Search Results - "Many task computing"

Multi-objective scheduling of many tasks in cloud platforms by Zhang, Fan, Cao, Junwei, Li, Keqin, Khan, Samee U., Hwang, Kai

Get full text

Asymptotic scheduling for many task computing in Big Data platforms by 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…”
Get full text

Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud by 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…”
Get full text

Load-balanced and locality-aware scheduling for data-intensive workloads at extreme scales by 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…”
Get full text

In Cloud, Can Scientific Communities Benefit from the Economies of Scale? by 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…”
Get full text

Towards effective scheduling policies for many‐task applications: Practice and experience based on HTCaaS by 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…”
Get full text

DALiuGE: A graph execution framework for harnessing the astronomical data deluge by 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…”
Get full text

Achieving Fairness-Aware Two-Level Scheduling for Heterogeneous Distributed Systems by 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…”
Get full text

The Use of Algorithmic Skeletons to Design Actor-Based Parallel Algorithms by 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…”
Get full text

Resource Allocation Policies for Loosely Coupled Applications in Heterogeneous Computing Systems by 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…”
Get full text

Overcoming data locality: An in-memory runtime file system with symmetrical data distribution by 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…”
Get full text

Efficient algorithms for frequent pattern mining in many-task computing environments by 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…”
Get full text

Resource Profiling and Performance Modeling for Distributed Scientific Computing Environments by 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…”
Get full text

Dynamic DAG scheduling for many-task computing of distributed eco-hydrological model by 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…”
Get full text

A cloudification methodology for multidimensional analysis: Implementation and application to a railway power simulator by 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…”
Get full text

Coupled Ocean-Acoustic Prediction of Transmission Loss in a Continental Shelfbreak Region: Predictive Skill, Uncertainty Quantification, and Dynamical Sensitivities by 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…”
Get full text

A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing by 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…”
Get full text

On the role of message broker middleware for many-task computing on a big-data platform by 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…”
Get full text

Robust Performance-Based Resource Provisioning Using a Steady-State Model for Multi-Objective Stochastic Programming by 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…”
Get full text

A Hybrid Scheduler for Many Task Computing in Big Data Systems by Vasiliu, Laura, Pop, Florin, Negru, Catalin, Mocanu, Mariana, Cristea, Valentin, Kolodziej, Joanna

“…With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or…”
Get full text