We propose the use of programmable Grid resource partitioning heuristics in the context of a distributed service Grid management architecture. The architecture is capable of performing automated and exclusive resource-to-service assignations based on Grid resource status/properties and monitored service demand. We present two distinct approaches for the partitioning problem, the first based on ...

It is desirable to design partitioning techniques that minimize the I/O time incurred during query execution in spatial databases. In this paper, we explore optimal partitioning techniques for spatial data for diierent types of queries, and develop multi-disk allocation techniques that maximize the degree of I/O parallelism obtained during the retrieval. We show that hexagonal partitioning has ...

Accurate energy production forecasting is critical when planning for the economic development of a country. A deep learning approach based on Long Short-Term Memory (LSTM) to forecast one-day-ahead from run-of-river hydroelectric power plants in Turkey was introduced present study. In addition LSTM network, three different data-driven methods, namely, adaptive neuro-fuzzy inference system (ANFI...

It is desirable to design partitioning techniques that minimize the I/O time incurred during query execution in spatial databases. In this paper, we explore optimal partitioning techniques for spatial data for diierent types of queries. In particular, we show that hexagonal partitioning has optimal I/O cost for circular queries compared to all possible non-overlapping partitioning techniques th...

This paper presents a computationally efficient runtime partitioning and load-balancing scheme for the Distributed Adaptive Grid Hierarchies that underlie adaptive mesh-refinement methods. The partitioning scheme yields an efficient parallel computational structure that maintains locality to reduce communications. Further, it enables dynamic re-partitioning and loadbalancing of the adaptive gri...

Parallel structured adaptive mesh refinement (SAMR) methods increase the efficiency of the numerical solution to partial differential equations. These methods use an adaptive grid hierarchy to dynamically assign computational resources to areas with large solution errors. The grid hierarchy needs to be repeatedly repartitioned and distributed over the processors but no single partitioning algor...

Rectilinear Binary Space Partitioning (BSP) trees are often used for solving various types of range searching problems including ray shooting. We propose a novel method for construction of rectilinear BSP trees for a preferred set of ray shooting queries. Particularly, we study ray sets formed by fixing either the direction or the origin of rays. We analyse and discuss the properties of constru...

In this paper we present a pilot implementation of the Meta-Partitioner, a partitioning framework that automatically selects, configures, and invokes suitable partitioning algorithms for Structured Adaptive Mesh Refinement (SAMR) applications. Efficient use of SAMR on parallel computers requires that the dynamic grid hierarchy is repeatedly repartitioned and redistributed. The partitioning proc...

A computational method for partitioning a charge density grid into Bader volumes is presented which is efficient, robust, and scales linearly with the number of grid points. The partitioning algorithm follows the steepest ascent paths along the charge density gradient from grid point to grid point until a charge density maximum is reached. In this paper, we describe how accurate off-lattice asc...