. It is one of the approaches known today, to make computation feasible. Heterogeneous systems create unlimited opportunities and challenges in the fields of parallel processing, design of algorithms, ...
Parallel processing is an efficient form of information processing that emphasizes the concurrent manipulation of data elements belonging to one or more processes solving a single problem. It makes a tremendous impact on many areas of computer applications like computational simulations for scientific and engineering applications, commercial applications in data mining, transaction processing etc. It is one of the approaches known today, to make computation feasible. Heterogeneous systems create unlimited opportunities and challenges in the fields of parallel processing, design of algorithms, and partitioning and mapping of parallel tasks. In mapping of parallel tasks, scheduling plays an important role. In this book, three algorithms Task oriented Dynamic Scheduling Algorithm (TDSA), Dynamic Task Duplication based Scheduling Algorithm (DyDupSA) and Dynamic Ant Colony Optimization (DyACO) are proposed. TDSA algorithm use the concept of migration, DyDupSA applies duplication and migration and DyACO meta heuristic to minimize the makespan and to maximize the processor utilization. Among the proposed algorithms, DyACO algorithm outperforms the other algorithms.
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