843 research outputs found

    A Black-box Monitoring Approach to Measure Microservices Runtime Performance

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    Microservices changed cloud computing by moving the applications' complexity from one monolithic executable to thousands of network interactions between small components. Given the increasing deployment sizes, the architectural exploitation challenges, and the impact on data-centers' power consumption, we need to efficiently track this complexity. Within this article, we propose a black-box monitoring approach to track microservices at scale, focusing on architectural metrics, power consumption, application performance, and network performance. The proposed approach is transparent w.r.t. the monitored applications, generates less overhead w.r.t. black-box approaches available in the state-of-the-art, and provides fine-grain accurate metrics

    Correlation functions of chiral primary operators in perturbative N = 4 SYM

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    We discuss recent results on two-point functions of chiral primary operatorsin {\cal N}=4 SU(N) supersymmetric Yang-Mills theory. Our results give furthersupport to the belief that such correlators are not renormalized to all ordersin g and to all orders in N

    Reconfigurable Computing and Hardware/Software Codesign

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    none3Article ID 731830 - EditorialPLAKS T. P; SANTAMBROGIO M. D; D. SCIUTOPLAKS T., P; Santambrogio, MARCO DOMENICO; Sciuto, Donatell

    Finite-size effects in the superconformal beta-deformed N=4 SYM

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    We study finite size effects for composite operators in the SU(2) sector of the superconformal beta-deformed N=4 SYM theory. In particular we concentrate on the spectrum of one single magnon. Since in this theory one-impurity states are non BPS we compute their anomalous dimensions including wrapping contributions up to four loops and discuss higher order effects.Comment: LaTeX, mpost, feynmf, 20 pages, 4 figures, 5 tables; v2: references added, equations (4.13) and (4.17) correcte

    Smartlocks: Self-Aware Synchronization through Lock Acquisition Scheduling

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    As multicore processors become increasingly prevalent, system complexity is skyrocketing. The advent of the asymmetric multicore compounds this -- it is no longer practical for an average programmer to balance the system constraints associated with today's multicores and worry about new problems like asymmetric partitioning and thread interference. Adaptive, or self-aware, computing has been proposed as one method to help application and system programmers confront this complexity. These systems take some of the burden off of programmers by monitoring themselves and optimizing or adapting to meet their goals. This paper introduces an open-source self-aware synchronization library for multicores and asymmetric multicores called Smartlocks. Smartlocks is a spin-lock library that adapts its internal implementation during execution using heuristics and machine learning to optimize toward a user-defined goal, which may relate to performance, power, or other problem-specific criteria. Smartlocks builds upon adaptation techniques from prior work like reactive locks, but introduces a novel form of adaptation designed for asymmetric multicores that we term lock acquisition scheduling. Lock acquisition scheduling is optimizing which waiter will get the lock next for the best long-term effect when multiple threads (or processes) are spinning for a lock. Our results demonstrate empirically that lock scheduling is important for asymmetric multicores and that Smartlocks significantly outperform conventional and reactive locks for asymmetries like dynamic variations in processor clock frequencies caused by thermal throttling events

    Using Speculative Computation and Parallelizing Techniques to Improve Scheduling of Control based Designs

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    partially_open5Recent research results have seen the application of parallelizing techniques to high-level synthesis. In particular, the effect of speculative code transformations on mixed control-data flow designs has demonstrated effective results on schedule lengths. In this paper we first analyze the use of the control and data dependence graph as an intermediate representation that provides the possibility of extracting the maximum parallelism. Then we analyze the scheduling problem by formulating an approach based on Integer Linear Programming (ILP) to minimize the number of control steps given the amount of resources. We improve the already proposed ILP scheduling approaches by introducing a new conditional resource sharing constraint which is then extended to the case of speculative computation. The ILP formulation has been solved by using a Branch and Cut framework which provides better results than standard branch and bound techniquesR. Cordone; F. Ferrandi; G. Palermo; M. Santambrogio; D. SciutoR., Cordone; Ferrandi, Fabrizio; Palermo, Gianluca; Santambrogio, MARCO DOMENICO; Sciuto, Donatell
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