Deep learning developed in the last decade and has been established as recent, modern and very promising technique with large potential to be successfully applied in various domains. Despite deep learning outperforms ...
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We present TaskTorrent, a lightweight distributed task-based runtime in C++.TaskTorrent uses a parametrized task graph to express the task DAG, and one-sided active messages to trigger remote tasks asynchronously. As ...
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CCS (Cluster Computing System) is coming to solve the problems of standard technology. Whose, objective is to improve the performance/power efficiency of a single processor for storing and mining the large data sets, ...
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ISBN:
(纸本)9781450376341
CCS (Cluster Computing System) is coming to solve the problems of standard technology. Whose, objective is to improve the performance/power efficiency of a single processor for storing and mining the large data sets, using the parallel programming to read and process the massive data sets on multiple disks and CPUs. The thing which makes these systems somewhat performant than the standard technology is the physical organization of computing nodes in the cluster. Currently, this kind of cluster does not entirely solve the problem because it comes with its challenges, which are Node failures, Computations, Network Bottleneck, and distributed programming. All these problems are coming when we are mining and storing the massive volume of data using cluster computing. To solve these challenges, Google invented a new Big Data framework of data processing called MapReduce, to manage large scale data processing across large clusters of commodity servers. The paper outlines the running of CCS and presents its challenges in this era of Big Data. Moreover, it introduces the most popular Big Data solutions proposed to overcome the CCS challenges. Also, it shows how Big Data technologies solve CCS issues. Generally, the main goal of this work is to provide a better understanding of the challenges of CCS and identify the essential big data solutions in this increasingly important area.
Logs record valuable system information at runtime. They are widely used by data-driven approaches for development and monitoring purposes. Parsing log messages to structure their format is a classic preliminary step ...
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ISBN:
(纸本)9781665423984
Logs record valuable system information at runtime. They are widely used by data-driven approaches for development and monitoring purposes. Parsing log messages to structure their format is a classic preliminary step for log-mining tasks. As they appear upstream, parsing operations can become a processing time bottleneck for downstream applications. The quality of parsing also has a direct influence on their efficiency. Previous approaches toward online log parsing focused on stateful methods. But an increasing number of tasks ask for real time monitoring. Regarding this problem, we propose USTEP, an online log parsing method based on an evolving tree structure. Evaluation results on a panel of 13 datasets coming from different real-world systems demonstrate USTEP superiority in terms of both effectiveness and robustness when compared to other online methods. We also introduce USTEP-UP, a way of running multiple decentralized instances of USTEP in parallel.
Actor languages decouple communication from synchronization, which makes them suitable for distributed and scalable applications with flexible synchronization patterns, but also facilitates analysis. ABS is a timed ac...
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ISBN:
(纸本)9783030781415;9783030781422
Actor languages decouple communication from synchronization, which makes them suitable for distributed and scalable applications with flexible synchronization patterns, but also facilitates analysis. ABS is a timed actor-based modeling language which supports cooperative scheduling and the specification of timing- and resource-sensitive behavior. Cooperative scheduling allows a process which is executing in an actor to be suspended while it is waiting for an event to occur, such that another process in the same actor can execute. Timed semantics allows the specification of the temporal behavior of the modeled system. Resource-sensitive behavior takes a supply and demand perspective of execution, relating cost centers which provision resources to processes which require them. These modeling concepts have been used in ABS to model cloud computing, e.g., data-processingapplications running on the Hadoop platform and microservices running on containers orchestrated by Kubernetes. In this tutorial, we present ABS and its execution environment, and discuss the use of cooperative scheduling and resources in modeling cyber-physical systems and applications deployed on virtualized infrastructure.
When using the compressed sensing method in Synthetic Aperture Radar(SAR) imaging, there are two major problems: long calculation time and insufficient scalability of t calculation ability. In order to solve the above...
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At present, parallel fuzzing mainly has the following two problems. The first is that parallelization is mainly aimed at single-machine with multi-core situation, and there is no test case generation method suitable f...
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Apache Storm is a scalable fault-tolerant distributed real-time stream-processing framework widely used in big data applications. For distributed data-sensitive applications, low-latency, high-throughput communication...
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The weather nowadays has become so unpredictable that there is a need for a system that predicts correct weather patterns and allows them to take a precautionary plan of action to cope up with it. Three major sources ...
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The proceedings contain 94 papers. The topics discussed include: design of high torque variable stiffness actuator with fast adjustment and wide range of stiffness using lever and parallel mechanism;analyzing the effe...
ISBN:
(纸本)9781728165707
The proceedings contain 94 papers. The topics discussed include: design of high torque variable stiffness actuator with fast adjustment and wide range of stiffness using lever and parallel mechanism;analyzing the effect of soft arm design on obstacle navigation through collision;the quad-spatula gripper: a novel soft-rigid gripper for food handling;soft robotic module for sensing and controlling contact force;sensorized phantom for characterizing large area deformation of soft bodies for medical applications;soft thermal actuators with embedded liquid metal microdroplets for improved heat management;mixing state estimation of peristaltic continuous mixing conveyor with distributed sensing system based on soft intestine motion;feedback control of a soft swinging appendage;and towards vision-based robotic skins: a data-driven, multi-camera tactile sensor.
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