We describe a high performance Grid based signal search tool for distributed diagnostic applications developed in conjunction with Rolls-Royce plc for civil aero engine condition monitoring applications. With the intr...
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ISBN:
(纸本)0769525857
We describe a high performance Grid based signal search tool for distributed diagnostic applications developed in conjunction with Rolls-Royce plc for civil aero engine condition monitoring applications. With the introduction of advanced monitoring technology into engineering systems, healthcare, etc., the associated diagnostic processes are increasingly required to handle and consider vast amounts of data. An exemplar of such a diagnosis process was developed during the DAME project, which built a proof of concept demonstrator to assist in the enhanced diagnosis and prognosis of aero-engine conditions. In particular it has shown the utility of an interactive viewing and high performance distributed search tool (the Signal Data Explorer) in the aero-engine diagnostic process. The viewing and search techniques are equally applicable to other domains. The Signal Data Explorer and search services have been demonstrated on the Worldwide Universities Network to search distributed databases of electrocardiograph data.
In large-scale distributed simulation systems, the primary goals of the data distribution management are to manage the distribution of state updates and interaction information, as well as to limit and control the vol...
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This paper presents a distributed file-system for the present day medium-sized network. Existing servers and workstations pool their unused storage resources to form a communal share. Erasure codes provide fault toler...
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This paper is the first to present a parallelization of a highly efficient best-first branch-and-bound algorithm to solve large symmetric traveling salesman problems on a massively parallel computer containing 1024 pr...
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This paper is the first to present a parallelization of a highly efficient best-first branch-and-bound algorithm to solve large symmetric traveling salesman problems on a massively parallel computer containing 1024 processors. The underlying sequential branch-and-bound algorithm is based on 1-tree relaxation. The parallelization of the branch-and-bound algorithm is fully distributed. Every processor performs the same sequential algorithm but on a different part of the solution tree. To distribute subproblems among the processors we use a new direct-neighbor dynamic load-balancing strategy. The general principle can be applied to all other branch-and-bound algorithms leading to an 'automatic' parallelization. At present we can efficiently solve traveling salesman problems up to a size of 318 cities on networks of up to 1024 transputers. On hard problems we achieve an almost linear speed-up.
In this paper, we analyze the reference signal stability of 1 PPS and 10 MHz signals provided by a low-cost GPS disciplined oscillator under application specific conditions using a comparable light-weight measurement ...
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ISBN:
(纸本)9781728164304
In this paper, we analyze the reference signal stability of 1 PPS and 10 MHz signals provided by a low-cost GPS disciplined oscillator under application specific conditions using a comparable light-weight measurement system based on software defined radio and digital signal processing. In mobile measurement scenarios, GPS signal impairments are inevitable, due to obstacles such as buildings, street canyons, bridges, and tunnels. Therefore, we preliminarily characterize four GPSDOs under test in a stationary setup using controlled GPS reception loss to drive them into alternating operation modes, namely free-run, disciplined and holdover mode. Further, we conducted a more than 100 km real-world diversified test drive to characterize the performance of the particular GPSDO as realistically as possible for the intended use in mobile V2X measurements.
MapReduce is a commonly used framework for parallelprocessing of data-intensive tasks, but its performance usually suffers from heavy communication load incurred by the shuffling of intermediate values (IVs) among co...
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ISBN:
(纸本)9781728190747
MapReduce is a commonly used framework for parallelprocessing of data-intensive tasks, but its performance usually suffers from heavy communication load incurred by the shuffling of intermediate values (IVs) among computing servers. Recently, the Coded MapReduce framework is proposed which uses a coding scheme named coded distributed computing (CDC) to trade the communication load with extra computation in MapReduce. CDC can achieve the optimal computation-communication tradeoff when all the IVs have the same size. However, in many practical applications, the sizes of IVs can vary over a large range, leading to inferior performance. In this paper, we introduce a generalized CDC scheme which takes the sizes of IVs into account and then propose a combinatorial optimization problem aiming to minimize the communication load when the computation load is fixed. We show that the problem is NP-hard, and further propose a very efficient algorithm which achieves an approximation ratio of 2. Experiments conducted on Alibaba Cloud show that, compared to the original CDC scheme, our proposed IV size aware approach can significantly reduce the communication load and achieve a lower total execution time.
