In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to organize the computation of conjugate gradient method with preconditioner applied to normal equations, and Incomplet...
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ISBN:
(纸本)0818678763
In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to organize the computation of conjugate gradient method with preconditioner applied to normal equations, and Incomplete Modified Gram-Schmidt (IMGS) preconditioner for solving sparse least squares problems on massively paralleldistributed memory computers. The performance of these methods an this kind of architecture is always limited because of the global communication required for the inner products. We will describe the parallelization of PCGLS and lMGS preconditioner by two ways of improvement. One is To assemble the results of a number of inner products collectively and the other is to create situations where communication can be overlapped with computation. A theoretical model of computation and communication phases is presented which allows us to decide the number of processors that minimizes the runtime. Several numerical experiments on Parsytec GC/PowerPlus are presented.
Analyzing large data sets is gaining more importance because of its wide variety of applications in parallel and distributed environment. Hadoop environment gives more flexibility to programmers in parallelcomputing....
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ISBN:
(纸本)9789811031564;9789811031557
Analyzing large data sets is gaining more importance because of its wide variety of applications in parallel and distributed environment. Hadoop environment gives more flexibility to programmers in parallelcomputing. One of the advantages of Hadoop is query evaluation over large datasets. Join operations in query evaluation plays a major role over the large data. This paper Ferret outs the earlier solutions, prolongs them and recommends a new approach for the implementation of joins in Hadoop.
The special issue of the ScienceDirect Journal contained 7 extended and revised papers that informed about some of the significant advancements in system performance modeling, analysis, and enhancement. These papers w...
The special issue of the ScienceDirect Journal contained 7 extended and revised papers that informed about some of the significant advancements in system performance modeling, analysis, and enhancement. These papers were presented at the international Workshop on Performance Modeling, Evaluation, and Optimization of parallel and distributed Systems (PMEO-PDS'07). The workshop was held along with the 21st IEEE internationalparallel and distributed Processing Symposium (IPDPS'07) from March 26 30, 2007 in California, US. It aimed to promote the discussion on the development of innovative tools and techniques to deal with the rapid evolution and increasing complexity of high-performance computing and networking systems. The selected papers also dealt with a wide range of significant aspects of performance modeling, analysis, and enhancement of high-performance computing and networking systems.
This paper presents a new structured parallel programming model, ''SEQ OF PAR'': based on the Communication Closed Layer (CCL) principle of causal composition for parallel programs and Bird-Meertens fo...
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ISBN:
(纸本)0818678763
This paper presents a new structured parallel programming model, ''SEQ OF PAR'': based on the Communication Closed Layer (CCL) principle of causal composition for parallel programs and Bird-Meertens formalism (Bh IF) of locality-based parallel computation. This model is to support for more general, architecture-independent parallel programming. It provides a structured approach to integrate task (or process) parallelism and data-parallelism in one framework. The well-founded algebra of CCL and BMF makes it also possible to derive, optimize and verify parallel programs through algebraic transformations. Experimental results show that it is very promising to adopt this programming model for getting efficient, portable parallel code.
advances in computer technologies have enabled corporations to accumulate data at an unprecedented speed. Large-scale business data might contain billions of observations and thousands of features, which easily brings...
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advances in computer technologies have enabled corporations to accumulate data at an unprecedented speed. Large-scale business data might contain billions of observations and thousands of features, which easily brings their scale to the level of terabytes. Most traditional feature selection algorithms are designed and implemented for a centralized computing architecture. Their usability significantly deteriorates when data size exceeds tens of gigabytes. High-performance distributedcomputing frameworks and protocols, such as the Message Passing Interface (MPI) and MapReduce, have been proposed to facilitate software development on grid infrastructures, enabling analysts to process large-scale problems efficiently. This paper presents a novel large-scale feature selection algorithm that is based on variance analysis. The algorithm selects features by evaluating their abilities to explain data variance. It supports both supervised and unsupervised feature selection and can be readily implemented in most distributedcomputing environments. The algorithm was implemented as a SAS High-Performance Analytics procedure, which can read data in distributed form and perform parallel feature selection in both symmetric multiprocessing mode (SMP) and massively parallel processing mode (MPP). Experimental results demonstrated the superior performance of the proposed method for large scale feature selection.
