Design and implementation of a novel dynamic load balancing library for cluster computing

Towards the Scalability of Dynamic Loop Scheduling Techniques via Discrete Event Simulation

“…Some of these techniques proved to be extremely useful in load balancing scientific applications, such as N-body simulations, Monte Carlo simulations, computational fluid dynamics applications, and others. A number of techniques were also integrated into runtime systems and compilers technology, such as the Fortran compiler PTRAN [7], Mobile Object Layer [8], [9] and Sun ANSI/ISO C compiler. For a more complete analysis of these techniques, the reader may refer to fixed size chunking (FSC) [10], guided self scheduling (GSS) [11], factoring (FAC) [12], weighted factoring (WF) [13], fractiling [14], adaptive weighted factoring (AWF) [15] and variants (AWF-B & AWF-C) [16], adaptive factoring (AF) [17], and others.…”

Autonomic microcell assignment in massively distributed online virtual environments

“…The focus of their work is to optimize and speed up the relocation of tasks by reassigning batches of tasks to optimize the resource negotiations. For systems with a distributed memory architecture, Banicescu et al (2005) propose a dynamic load-balancing library which can be used for parallelizing scientific applications. However, this cannot trivially be applied to highly interactive applications such as MMOGs.…”

Parallel CBIR implementations with load balancing algorithms

“…Banicescu et al propose a load balancing library for scientific applications on distributed memory architectures. The library integrates dynamic loop scheduling as an object migration policy with the object migration mechanism provided by the data movement and control substrate which is extended with a mobile object layer [2].…”