This poster presentation describes our vision, goals and plans for HARNESS, a distributed reconfigurable and heterogeneous computing environment that supports dynamically adaptable parallelapplications. HARNESS build...
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ISBN:
(纸本)0818685794
This poster presentation describes our vision, goals and plans for HARNESS, a distributed reconfigurable and heterogeneous computing environment that supports dynamically adaptable parallelapplications. HARNESS builds on the core concept of the personal virtual machine as an abstraction for distributedparallel programming but fundamentally extends this idea, greatly enhancing dynamic capabilities. HARNESS is being designed to embrace dynamics at every level through a pluggable model that allows multiple distributed virtual machines (DVMs) to merge, split and interact with each other It provides mechanisms for new and legacy applications to collaborate with each other using the HARNESS infrastructure, and defines and implements new plug-in interfaces and modules so that applications can dynamically customize their virtual environment. HARNESS fits well within the larger picture of computational grids as a dynamic mechanism to hide the heterogeneity and complexity of the nationally distributed infrastructure. HARNESS DVMs allow programmers and users to construct personal subsets of an existing computational grid and treat them as unified network computers, providing a familiar and comfortable environment that provides easy-to-understand scoping. Similarly, a particular site could use HARNESS to construct a virtual machine that is presented and utilized as a single resource for scheduling within the grid. Our research focuses on understanding and developing three key capabilities within the framework of a heterogeneous computing environment: I) Techniques and methods for creating an environment where multiple distributed virtual machines can collaborate, merge or split;2) Specification and design of plug-in interfaces to allow dynamic extensions to services and functionality within a distributed virtual machine;and 3) Methodologies for distinct parallelapplications to discover each other;dynamically attach, collaborate, and cleanly detach.
A flexible biomedical visualization framework implemented with Java, OpenGL, and OpenCL performs efficient volume rendering with large, multi-modal datasets. The,framework takes advantage of the parallelprocessing po...
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ISBN:
(纸本)9781467320511
A flexible biomedical visualization framework implemented with Java, OpenGL, and OpenCL performs efficient volume rendering with large, multi-modal datasets. The,framework takes advantage of the parallelprocessing power on modern graphics hardware with novel Open CL and GLSL shading language implementations. The Java and GPU environment provide portable advanced biomedical image visualization applications. Several applications built on top of the GPU framework are also presented to show the extensibility of the application. These include multi-surface rendering, stereoscopic rendering, image fusion, and diffusion tensor visualization.
At present, saving energy consumption of modern processors and fault tolerance become major concerns due to the fact that high power consumption increases heat dissipation, which leads to decreased reliability of syst...
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ISBN:
(纸本)0769523129
At present, saving energy consumption of modern processors and fault tolerance become major concerns due to the fact that high power consumption increases heat dissipation, which leads to decreased reliability of systems. Similarly, the faults of running tasks also reduce the reliability of systems. The algorithms proposed in this paper are based on the policy of shortest-task-first and combined with other efficient techniques, such as shared slack reclamation and checkpoint. Consequently, not only real-time tasks can be completed before deadline, but also reduction of the global power consumption and fault-tolerance will be satisfied dynamically. In this paper, we present four algorithms to cope with scheduling independent task sets and task sets with precedence relationship in homogeneous and heterogeneous systems, respectively. Moreover, we present dynamic fault-tolerant algorithm. Compared to the efficient algorithms presented so far, our algorithms show lower communicational complexity and much better scheduling performance in terms of makespan and energy consumption.
In this paper, a new distributed algorithm is investigated for optimal routing problems of large data network with multicommodities. The existing algorithms for general network topology have parallel time complexity o...
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In this paper, a new distributed algorithm is investigated for optimal routing problems of large data network with multicommodities. The existing algorithms for general network topology have parallel time complexity of at least O(MΦ2) using all the nodes of the network as processors. Our algorithm takes O(mΦ2) time units using the same number of processors if some mild network conditions are met. Here, Φ is the diameter of the network;M is the number of commodities;m is a positive number usually much smaller than M and is a function of the pattern of all the OD pairs including the locations of each origin node and destination node, and the flow demand of each OD pair. The implementation of the algorithm for a 200-node network is simulated using OPNET simulation tool and the results show that our algorithm is much faster than the general algorithms.
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