In the recent years multimedia technology has emerged as a key technology, mainly because of its ability to represent information in disparate forms as a bit-stream. this enables everything from text to video and soun...
ISBN:
(纸本)3540440496
In the recent years multimedia technology has emerged as a key technology, mainly because of its ability to represent information in disparate forms as a bit-stream. this enables everything from text to video and sound to be stored, processed, and delivered in digital form. A great part of the current research community effort has emphasized the delivery of the data as an important issue of multimedia technology. However, the creation, processing, and management of multimedia forms are the issues most likely to dominate the scientific interest in the long run. the aim to deal with information coming from video, text, and sound will result in a data explosion. this requirement to store, process, and manage large data sets naturally leads to the consideration of programmable parallelprocessing systems as strong candidates in supporting and enabling multimedia technology. therefore, this fact taken together withthe inherent data parallelism in these data types makes multimedia computing a natural application area for parallel and distributed processing. In addition to this, the concepts developed for parallel and distributed algorithms are quite useful for the implementation of distributed multimedia systems and applications. thus, the adaptation of these methods for distributed multimedia systems is an interesting topic to be studied.
the proceedings contain 8 papers. the topics discussed include: a block-oriented, parallel and collective approach to sparse indefinite preconditioning on GPUs;software prefetching for unstructured mesh applications;t...
ISBN:
(纸本)9781728101866
the proceedings contain 8 papers. the topics discussed include: a block-oriented, parallel and collective approach to sparse indefinite preconditioning on GPUs;software prefetching for unstructured mesh applications;there are trillions of little forks in the road. choose wisely! - estimating the cost and likelihood of success of constrained walks to optimize a graph pruning pipeline;scale-free graph processing on a NUMA machine;a fast and simple approach to merge and merge sort using wide vector instructions;impact of traditional sparse optimizations on a migratory thread architecture;mix-and-match: a model-driven runtime optimization strategy for BFS on GPUs;and high-performance GPU implementation of PageRank with reduced precision based on mantissa segmentation.
In order to facilitate efficient query processing, the information contained in data warehouses is typically stored as a set of materialized views. Deciding which views to materialize represent a challenge in order to...
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ISBN:
(纸本)9783540695004
In order to facilitate efficient query processing, the information contained in data warehouses is typically stored as a set of materialized views. Deciding which views to materialize represent a challenge in order to minimize view maintenance and query processing costs. Some existing approaches are applicable only for small problems, which are far from reality. In this paper we introduce a new approach for materialized view selection using parallel Simulated Annealing (PSA) that selects views from an input Multiple View processing Plan (MVPP). With PSA, we are able to perform view selection on MVPPs having hundreds of queries and thousands of views. Also, in our experimental study we show that our method provides a significant improvement in the quality of the obtained set of materialized views over existing heuristic and sequential simulated annealing algorithms.
How to map IP cores onto NoC architectures is a significant issue (application mapping) in multi-core system design. Many mapping algorithms which aim at optimizing cost metrics(e.g. energy consumption) in the mapping...
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parallel computers provide an efficient and economical way to solve large-scale and/or time-constrained scientific, engineering, and industry problems. Consequently, there is a need to predict the performance order of...
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ISBN:
(纸本)9783540695004
parallel computers provide an efficient and economical way to solve large-scale and/or time-constrained scientific, engineering, and industry problems. Consequently, there is a need to predict the performance order of both deterministic and non-deterministic parallelalgorithms. the performance prediction of the traveling salesman problem (TSP) is a challenging problem because similar input data sets may cause significant variability in execution times. parallel performance of data-dependent algorithms depends on the problem size, the number of processors, and other parameters. Discovering the main other parameters is the real key to obtain a good estimation of performance order. this paper presents a novel methodology to the problem of predicting the performance of a parallel algorithm for solving the TSP. the entire process explores data in search of patterns and/or relationships detecting the main parameters that affect performance. then, it uses the measured values for this limited number of inputs to produce a multiple-linear-regression model. Finally, the regression equation allows for predicting how the algorithm will respond when given new input data sets. the preliminary experimental results are quite promising.
parallelalgorithms developed for CAD problems today suffer from three important drawbacks. first, they are machine specific and tend to perform poorly on architectures other than the one for which they were designed....