In this paper we present an efficient algorithm for compile-time scheduling and clustering of parallel programs onto parallel processing systems with distributed memory, which is called The Dynamic Critical Path Sched...
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In this paper we present an efficient algorithm for compile-time scheduling and clustering of parallel programs onto parallel processing systems with distributed memory, which is called The Dynamic Critical Path Scheduling DCPS. The DCPS is superior to several other algorithms from the literature in terms of computational complexity, processors consumption and solution quality. DCPS has a time complexity of O(e + v logv), as opposed to DSC algorithm O((e+v) logv) which is the best known algorithm. Experimental results demonstrate the superiority of DCPS over the DSC algorithm.
The advances made by technology ensure increasing popularity of cloud computing, with major industry players having their foundation deeply rooted in the cloud computing technology. The technology depends on resource ...
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ISBN:
(纸本)9781467329255
The advances made by technology ensure increasing popularity of cloud computing, with major industry players having their foundation deeply rooted in the cloud computing technology. The technology depends on resource sharing, thus facilitating coherence and economies of scale. The incessant advances in the technology pose security challenges that are equally striking. It has already been pointed out that cryptography alone cannot meet the privacy demanded by common cloud computing services. The paper presents an implementation of an identity based distributed cloud storage encryption scheme for data storage on cloud which facilitates privacy preservation when the confidential data is stored with a third party and hence escapes the protection sphere of data owner. The proposed scheme is more suitable for the privacy preserving of mass users.
An innovative approach to password cracking by leveraging a distributedcomputing model is developed. The sys- tem comprises a client-server architecture where clients receive segmented password ranges for parallelize...
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An innovative approach to password cracking by leveraging a distributedcomputing model is developed. The sys- tem comprises a client-server architecture where clients receive segmented password ranges for parallelized hashing attempts. The Java-based implementation employs MD5 hashing and divides the password into smaller units for distribution among multiple clients. Each client independently processes its assigned password range, attempting to match the hash against a pre- determined target. The server orchestrates the distribution of password segments and collects results from clients, facilitating the cracking process. Security measures include secure communication protocols, and ethical considerations center around legality, user consent, and emphasizing the educational value of responsible hacking practices. The work explores the tech- nical challenges of distributed password cracking, addressing efficiency, scalability, and security implications, while fostering a deeper understanding of cybersecurity and distributed systems.
A P2P distributed platform is developed using the JXTA technology, which is endowed with resource brokerage strategies to efficiently select peers using our hybrid model which is designed and implemented. The designed...
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ISBN:
(纸本)9781467356183;9781467356176
A P2P distributed platform is developed using the JXTA technology, which is endowed with resource brokerage strategies to efficiently select peers using our hybrid model which is designed and implemented. The designed and implemented peer selection model finds provision as many idle peers as possible while allocating tasks to the various nodes. The control node distributes the tasks to the peers in the network on certain predefined criteria. The controlling node breaks the task into number of subtasks and then submits them to the computing nodes using the hybrid selection process for remote computing. First the peers who are idle will be selected and among those least costly peers will be selected.
Snapshot algorithms are fundamental for many distributed applications and must often be executed repeatedly. We present three snapshot algorithms The first one is based on the assumption of global time, if computes ch...
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ISBN:
(纸本)0818678763
Snapshot algorithms are fundamental for many distributed applications and must often be executed repeatedly. We present three snapshot algorithms The first one is based on the assumption of global time, if computes channel states using several schemes. Taking consistent cut for global time instant, we show that the algorithm is applicable for existing snapshot algorithms The second one is a real token passing based algorithm for non-FIFO asynchronous distributed systems Its message complexity of control messages is O(n). The last algorithm is the repeated version of the second one. Using this algorithm, processes can get consistent global states af their convenience concurrently.
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