Výsledky vyhľadávania - "Many-Task Computing"

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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Asymptotic scheduling for many task computing in Big Data platforms Autor Sfrent, Andrei, Pop, Florin

“…Due to the advancement of technology the datasets that are being processed nowadays in modern computer clusters extend beyond the petabyte scale – the 4…”
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Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud Autor Warneke, D, Kao, O

“…In recent years ad hoc parallel data processing has emerged to be one of the killer applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud…”
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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‐intensive scientific applications. MTC applies…”
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In Cloud, Can Scientific Communities Benefit from the Economies of Scale? Autor Wang, Lei, Zhan, Jianfeng, Shi, Weisong, Liang, Yi

“…The basic idea behind cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to…”
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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‐task applications where multiple users…”
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DALiuGE: A graph execution framework for harnessing the astronomical data deluge Autor Wu, C., Tobar, R., Vinsen, K., Wicenec, A., Pallot, D., Lao, B., Wang, R., An, T., Boulton, M., Cooper, I., Dodson, R., Dolensky, M., Mei, Y., Wang, F.

“…The Data Activated Liu1 Graph Engine – DALiuGE2– is an execution framework for processing large astronomical datasets at a scale required by the Square…”
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Achieving Fairness-Aware Two-Level Scheduling for Heterogeneous Distributed Systems Autor Hwang, Eunji, Kim, Jik-Soo, Choi, Young- ri

“…In a heterogeneous distributed system composed of various types of computing platforms such as supercomputers, grids, and clouds, a two-level scheduling…”
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The Use of Algorithmic Skeletons to Design Actor-Based Parallel Algorithms Autor Sergey Vostokin, Irina Bobyleva

“…The paper proposes a method for writing parallel algorithms. Our goal was to make a detailed description of concurrency while carrying no dependencies in…”
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Resource Allocation Policies for Loosely Coupled Applications in Heterogeneous Computing Systems Autor Hwang, Eunji, Kim, Suntae, Yoo, Tae-kyung, Kim, Jik-Soo, Hwang, Soonwook, Choi, Young-ri

“…High-Throughput Computing (HTC) and Many-Task Computing (MTC) paradigms employ loosely coupled applications which consist of a large number, from tens of…”
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MTCProv: a practical provenance query framework for many-task scientific computing Autor Gadelha, Luiz M. R., Wilde, Michael, Mattoso, Marta, Foster, Ian

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Overcoming data locality: An in-memory runtime file system with symmetrical data distribution Autor Uta, Alexandru, Sandu, Andreea, Kielmann, Thilo

“…In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communicate via intermediate files; application performance…”
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Efficient algorithms for frequent pattern mining in many-task computing environments Autor Lin, Kawuu W., Lo, Yu-Chin

“…The goal of data mining is to discover hidden useful information in large databases. Mining frequent patterns from transaction databases is an important…”
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Resource Profiling and Performance Modeling for Distributed Scientific Computing Environments Autor Hossain, Md Azam, Hwang, Soonwook, Kim, Jik-Soo

“…Scientific applications often require substantial amount of computing resources for running challenging jobs potentially consisting of many tasks from hundreds…”
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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

“…The computing of distributed hydrological model at large scale is increasingly characterized by data intensive and computation intensive, especially for the…”
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A cloudification methodology for multidimensional analysis: Implementation and application to a railway power simulator Autor Caíno-Lores, Silvina, Fernández, Alberto García, García-Carballeira, Félix, Pérez, Jesús Carretero

“…Many scientific areas make extensive use of computer simulations to study complex real-world processes. These computations are typically very…”
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Coupled Ocean-Acoustic Prediction of Transmission Loss in a Continental Shelfbreak Region: Predictive Skill, Uncertainty Quantification, and Dynamical Sensitivities Autor Lermusiaux, Pierre F J, Jinshan Xu, Chi-Fang Chen, Jan, Sen, Chiu, Linus Y, Yiing-Jang Yang

“…In this paper, we quantify the dynamical causes and uncertainties of striking differences in acoustic transmission data collected on the shelf and shelfbreak…”
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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…”
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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) which aims to effectively support fine-grained…”
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Robust Performance-Based Resource Provisioning Using a Steady-State Model for Multi-Objective Stochastic Programming Autor Tarplee, Kyle M., Maciejewski, Anthony A., Siegel, Howard Jay

“…Cloud computing has enabled entirely new business models for high-performance computing. Having a dedicated local high-performance computer is still an option…”
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