Speed-up of Parallel Processing of Divisible Loads on k-dimensional Meshes and Tori

2003 ◽  
Vol 46 (6) ◽  
pp. 625-631 ◽  
Author(s):  
K. Li
Keyword(s):  
Parallel Processing ◽  
Divisible Loads ◽  
Speed Up

Divisible Loads and Parallel Processing

2020 ◽  
pp. 101-137
Author(s):  
Thomas G. Robertazzi ◽  
Li Shi
Keyword(s):  
Parallel Processing ◽  
Divisible Loads

A PRODUCT FORM SOLUTION FOR TREE NETWORKS WITH DIVISIBLE LOADS

2011 ◽  
Vol 21 (01) ◽  
pp. 13-20 ◽  
Author(s):  
THOMAS G. ROBERTAZZI
Keyword(s):  
Parallel Processing ◽  
Equilibrium State ◽  
Queueing Networks ◽  
Form Solution ◽  
Product Form ◽  
Minimal Amount ◽  
Divisible Loads ◽  
Divisible Load ◽  
Multi Level ◽  
Open Question

A product form solution for the optimal fractions of divisible load to distribute to processors in a multi-level tree network is described. Here optimality involves parallel processing the load in a minimal amount of time. This tractable solution is similar to the product form solution for equilibrium state probabilities arising in Markovian queueing networks. The existence of this product form solution answers a long standing open question for divisible load scheduling.

Bitmap Join Indexes vs. Data Partitioning

2009 ◽  
pp. 2292-2300
Author(s):  
Ladjel Bellatreche
Keyword(s):  
Parallel Processing ◽  
Data Partitioning ◽  
Optimization Techniques ◽  
Sloan Digital Sky Survey ◽  
Materialized Views ◽  
Binary Operations ◽  
Vertical Partitioning ◽  
Speed Up ◽  
Redundant Structure ◽  
Horizontal Partitioning

Scientific databases and data warehouses store large amounts of data ith several tables and attributes. For instance, the Sloan Digital Sky Survey (SDSS) astronomical database contains a large number of tables with hundreds of attributes, which can be queried in various combinations (Papadomanolakis & Ailamaki, 2004). These queries involve many tables using binary operations, such as joins. To speed up these queries, many optimization structures were proposed that can be divided into two main categories: redundant structures like materialized views, advanced indexing schemes (bitmap, bitmap join indexes, etc.) (Sanjay, Chaudhuri & Narasayya, 2000) and vertical partitioning (Sanjay, Narasayya & Yang 2004) and non redundant structures like horizontal partitioning (Sanjay, Narasayya & Yang 2004; Bellatreche, Boukhalfa & Mohania, 2007) and parallel processing (Datta, Moon, & Thomas, 2000; Stöhr, Märtens & Rahm, 2000). These optimization techniques are used either in a sequential manner ou combined. These combinations are done intra-structures: materialized views and indexes for redundant and partitioning and data parallel processing for no redundant. Materialized views and indexes compete for the same resource representing storage, and incur maintenance overhead in the presence of updates (Sanjay, Chaudhuri & Narasayya, 2000). None work addresses the problem of selecting combined optimization structures. In this paper, we propose two approaches; one for combining a non redundant structures horizontal partitioning and a redundant structure bitmap indexes in order to reduce the query processing and reduce the maintenance overhead, and another to exploit algorithms for vertical partitioning to generate bitmap join indexes. To facilitate the understanding of our approaches, for review these techniques in details.

scholarly journals Enhancing Apple Maturation Recognition Performance Based on Field Programmable Gate Array Implementation

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Fouad H. Awad ◽  
Mohammed A. Fadhel ◽  
Khattab M. Ali Alheeti ◽  
Omran Al-Shamma ◽  
Laith Alzubaidi
Keyword(s):  
Parallel Processing ◽  
Field Programmable Gate Array ◽  
Recognition Performance ◽  
Recognition System ◽  
Clustering Technique ◽  
Field Programmable ◽  
Speed Up ◽  
Gate Array ◽  
Hardware Designs ◽  
Mature Apple

