Porting large applications to distributed computing platforms is a challenging task from a software engineering perspective. The Computational Grid has gained tremendous popularity as it aggregates unprecedented amoun...
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ISBN:
(纸本)9780769515823
Porting large applications to distributed computing platforms is a challenging task from a software engineering perspective. The Computational Grid has gained tremendous popularity as it aggregates unprecedented amounts of compute and storage resources by means of increasingly high performance network technology. The primary aim of this paper is to demonstrate how the development time to port very large applications to this environment can be significantly reduced. TOP-C and AMPIC are software packages that have each seen successful application in their respective domains of parallel computing and process creation/communication. We combine them to implement and deploy a master-worker model of parallel computing over the Computational Grid. To demonstrate the benefit of our approach, we ported the 1,000,000 line Geant4 sequential code in three man-weeks by using our TOP-C/AMPIC integration. This paper evaluates the benefits of our approach from a software engineering perspective, and presents experimental results obtained with the new implementation of Geant4 on a Grid testbed.
Some important issues in engineering the requirements of a distributed software system and methods that facilitate software system design for distributed or parallel implementations are discussed. The issues are prese...
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Some important issues in engineering the requirements of a distributed software system and methods that facilitate software system design for distributed or parallel implementations are discussed. The issues are presented from a knowledge engineering perspective and are divided into four levels: acquisition; representation; structuring; and design. The acquisition level entails the methods for eliciting system requirements data (attributes and relationships of software entities) from the end-user group using a model of context classes. The representation level deals with the language paradigm for representing the attributes and relationships of the software entities. The structuring level addresses methods for rearranging and grouping the software objects of the context classes into related clusters. The design level deals with methods for mapping or transforming the clusters of software objects into specification modules to facilitate distributed design. To this end, the design level uses an object-based paradigm for specifying the attributes and abstract behavior of the objects within the modules.< >
Large graphs analytics has been an important aspect of many big data applications, such as web search, social networks and recommendation systems. Many research focuses on processing large scale graphs using distribut...
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ISBN:
(纸本)9781509042982
Large graphs analytics has been an important aspect of many big data applications, such as web search, social networks and recommendation systems. Many research focuses on processing large scale graphs using distributed system over past few years. And numbers of studies turn to construct graph processing system on a single server-class machine in consideration of cost, usability and maintainability. HPGraph is a high parallel graph processing system which adopts the edge-centric model, our contributions are as follows: (1) designing an efficient data allocation and access strategy for NUMA machine, and providing tasks scheduling to keep load balance, (2) raising a fine-grained edge-block filtering mechanism to avoid accessing unnecessary edge data, (3) constructing a high-speed flash array as the second storage. We made a detailed evaluation on a 16-core machine using asset of popular real word and synthetic data sets, and the results show that HPGraph always outperforms the state-of-the-art single machine graph processing systems-GridGraph. And HPGraph can achieve 1.27X faster than GridGraph for specific application. Our source code is available at https://***/xinghuan1990/HPGraph.
The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) s...
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The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently.
Software pipelining is an instruction-level loop scheduling method for achieving high performance fine-grain parallelism on VLIW (very long instruction word) processors. This paper presents a novel software pipelining...
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ISBN:
(纸本)9539676940
Software pipelining is an instruction-level loop scheduling method for achieving high performance fine-grain parallelism on VLIW (very long instruction word) processors. This paper presents a novel software pipelining method for non-pipelining parallel processors based on integer scaling and retiming transformations. This approach generalises and simplifies the analogous extended retiming model of T.W. O'Neil et al. (see Proc. ISCA 12th Int. Conf. parallel & distributed Computing Syst., p.292-7, 1999; Proc. of ICASSP'99 Conf., vol.4 p.2001-4, 1999). Matrix techniques are used in order to simplify the corresponding graph transformations. Some general properties taken from algebraic graph theory are applied in order to obtain general scheduling techniques: node and cycle methods. The two-phase scheduling method considered is first defined by means of two standard linear programming problems. We transform the corresponding problems into some variants of the maximum cost-to-time ratio problem and shortest path problem, in order to obtain efficient polynomial time algorithms. An example of software pipelining optimization of a digital correlator is also given.
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