In large-scale cloud computing systems, the growing scale and complexity of component interactions pose great challenges for operators to understand the characteristics of system performance. Performance profiling has...
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In large-scale cloud computing systems, the growing scale and complexity of component interactions pose great challenges for operators to understand the characteristics of system performance. Performance profiling has long been proved to be an effective approach to performance analysis; however, existing approaches do not consider two new requirements that emerge in cloud computing systems. First, the efficiency of the profiling becomes of critical concern; second, visual analytics should be utilized to make profiling results more readable. To address the above two issues, in this paper, we present P-Tracer, an online performance profiling approach specifically tailored for large-scale cloud computing systems. P-Tracer constructs a specific search engine that adopts a proactive way to process performance logs and generates particular indices for fast queries; furthermore, PTracer provides users with a suite of web-based interfaces to query statistical information of all kinds of services, which helps them quickly and intuitively understand system behavior. The approach has been successfully applied in Alibaba Cloud Computing Inc. to conduct online performance profiling both in production clusters and test clusters. Experience with one real-world case demonstrates that P-Tracer can effectively and efficiently help users conduct performance profiling and localize the primary causes of performance anomalies.
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.
Following current IC design technology trend, modern GPUs integrate more and more processing cores, and the speed gap between processor and memory system becomes even larger. As the number of cores continually increas...
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Real-time H.264 encoding of high-definition (HD) video (up to 1080p) is a challenge workload to most existing programmable processors. Instead, the novel programmable parallel processors such as stream processor, Grap...
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Heterogeneous parallel systems have become popular in general purpose computing and even high performance computing fields. There are many studies focused on harnessing heterogeneous parallelprocessing for better per...
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The reliability issue of Exascale system is extremely serious. Traditional passive fault-tolerant methods, such as rollback-recovery, can not fully guarantee system reliability any more because of their large executin...
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Satisfiability Modulo Theories (SMT) is an extension of SAT towards FOL. SMT solvers have proven highly scalable and efficient for problems based on some ground theorems. However, SMT problems involving quantifiers an...
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This work explores the feasibility to implement IEEE-754-2008 standard quadruple precision (Quad) elementary functions on recent FPGAs with plenty of embedded memories and DSP blocks. First, we analysis the implementa...
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Multi-island single electron transistor is an important kind of the single electron transistor, which is convenient to realize the controllable room temperature operation. A novel semi-empirical compact model for the ...
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ISBN:
(纸本)9781424435449
Multi-island single electron transistor is an important kind of the single electron transistor, which is convenient to realize the controllable room temperature operation. A novel semi-empirical compact model for the Multi-island single electron transistor is proposed. The new approach combines the orthodox theory of the single electron tunneling through single coulomb island and a novel empirical analysis procedure for the chain of multi coulomb islands to solve the current of the whole multi-island single electron transistor. The tunneling rates are calculated based on the orthodox theory for the single electron tunneling. The tunneling currents representing the first splitted peaks in the coulomb oscillation curves are calculated according to the assumption that the currents through all the coulomb islands are equal to each other at the stable states, while the currents representing the other splitted peaks are constructed and merged together according to the empirical analysis. The model is verified by the traditional SET simulator SIMON and shows much faster calculation speed than SIMON. Therefore, the novel compact model is suitable for the large scale MISET circuit simulation.
As the energy consumption becomes increasingly prominent, how to meet time constraints while reducing the energy consumption as much as possible is a fundamental problem of the real-time scheduling in multi-core syste...
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