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ISBN:
(纸本)0818656026
parallelalgorithms developed for CAD problems today suffer from three important drawbacks. first, they are machine specific and tend to perform poorly on architectures other than the one for which they were designed. Second, they cannot use the latest advances in improved versions of the sequential algorithms for solving the problem. third, the quality of results degrade significantly during parallel execution. In this paper we address these three problems for an important CAD application: standard cell placement. We have developed a new parallel placement algorithm that is portable across a range of MIMD parallelarchitectures. the algorithm is part of the ProperCAD project which allows the development and implementation of a parallel algorithm such that it can be executed on a wide variety of parallel machines without any change to the source. the parallel placement algorithm is based on an existing implementation of the sequential simulated annealing algorithm, TimberWolfSC 6.0 [1].
Network packet processingarchitectures use heterogeneous processors as accelerators to speed-up classic application domain tasks. Our platform compiles applications to bytecodes for a generalized packet processing ma...
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ISBN:
(纸本)9781538694039
Network packet processingarchitectures use heterogeneous processors as accelerators to speed-up classic application domain tasks. Our platform compiles applications to bytecodes for a generalized packet processing machine, then uses microcoded interpreters running in parallel to trigger accelerators as needed. To make the system effective requires helping users debug apps, which includes tracking runtime exceptions. Exception tracking is complicated when a system-thrown exception is detected on an accelerator and the current binary form is far removed from the original high-level language source or associated assembly code. We tackle this problem by (1) instrumenting the compiler and a low-level bytecode tool, (2) reporting exceptions withthe interpreter, (3) creating a specialized tool to collate the higher-level program forms withthe lower-level bytecode forms. this functionality provides data needed for post-mortem program analysis.
An algorithm, which solves the cooperative concurrent computing tasks by using the idle cycle of a number of high performance heterogeneous workstations interconnected by a high-speed network, is proposed. In order to...
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ISBN:
(纸本)0769515126
An algorithm, which solves the cooperative concurrent computing tasks by using the idle cycle of a number of high performance heterogeneous workstations interconnected by a high-speed network, is proposed. In order to get better parallel computation performance, this paper gives a model and an algorithm of task scheduling among heterogeneous workstations, in which the costs of loading data, computing, communication and collecting results are considered. Using this efficient algorithm, an optimal subset of heterogeneous workstations withthe shortest parallel executing time of tasks can be selected.
Complex networks are a technique for the modeling and analysis of large data sets in many scientific and engineering disciplines. Due to their excessive size conventional algorithms and single core processors struggle...
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ISBN:
(纸本)9781479904945;9781479904938
Complex networks are a technique for the modeling and analysis of large data sets in many scientific and engineering disciplines. Due to their excessive size conventional algorithms and single core processors struggle withthe efficient processing of such networks. Employing multi-core graphic processing units (GPUs) could provide sufficient processing power for the analysis of such networks. However, commonly designed algorithms cannot exploit these massively parallelprocessing power for the analysis of such networks. In this paper, we present the Multi Layer Network Decomposition (MLND) approach which provides a general approach for parallel network analysis using multi-core processors via efficient partitioning and mapping of networks onto GPU architectures. Evaluation using a 336 core GPU graphic card demonstrated a 16x speed-up in complex network analysis relative to a CPU based approach.
Dynamic programming techniques are well-established and employed by various practical algorithms which are used as similarity measures, for instance the edit-distance algorithm or the dynamic time warping algorithm. T...
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ISBN:
(纸本)9783319250878;9783319250861
Dynamic programming techniques are well-established and employed by various practical algorithms which are used as similarity measures, for instance the edit-distance algorithm or the dynamic time warping algorithm. these algorithms usually operate in iteration-based fashion where new values are computed from values of the previous iteration, thus they cannot be processed by simple data-parallel approaches. In this paper, we propose a way how to utilize computational power of massively parallel GPUs to compute dynamic programming algorithms effectively and efficiently. We address boththe problem of computing one distance on large inputs concurrently and the problem of computing large number of distances simultaneously (e.g., when a similarity query is being resolved).
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