This paper deals with the numerical determination of the stress and displacement distribution in a solid body subjected to the applied external force. The tackled solid mechanics problem is governed by the Navier-Cauc...
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We show that the problem of predicate detection in distributedsystems is NP-complete. We introduce a class of predicates, linear predicates, such that for any linear predicate B there exists an efficient detection of...
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This work deals with an optimization of a coupled transport problem, more precisely a thermo-fluid transport in a closed cavity. The considered natural convection problem is governed by energy and momentum transport c...
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ISBN:
(纸本)9789609999465
This work deals with an optimization of a coupled transport problem, more precisely a thermo-fluid transport in a closed cavity. The considered natural convection problem is governed by energy and momentum transport coupled with Boussinesq approximation. The governing equations are solved with a local explicit meshless method while the optimization is performed with Differential Evolutionary Multi objective Optimization (DEMO). The differentially heated cavity is partially covered with non-permeable obstacles that obstruct the natural convection flow. We seek the optimal position and shape of the obstacles to minimize the heat flux through the domain with the minimal cumulative size of the obstacles, i.e. we maximize insulation with minimal material needed. The results are presented in terms of velocity fields and temperature fields, and optimization Pareto fronts.
Fast, byte-addressable NVM promises near-cache latency and near memory bus throughput for file systems, which is evident by recent development of a number of NVM file systems (NVMFS). However, a key approach to measur...
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Recent in-memory database systems leverage advanced hardware features like RDMA to provide transaction processing at millions of transactions per second. distributed transaction processing systems can scale to even hi...
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Graph-structured analytics has been widely adopted in a number of big data applications such as social computation, web-search and recommendation systems. Though much prior research focuses on scaling graph-analytics ...
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ISBN:
(纸本)9781450332057
Graph-structured analytics has been widely adopted in a number of big data applications such as social computation, web-search and recommendation systems. Though much prior research focuses on scaling graph-analytics on distributed environments, the strong desire on performance per core, dollar and joule has generated considerable interests of processing large-scale graphs on a single server-class machine, which may have several terabytes of RAM and 80 or more cores. However, prior graph-analytics systems are largely neutral to NUMA characteristics and thus have suboptimal performance. This paper presents a detailed study of NUMA characteristics and their impact on the efficiency of graph-analytics. Our study uncovers two insights: 1) either random or interleaved allocation of graph data will significantly hamper data locality and parallelism;2) sequential inter-node (i.e., remote) memory accesses have much higher bandwidth than both intra- and inter-node random ones. Based on them, this paper describes Polymer, a NUMA-aware graph-analytics system on multicore with two key design decisions. First, Polymer differentially allocates and places topology data, application-defined data and mutable runtime states of a graph system according to their access patterns to minimize remote accesses. Second, for some remaining random accesses, Polymer carefully converts random remote accesses into sequential remote accesses, by using lightweight replication of vertices across NUMA nodes. To improve load balance and vertex convergence, Polymer is further built with a hierarchical barrier to boost parallelism and locality, an edge-oriented balanced partitioning for skewed graphs, and adaptive data structures according to the proportion of active vertices. A detailed evaluation on an 80-core machine shows that Polymer often outperforms the state-of-the-art single-machine graph-analytics systems, including Ligra, X-Stream and Galois, for a set of popular real-world and synthetic grap
Optimizing compilers perform various optimizations in order to exploit the best performance from computer systems. However, some kinds of optimizations cannot be applied if values of variables or system parameters are...
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We present a new approach to the problem of dependence-free partitioning of structured domains, also known as alignment. The proposed method is based on a unified description of data and dependence structures with the...
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The Mercury Monitoring System is a generic GMA-compatible grid monitoring framework. In this paper we present how higher level application monitoring and debugging facilities can be built on top of Mercury. Currently ...
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We analyze the scheduling aspects of database queries submitted to an abstract model of a very large distributed system. The essential elements of this model are: (a) a finite number of identical processing nodes with...
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