Výsledky vyhľadávania - Many Task Computing

On the role of message broker middleware for many-task computing on a big-data platform Autor Nguyen, Cao Ngoc, Lee, Jaehwan, Hwang, Soonwook, Kim, Jik-Soo

“…We have designed and implemented a new data processing framework called “Many-task computing On HAdoop” (MOHA…”
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Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing Autor Iosup, A, Ostermann, S, Yigitbasi, M N, Prodan, R, Fahringer, T, Epema, D H J

“…Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike…”
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Asymptotic scheduling for many task computing in Big Data platforms Autor Sfrent, Andrei, Pop, Florin

“… Large scale computing solutions are increasingly used for genome sequencing tasks in the Human Genome Project…”
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Developing political-ecological theory: The need for many-task computing Autor Haas, Timothy

“… To meet this statistical and computational challenge, this article delivers statistical algorithms and a method for constructing ecosystem management plans that are coded as distributed computing applications…”
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Multi-core versus many-core computing for many-task Branch-and-Bound applied to big optimization problems Autor Melab, N., Gmys, J., Mezmaz, M., Tuyttens, D.

“…On the road to exascale, coprocessors are increasingly becoming key building blocks of High Performance Computing platforms…”
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Efficient Task Scheduling for Many Task Computing with Resource Attribute Selection Autor Zhao, Yong, Chen, Liang, Li, Youfu, Tian, Wenhong

“…Many Task Computing（MTC）is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely…”
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Load-balanced and locality-aware scheduling for data-intensive workloads at extreme scales Autor Wang, Ke, Qiao, Kan, Sadooghi, Iman, Zhou, Xiaobing, Li, Tonglin, Lang, Michael, Raicu, Ioan

“…Summary Data‐driven programming models such as many‐task computing (MTC) have been prevalent for running data…”
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Towards effective scheduling policies for many‐task applications: Practice and experience based on HTCaaS Autor Kim, Jik‐Soo, Quang, Bui, Rho, Seungwoo, Kim, Seoyoung, Kim, Sangwan, Breton, Vincent, Hwang, Soonwook

“…Summary In this paper, we conduct a comparative study of relatively simple yet effective scheduling policies for many…”
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Dynamic DAG scheduling for many-task computing of distributed eco-hydrological model Autor Yue, Shasha, Ma, Yan, Chen, Lajiao, Wang, Yuzhu, Song, Weijing

“… Based on many-task computing, we proposed a parallel scheme that the whole computing of the distributed hydrological model is split into tremendous amount of small sub-tasks which are directly…”
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Efficient algorithms for frequent pattern mining in many-task computing environments Autor Lin, Kawuu W., Lo, Yu-Chin

“… However, most studies have focused on improving the performance for a single task and have neglected the many-task computing issue, which is important in the current cloud-computing environments…”
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Parameter Exploration in Science and Engineering Using Many-Task Computing Autor Abramson, D, Bethwaite, B, Enticott, C, Garic, S, Peachey, T

“… Many-Task Computing (MTC) provides a framework for performing robust design, because it supports the execution of a large number of otherwise independent processes…”
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Many-to-many matching based task allocation for dispersed computing Autor Hui, Hongwen, Lin, Fuhong, Meng, Lei, Yang, Lei, Zhou, Xianwei

“…Dispersed computing is a new resource-centric computing paradigm, which makes use of idle resources in the network to complete the tasks…”
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A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing Autor Dengpan Yin, Yildirim, E, Kulasekaran, S, Ross, B, Kosar, T

“…In this paper, we present the design and implementation of an application-layer data throughput prediction and optimization service for many-task computing in widely distributed environments…”
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A Hybrid Scheduler for Many Task Computing in Big Data Systems Autor Vasiliu, Laura, Pop, Florin, Negru, Catalin, Mocanu, Mariana, Cristea, Valentin, Kolodziej, Joanna

“… but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying…”
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Middleware support for many-task computing Autor Raicu, Ioan, Foster, Ian, Wilde, Mike, Zhang, Zhao, Iskra, Kamil, Beckman, Peter, Zhao, Yong, Szalay, Alex, Choudhary, Alok, Little, Philip, Moretti, Christopher, Chaudhary, Amitabh, Thain, Douglas

“…Many-task computing aims to bridge the gap between two computing paradigms, high throughput computing and high performance computing…”
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A fast and low idle time method for mining frequent patterns in distributed and many-task computing environments Autor Lin, Chun-Cheng, Chung, Sheng-Hao, Chen, Ju-Chin, Yu, Yuan-Tse, Lin, Kawuu W.

“… technology to improve mining processing time in many-task computing, thereby bridging the gap…”
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Multi-objective scheduling of many tasks in cloud platforms Autor Zhang, Fan, Cao, Junwei, Li, Keqin, Khan, Samee U., Hwang, Kai

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Dynamical systems analysis using many-task interactive cloud computing Autor Popov, Stefan N., Vostokin, Sergei V., Doroshin, Anton V.

“… Parallelization of the computational process is achieved by supplying the list of running tasks for computing Lyapunov characteristic exponents, depending on the result of finished tasks during calculations…”
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A Bilevel Decomposition Approach for Many Homogeneous Computing Tasks Scheduling in Software-Defined Industrial Networks Autor Wang, Yong, Feng, Yixiong, Jin, Xuanzhi, Feng, Yiping, Li, Zhiwu, Tan, Jianrong

“… Deciding how to more efficiently schedule many homogeneous computing tasks, which extensively appear in SDIN, becomes of critical importance…”
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Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud Autor Warneke, D, Kao, O

“… Major Cloud computing companies have started to integrate frameworks for parallel data processing in their product portfolio, making it easy for customers to access these services and to deploy their programs…”
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