Recently, several techniques have been developed for vegetable and fruit maturing recognition. Adding hardware designs will enhance the recognition performance. Especially, parallel processing designs efficiently speed up the process functions. This paper utilizes a hardware parallel processing design called field programmable gate array for that purpose. In addition, two different methods; namely K-means clustering and color thresholding are used for recognizing the apple maturation. This study aims to design and implement a mature apple recognition system based on field programmable gate array. The results demonstrate that the color thresholding technique is faster, more reliable and more effective than the K-means clustering technique.

A PARALLEL DECOUPLING TECHNIQUE TO ACCELERATE CONVERGENCE OF RELAXATION SOLUTION OF INTEGRAL-DIFFERENTIAL-ALGEBRAIC EQUATIONS

2001 ◽  
Vol 02 (03) ◽  
pp. 295-304 ◽  
Author(s):  
ZU-LAN HUANG ◽  
RICHARD M. M. CHEN ◽  
YAO-LIN JIANG
Keyword(s):  
Parallel Processing ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Numerical Examples ◽  
Novel Technique ◽  
Relaxation Solution ◽  
Speed Up ◽  
Accelerate Convergence ◽  
Linear Integral

In this paper, we first study the covergence performance of relaxatio-based algorithms for linear integral differential-algebraic equations (IDAEs), then a parallel decoupling technique to speed up the convergence of the relaxation-based algorithms is derived. This novel technique is suitable for implementation of parallel processing for complicated systems of IDAEs. Factors taking effect on the performance of parallel processing are discussed in detail. Large numerical examples running on a network of IBM RS/6000 SP2 system are given to illustrate how judicious partitionings of matrices can help improve convergence in parallel processing.

Bitmap Join Indexes vs. Data Partitioning

2011 ◽  
pp. 171-177
Author(s):  
Ladjel Bellatreche
Keyword(s):  
Parallel Processing ◽  
Data Partitioning ◽  
Optimization Techniques ◽  
Sloan Digital Sky Survey ◽  
Materialized Views ◽  
Binary Operations ◽  
Vertical Partitioning ◽  
Speed Up ◽  
Redundant Structure ◽  
Horizontal Partitioning

Scientific databases and data warehouses store large amounts of data ith several tables and attributes. For instance, the Sloan Digital Sky Survey (SDSS) astronomical database contains a large number of tables with hundreds of attributes, which can be queried in various combinations (Papadomanolakis & Ailamaki, 2004). These queries involve many tables using binary operations, such as joins. To speed up these queries, many optimization structures were proposed that can be divided into two main categories: redundant structures like materialized views, advanced indexing schemes (bitmap, bitmap join indexes, etc.) (Sanjay, Chaudhuri & Narasayya, 2000) and vertical partitioning (Sanjay, Narasayya & Yang 2004) and non redundant structures like horizontal partitioning (Sanjay, Narasayya & Yang 2004; Bellatreche, Boukhalfa & Mohania, 2007) and parallel processing (Datta, Moon, & Thomas, 2000; Stöhr, Märtens & Rahm, 2000). These optimization techniques are used either in a sequential manner ou combined. These combinations are done intra-structures: materialized views and indexes for redundant and partitioning and data parallel processing for no redundant. Materialized views and indexes compete for the same resource representing storage, and incur maintenance overhead in the presence of updates (Sanjay, Chaudhuri & Narasayya, 2000). None work addresses the problem of selecting combined optimization structures. In this paper, we propose two approaches; one for combining a non redundant structures horizontal partitioning and a redundant structure bitmap indexes in order to reduce the query processing and reduce the maintenance overhead, and another to exploit algorithms for vertical partitioning to generate bitmap join indexes. To facilitate the understanding of our approaches, for review these techniques in details.

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