A broad overview of gigabit local area networks (LANs) is presented from a systems perspective. Motivations and technical goals of gigabit LANs and challenges of coping with highly bursty traffic and large bandwidth m...
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A broad overview of gigabit local area networks (LANs) is presented from a systems perspective. Motivations and technical goals of gigabit LANs and challenges of coping with highly bursty traffic and large bandwidth mismatches between network links are described. The focus is on concerns unique to gigabit LANs, especially issues that differentiate them from gigabit wide area networks (WANs), metropolitan area networks (MANs), and lower-speed LANs. Major systems issues are discussed, and possible solutions, such as the virtual-connection architecture, are presented. The hardware technology required by gigabit LANs is illustrated by SONET components.< >
We consider a generalisation of the multiple sc cess problem where it is necessary to identify a subset of the ready users, not all. The problem is motivated by several ''response collection'' applicat...
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We consider a generalisation of the multiple sc cess problem where it is necessary to identify a subset of the ready users, not all. The problem is motivated by several ''response collection'' applications that arise in distributed computing and database systems. In these applications, a collector is interested in gathering a set of responses from a number of potential respondents. The collector and respondents communicate over a shared channel. We define three collection objectives and investigate a suite of protocols that can be used to achieve these objectives. The protocols are based on the use of Polling, TDMA, and Group Testing. Using a binomial respondent model we analyse and, where applicable, optimise the performance of the protocols. Our concern is with cost measures that reflect the computational load placed on the system, as well as the delay incurred for achieving a particular objective.
The blocking phenomena in two-phase commit (2PC) reduces the availability of the system as the blocked transactions keep all the resources until the recovery of the coordinator. The three-phase commit (3PC) protocol i...
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The blocking phenomena in two-phase commit (2PC) reduces the availability of the system as the blocked transactions keep all the resources until the recovery of the coordinator. The three-phase commit (3PC) protocol involves an extra round of message transmission to resolve the blocking problem. In this paper, we propose a backup commit (BC) protocol to reduce the blocking problem by attaching multiple backup sites to the coordinator site. In BC, after receiving responses from the participants, the coordinator quickly communicates the final decision to the backup sites, before it sends the final decision to the participants. When blocking occurs, the participant sites can terminate the transaction by consulting a backup site of the coordinator. The BC protocol resolves the blocking in most of the coordinator site failures without involving an expensive communication cycle as in 3PC. The simulation experiments indicate that the throughput performance of BC is close to 2PC. (C) 2002 Elsevier Science B.V. All rights reserved.
Routing is a very time-consuming stage in the FPGA design flow, significantly hindering the productivity. This article proposes CPRS, a coarse-grained parallel routing scheme in a distributed computing environment. Fi...
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Routing is a very time-consuming stage in the FPGA design flow, significantly hindering the productivity. This article proposes CPRS, a coarse-grained parallel routing scheme in a distributed computing environment. First, we partition entire routing region to guide the assignment of nets for parallel processing. The partitioning is a recursive fashion, and at each recursive partitioning, the region is partitioned into two subregions forming three subsets of nets. The first subset consists of potentially dependent nets and they are distributed in different subregions. The remaining two subsets consist of potentially independent nets and they are distributed in their own subregions. Second, we route the nets of first subset in serial and process the remaining two subsets in parallel. The parallel processing is a coarse-grained fashion, which is implemented by MPI parallel programming model. Finally, we explore the optimization of both partitioning and parallel processing to further improve the overall speedup of parallel routing. In addition, we adopt MPI message to synchronize the intermediate results between different cores in parallel routing for a feasible solution. Experiments use a set of commonly used benchmarks to demonstrate the effectiveness of CPRS. Notably, CPRS achieves about 18x speedup on average using 32 processor cores with minor loss of quality, compared with the VTR 7.0 serial router. There is about 1.6x improvement over the state-of-the-art parallel router.
Software developers can gain insight into software-hardware interactions by decomposing processor performance into individual cycles-per-instruction components that differentiate cycles consumed in active computation ...
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Software developers can gain insight into software-hardware interactions by decomposing processor performance into individual cycles-per-instruction components that differentiate cycles consumed in active computation from those spent handling various miss events. Constructing accurate CPI components for out-of-order superscalar processors is complicated, however, because computation and miss event handling overlap. The authors' counter architecture, using an analytical superscalar performance model, handles overlap effects more accurately than existing methods.
This paper presents a new opportunistic scheduling and resource consolidation system based on an economic model related to different service level agreements (SLAs) classes. The goal is to address the problem of compa...
