Mankind's demand for more powerful computing capabilities is never met, which has led to the continuous improvement of supercomputers' performance. A more powerful supercomputer tends to have a larger system s...
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Mankind's demand for more powerful computing capabilities is never met, which has led to the continuous improvement of supercomputers' performance. A more powerful supercomputer tends to have a larger system scale, which brings serious challenges to the system management, within which how to monitor the system's state is a critical problem. To address this problem, a scalable and flexible monitoring system framework for supercomputers is brought forward in this paper which can monitor supercomputers with tens of thousands of nodes effectively and efficiently. In this paper, we firstly give an overview of the framework and then focus on the Super Computer System Description Language(SCSDL) which is key to the framework. In the end, we explain some techniques about implementing the framework, and the client GUIs of a job monitoring system and an error monitoring system for Tianhe-2 based on this framework are given, from which we can see that the framework is well scalable and flexible to monitor Tianhe-2 which has 16,000 nodes effectively and efficiently.
Image annotation generates a set of semantic labels that describe the contents of an input *** deep learning techniques have achieved significant success in many areas of image *** this paper,we present a multi-label ...
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Image annotation generates a set of semantic labels that describe the contents of an input *** deep learning techniques have achieved significant success in many areas of image *** this paper,we present a multi-label image annotation method that combines unsupervised object hypotheses generation and deep neural *** an image,object hypotheses are generated in an unsupervised *** we extract the image features for each hypothesis with a deep neural network *** combining the features of all hypotheses,we get the features of the entire ***,we calculate for each label the probability of that the label is correlated with the given *** can be trained in an end-to-end way using the standard backward propagation *** results on multiple benchmark datasets show that our method is better than the state-of-the-art ones.
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 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.
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.
Image diffusion plays a fundamental role for the task of image denoising. Recently proposed trainable nonlinear reaction diffusion (TNRD) model defines a simple but very effective framework for image denoising. Howeve...
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In the Internet of Things, it is important to detect the various relations among objects for mining useful knowledge. Existing works on relation detection are based on centralized processing, which is not suitable for...
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In this paper, an improved algorithm is proposed for the reconstruction of singularity connectivity from the available pairwise connections during preprocessing phase. To evaluate the performance of our algorithm, an ...
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Bloom filters are frequently used to to check the membership of an item in a set. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. This dilemma is ...
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With the social networks getting increasingly larger, fast community detection algorithms like the label propagation algorithm, are attracting more attention. But the label propagation algorithm deals vertices with no...
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