Performance and energy consumption of high performance computing (HPC) interconnection networks have a great significance in the whole supercomputer, and building up HPC interconnection network simulation plat- form...
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Performance and energy consumption of high performance computing (HPC) interconnection networks have a great significance in the whole supercomputer, and building up HPC interconnection network simulation plat- form is very important for the research on HPC software and hardware technologies. To effectively evaluate the per- formance and energy consumption of HPC interconnection networks, this article designs and implements a detailed and clock-driven HPC interconnection network simulation plat- form, called HPC-NetSim. HPC-NetSim uses application- driven workloads and inherits the characteristics of the de- tailed and flexible cycle-accurate network simulator. Besides, it offers a large set of configurable network parameters in terms of topology and routing, and supports router's on/off states. We compare the simulated execution time with the real execution time of Tianhe-2 subsystem and the mean error is only 2.7%. In addition, we simulate the network behaviors with different network structures and low-power modes. The results are also consistent with the theoretical analyses.
On the 41st Top500 list announced in June 2013, the MilkyWay-2 system produced by National University of Defense technology (NUDT) in China won the first place with a LINPACK test result of 33.86 PFLOPS. It has been...
On the 41st Top500 list announced in June 2013, the MilkyWay-2 system produced by National University of Defense technology (NUDT) in China won the first place with a LINPACK test result of 33.86 PFLOPS. It has been one and a half year since its predecessor, MilkyWay-1 (TH-1), reached the same place for the first time. On the newest Top500 list published in November 2013, MilkyWay-2 continued to win the champion.
This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model ...
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The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elas- tic, manageable, and economical computing over...
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The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elas- tic, manageable, and economical computing over the cloud becomes high. Fast provisioning of large-scale virtual ma- chines (VMs), in particular, is critical to guarantee quality of service (QoS). In this paper, we systematically review the existing VM provisioning schemes and classify them in three main categories. We discuss the features and research status of each category, and introduce two recent solutions, VMThunder and VMThunder+, both of which can provision hundreds of VMs in seconds.
We consider the maximal vector problem on uncertain data, which has been recently posed by the study on processing skyline queries over a probabilistic data stream in the database context. Let D n be a set of n points...
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We consider the maximal vector problem on uncertain data, which has been recently posed by the study on processing skyline queries over a probabilistic data stream in the database context. Let D n be a set of n points in a d-dimensional space and q (0 < q 1) be a probability threshold; each point in D n has a probability to occur. Our problem is concerned with how to estimate the expected size of the probabilistic skyline, which consists of all the points that are not dominated by any other point in D n with a probability not less than q. We prove that the upper bound of the expected size is O(min{n, (- ln q)(ln n) d-1 }) under the assumptions that the value distribution on each dimension is independent and the values of the points along each dimension are distinct. The main idea of our proof is to find a recurrence about the expected size and solve it. Our results reveal the relationship between the probability threshold q and the expected size of the probabilistic skyline, and show that the upper bound is poly-logarithmic when q is not extremely small.
Feature-based image matching algorithms play an indispensable role in automatic target recognition (ATR). In this work, a fast image matching algorithm (FIMA) is proposed which utilizes the geometry feature of ext...
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Feature-based image matching algorithms play an indispensable role in automatic target recognition (ATR). In this work, a fast image matching algorithm (FIMA) is proposed which utilizes the geometry feature of extended centroid (EC) to build affine invariants. Based on at-fine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.
Script is the structured knowledge representation of prototypical real-life event *** the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensibl...
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Script is the structured knowledge representation of prototypical real-life event *** the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensible *** learning is an interesting and promising research direction,in which a trained script learning system can process narrative texts to capture script knowledge and draw ***,there are currently no survey articles on script learning,so we are providing this comprehensive survey to deeply investigate the standard framework and the major research topics on script *** research field contains three main topics:event representations,script learning models,and evaluation *** each topic,we systematically summarize and categorize the existing script learning systems,and carefully analyze and compare the advantages and disadvantages of the representative *** also discuss the current state of the research and possible future directions.
On virtualization platforms, peak memory de- mand caused by hotspot applications often triggers page swapping in guest OS, causing performance degradation in- side and outside of this virtual machine (VM). Even thou...
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On virtualization platforms, peak memory de- mand caused by hotspot applications often triggers page swapping in guest OS, causing performance degradation in- side and outside of this virtual machine (VM). Even though host holds sufficient memory pages, guest OS is unable to utilize free pages in host directly due to the semantic gap between virtual machine monitor (MM) and guest operat- ing system (OS). Our work aims at utilizing the free memory scattered in multiple hosts in a virtualization environment to improve the performance of guest swapping in a transparent and implicit way. Based on the insightful analysis of behav- ioral characteristics of guest swapping, we design and im- plement a distributed and scalable framework HybridSwap. It dynamically constructs virtual swap pools using various policies, and builds up a synthetic swapping mechanism in a peer-to-peer way, which can adaptively choose different vir- tual swap pools. We implement the prototype of HybridSwap and evaluate it with some benchmarks in different scenar- ios. The evaluation results demonstrate that our solution has the ability to promote the guest swapping efficiency indeed and shows a double performance promotion in some cases. Even in the worst case, the system overhead brought by Hy- bridSwap is acceptable.
Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effecti...
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Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.
Consistency and responsiveness are two important factors in providing the sense of reality in distributed Virtual Environment (DVE). However, it is not easy to optimize both aspects because of the trade-off between th...
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