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This paper presents a new opportunistic scheduling and resource consolidation system based on an economic model related to different service level agreements (SLAs) classes. The goal is to address the problem of companies that manage a private infrastructure of machines, i.e., a cloud platform and would like to optimize the scheduling of several requests submitted online by users. For the sake of simplicity of the presentation, the proposed economic model has two SLAs classes (qualitative and quantitative) with three Quality of Service for each SLA class (Premium, Advanced and Best effort). The consequence of this choice as well as the need to serve requests as they come have an impact on the algorithmic ways to consolidate an infrastructure. Indeed, our system proposes a new allocation heuristic that adapts the number of active machines in the cloud according to the global resources usage of all machines inside the infrastructure. This heuristic can be examined as a consolidation heuristic, based on the idea that the system can make reasonable choices, based on the SLAs, for the placement and the allocation of resources for each request. Experimentation with our system is conducted on Prezi (Web workload) and Google Cloud Data (HPC-oriented workload) traces, and they demonstrate the potential of our approach under different scenarios. From a methodological point of view, we propose a general framework which is limited in scope, for the sake of simplicity in reading the paper, with a small number of SLAs, but the idea can be extended to many more SLAs and performance metrics. In this way, the user or the provider operating the cloud have more latitude, thanks to our multi-criteria approach, to control the workload without a sacrifice on performance.
A technique is presented for segmented attenuation correction in positron emission tomography (PET) based on the local thresholding technique (LTS) described previously. To accommodate the substantially different body...
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A technique is presented for segmented attenuation correction in positron emission tomography (PET) based on the local thresholding technique (LTS) described previously. To accommodate the substantially different body sections encountered in whole-body PET, an adaptive thresholding has been added to yield more uniform results throughout the body. By evaluating the intensity distribution of a set of transverse transmission images, the algorithm determines an optimal threshold for separating two or three different groups or classes of similar pixels. Interclass variance is maximized and intra-class errors are minimized. The algorithm also switches automatically between a three-class mode (background, lungs/air pockets, soft tissue) and a two-class mode (background, soft tissue), thereby achieving more uniform segmentation where lung spaces and bowel air pockets are alternately present then absent from the volume of interest. The addition of adaptive thresholding virtually eliminates the need for operator intervention. The clinical implementation requires short-duration, count-limited, transmission images that would otherwise be too noisy for direct attenuation correction, Emission images corrected with adaptive LTS were shown to be equivalent, both quantitatively and qualitatively, to those corrected using conventional measured attenuation correction.
Formalized study of self-assembly has led to the definition of the tile assembly model, Previously I presented ways to compute arithmetic functions, such as addition and multiplication, in the tile assembly model: a h...
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Formalized study of self-assembly has led to the definition of the tile assembly model, Previously I presented ways to compute arithmetic functions, such as addition and multiplication, in the tile assembly model: a highly distributed parallel model of computation that may be implemented using molecules or a large computer network such as the Internet. Here, I present tile assembly model systems that factor numbers nondeterministically using e(l) distinct components. The computation takes advantage of nondeterminism, but theoretically, each of the nondeterministic paths is executed in parallel, yielding the solution in time linear in the size of the input, with high probability. I describe mechanisms for finding the successful solutions among the many parallel executions and explore bounds on the probability of such a nondeterministic system succeeding and prove that the probability can be made arbitrarily close to 1. (C) 2007 Elsevier B.V. All rights reserved.
E -governance is capable of driving the transition of government from an administrative power allocation of public resources to a citizen -service -oriented governance model. However, during this transformation, vario...
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E -governance is capable of driving the transition of government from an administrative power allocation of public resources to a citizen -service -oriented governance model. However, during this transformation, various governmental bodies often face the challenge of "data silos" caused by factors such as cross -regional, cross -business, and cross -departmental operations. Without altering the existing information platforms, transparent access technology serves as a key solution for data access within egovernance systems. It enables convenient access to information resources stored in different mediums and formats, facilitating the sharing and consolidation of information and data within and between governmental departments, thereby addressing the issue of "data silos" and enhancing the comprehensive service capabilities of e -governance. This paper firstly provides an overview of the concept, levels, characteristics, and application scenarios of transparent access to government big data. Secondly, it conducts a comprehensive comparative analysis of transparent access technologies in the context of cloud computing and big data. Lastly, based on the requirements of various transparent access technologies and the application of transparent access to government big data, this paper proposes a visionary framework for transparent access to government big data based on cross -domain semantics and channel coupling. This framework includes modules for cross -domain semantic interoperability, coupling of heterogeneous information channels based on knowledge graph, and tracing of multi -source heterogeneous data, aiming to provide innovative solutions for achieving transparent access to government big data.
Next-generation scientific applications require the capability to visualize large archival data sets or on-going computer simulations of physical and other phenomena over wide-area network connections. To minimize the...
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Next-generation scientific applications require the capability to visualize large archival data sets or on-going computer simulations of physical and other phenomena over wide-area network connections. To minimize the latency in interactive visualizations across wide-area networks, we propose an approach that adaptively decomposes and maps the visualization pipeline onto a set of strategically selected network nodes. This scheme is realized by grouping the modules that implement visualization and networking subtasks and mapping them onto computing nodes with possibly disparate computing capabilities and network connections. Using estimates for communication and processing times of subtasks, we present a polynomial-time algorithm to compute a decomposition and mapping to achieve minimum end-to-end delay of the visualization pipeline. We present experimental results using geographically distributed deployments to demonstrate the effectiveness of this method in visualizing data sets from three application domains.
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