The proceedings contains 32 papers. Topics discussed include algorithms for parallelization, distributed computer systems and networking, software tools and environments, parallel finite and boundary elements, applica...
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The proceedings contains 32 papers. Topics discussed include algorithms for parallelization, distributed computer systems and networking, software tools and environments, parallel finite and boundary elements, applications in fluid flour and applications in applied science.
In the last decade, Graphics Processing Units(GPUs) have gained an increasing popularity as accelerators for High Performance computing (HPC) applications. Recent GPUs are not only powerful graphics engines but also h...
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computing routing schemes that support both high throughput and low latency is one of the core challenges of network optimization. Such routes can be formalized as h-length flows which are defined as flows whose flow ...
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ISBN:
(纸本)9781450399135
computing routing schemes that support both high throughput and low latency is one of the core challenges of network optimization. Such routes can be formalized as h-length flows which are defined as flows whose flow paths have length at most h. Many well-studied algorithmic primitives-such as maximal and maximum length-constrained disjoint paths-are special cases of h-length flows. Likewise the optimal h-length flow is a fundamental quantity in network optimization, characterizing, up to poly-log factors, how quickly a network can accomplish numerous distributed primitives. In this work, we give the first efficient algorithms for computing (1 - epsilon)-approximate h-length flows that are nearly "as integral as possible." We give deterministic algorithms that take (O) over tilde (poly(h, 1/epsilon)) parallel time and (O) over tilde (poly(h, 1/epsilon) center dot 2(O) (root log n)) distributed CONGEST time. We also give a CONGEST algorithm that succeeds with high probability and only takes (O) over tilde (poly(h, 1/epsilon)) time. Using our h-length flow algorithms, we give the first efficient deterministic CONGEST algorithms for the maximal disjoint paths problem with length constraints-settling an open question of Chang and Saranurak (FOCS 2020)-as well as essentially-optimal parallel and distributed approximation algorithms for maximum length-constrained disjoint paths. The former greatly simplifies deterministic CONGEST algorithms for computing expander decompositions. We also use our techniques to give the first efficient and deterministic (1-epsilon)-approximation algorithms for bipartite b-matching in CONGEST. Lastly, using our flow algorithms, we give the first algorithms to efficiently compute h-length cutmatches, an object at the heart of recent advances in length-constrained expander decompositions.
The authors describe a new class of name and resource management facility - a trading service - which allows users of a heterogeneous large distributed system to share resources and services (resources) which are not ...
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The recent advances in mobile computing and distributed multimedia systems allow mobile hosts (clients) to access wireless multimedia systems anywhere and at anytime, but not without creating a new set of issues and t...
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computing workload distribution is indispensable for resource sharing, cycle stealing and other modes of interaction in distributed systems/Grids. Computations should be arranged to adapt the capacity variation of sys...
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ISBN:
(纸本)9783642016707
computing workload distribution is indispensable for resource sharing, cycle stealing and other modes of interaction in distributed systems/Grids. Computations should be arranged to adapt the capacity variation of system resources. Although computation migration is the essential mechanism to move computing tasks around, the decision making of which task should be relocated is even more critical, especially when multithreaded parallel programs are involved. Multiple threads might be treated as partial workload and moved together. Based on thread similarity, this paper proposes a novel Multiresolution Thread Grouping algorithm (MTG) to classify threads into hierarchical Thread Bundles (TB) some of which can be picked by Multiresolution Thread Selection scheme (MTS) for load distribution. During the process of MTG, global variables are reorded so that one-time migration cost and post-migration communication volume and frequency can be reduced. Experimental results demonstrate the effectiveness of NITS for parallel workload distribution.
The ubiquity of mobile devices coupled with the advances in Internet of Things (IoT) technologies has led to the development of large-scale applications that can collect information about people and their environments...
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ISBN:
(纸本)9780769557854
The ubiquity of mobile devices coupled with the advances in Internet of Things (IoT) technologies has led to the development of large-scale applications that can collect information about people and their environments in real-time. Such applications are referred to as Mobile Crowdsensing (MCS). In MCS, tasks are allocated to participants (mobile devices) by a remote server according to the application requirements. The key challenge is reducing the energy consumption of the participating mobile devices. One of the effective approaches to reduce energy consumption of MCS applications is to improve efficiency of task allocation. An efficient task allocation approach can optimize several aspects of MCS applications such as task coverage (minimum number of participants required for a MCS task), data quality, and sensing costs. In this paper, we propose a novel Context-Aware Task Allocation (CATA) approach that aims to allocate sensing tasks to the best participant set while improving energy efficiency in MCS applications. Another important feature of the proposed CATA approach is that it preserves the privacy of participants' by only disclosing the less sensitive data to the server. The proposed approach employs local and global task allocation methods to enable two levels of data sharing and privacy. We describe the series of experiments that were conducted to validate our proposed approach in terms of coverage and efficiency.
Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of c...
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ISBN:
(纸本)9780769527840
Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of components, have-encouraged the development of grid computing. To exploit the promising potentials of geographically distributed resources, effective and efficient mapping algorithms are fundamental. Since the problem of optimally mapping is NP-complete, the development of evolutionary techniques to find near-optimal solutions is welcome. In this paper a distributed system based on Differential Evolution is designed and implemented to face the mapping problem in a gild environment aiming at reducing the degree of use of the grid resources. This system is tested on some different resource allocation scenarios.
This book constitutes the refereed proceedings of the 25th International Conference onparallel and distributedcomputing, Applications and Technologies, PDCAT 2024, held in Hong Kong, China, during December 14–16, 20...
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ISBN:
(数字)9789819642076
ISBN:
(纸本)9789819642069
This book constitutes the refereed proceedings of the 25th International Conference on
parallel and distributedcomputing, Applications and Technologies
, PDCAT 2024, held in Hong Kong, China, during December 14–16, 2024.
The 47 full papers and 8 short papers included in this book were carefully reviewed and selected from
114
submissions. They focus on advances in parallel and distributedcomputing, including parallel architectures, algorithms, and programming techniques.
Process of improving the performance of a parallel and distributed system through a redistribution of load among the processors is called load balancing. If it is being done at run time then it treats as dynamic load ...
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ISBN:
(纸本)9781605583518
Process of improving the performance of a parallel and distributed system through a redistribution of load among the processors is called load balancing. If it is being done at run time then it treats as dynamic load balancing. In this paper we present the framework for obtaining a user optimal load balancing scheme in distributed system. We formulate the Dynamic load balancing problem in distributed systems as a noncooperative game among users. The system model considers various parameters and accordingly the load balancing algorithm is defined. For the proposed noncooperative load balancing game, we consider the structure of the Nash equilibrium. Based on this structure we derive a new distributed load balancing algorithm. Our focus is to define the load balancing problem and the scheme to overcome it, by using new area called game theory. Copyright 2009 ACM.
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