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Related papers: Accelerating R-based Analytics on the Cloud

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Stochastic algorithms are efficient approaches to solving machine learning and optimization problems. In this paper, we propose a general framework called Splash for parallelizing stochastic algorithms on multi-node distributed systems.…

Machine Learning · Computer Science 2015-09-24 Yuchen Zhang , Michael I. Jordan

Developing efficient parallel applications is critical to advancing scientific development but requires significant performance analysis and optimization. Performance analysis tools help developers manage the increasing complexity and scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-25 Onur Cankur , Aditya Tomar , Daniel Nichols , Connor Scully-Allison , Katherine E. Isaacs , Abhinav Bhatele

Data exchange through mobile devices is rapidly increasing due to the high information demands of today's applications. The need for monitoring the exchanged traffic becomes important in order to control and optimize the device and network…

Networking and Internet Architecture · Computer Science 2024-06-27 Kyriazis Kokkinos , Ioannis Polymenidis , Ilias Siniosoglou , Athanasios Liatifis , Panagiotis Sarigiannidis

With weather becoming more extreme both in terms of longer dry periods and more severe rain events, municipal water networks are increasingly under pressure. The effects include damages to the pipes, flash floods on the streets and combined…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-18 Felix Lorenz , Morgan Geldenhuys , Harald Sommer , Frauke Jakobs , Carsten Lüring , Volker Skwarek , Ilja Behnke , Lauritz Thamsen

Cloud computing has become the leading paradigm for deploying large-scale infrastructures and running big data applications, due to its capacity of achieving economies of scale. In this work, we focus on one of the most prominent advantages…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-20 Athanasios Naskos , Emmanouela Stachtiari , Anastasios Gounaris , Panagiotis Katsaros , Dimitrios Tsoumakos , Ioannis Konstantinou , Spyros Sioutas

This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-15 Ali Khajeh-Hosseini , Ian Sommerville , Jurgen Bogaerts , Pradeep Teregowda

Machine Learning (ML) techniques have begun to dominate data analytics applications and services. Recommendation systems are a key component of online service providers. The financial industry has adopted ML to harness large volumes of data…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-29 Richard Mortier , Hamed Haddadi , Sandra Servia , Liang Wang

Function-as-a-Service is a novel type of cloud service used for creating distributed applications and utilizing computing resources. Application developer supplies source code of cloud functions, which are small applications or application…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-10 Maciej Pawlik , Kamil Figiela , Maciej Malawski

Today's cloud-hosted applications and services are complex systems, and a performance or functional instability can have dozens or hundreds of potential root causes. Our hypothesis is that by combining the pattern matching capabilities of…

Artificial Intelligence · Computer Science 2025-05-29 Yifan Wang , Kenneth P. Birman

This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures;…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-08-28 Marcos D. Assuncao , Rodrigo N. Calheiros , Silvia Bianchi , Marco A. S. Netto , Rajkumar Buyya

In order to plan for failure recovery, the designers of cloud systems need to understand how their system can potentially fail. Unfortunately, analyzing the failure behavior of such systems can be very difficult and time-consuming, due to…

Software Engineering · Computer Science 2022-03-09 Domenico Cotroneo , Luigi De Simone , Pietro Liguori , Roberto Natella , Nematollah Bidokhti

Dynamic nature of the cloud environment has made distributed resource management process a challenge for cloud service providers. The importance of maintaining the quality of service in accordance with customer expectations as well as the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-08-08 Sara Kardani-Moghaddam , Rajkumar Buyya , Kotagiri Ramamohanarao

Data communication in cloud-based distributed stream data analytics often involves a collection of parallel and pipelined TCP flows. As the standard TCP congestion control mechanism is designed for achieving "fairness" among competing flows…

Networking and Internet Architecture · Computer Science 2019-08-08 Walid Aljoby , Xin Wang , Tom Z. J. Fu , Richard T. B. Ma

The accelerating technological landscape and drive towards net-zero emission made the power system grow in scale and complexity. Serial computational approaches for grid planning and operation struggle to execute necessary calculations…

Systems and Control · Electrical Eng. & Systems 2022-07-07 Ahmed Al-Shafei , Hamidreza Zareipour , Yankai Cao

Emergence of sophisticated technologies in IT industries has posed several challenges such as production of products using advanced technical process for instance Result Orientation Approach, Deployment, Assessment and Refinement (RADAR) in…

Other Computer Science · Computer Science 2012-07-17 T. R. Gopalakrishnan Nair , M. Vaidehi , V. Suma

Optimizing resource allocation for analytical workloads is vital for reducing costs of cloud-data services. At the same time, it is incredibly hard for users to allocate resources per query in serverless processing systems, and they…

Due to the pervasive diffusion of personal mobile and IoT devices, many ``smart environments'' (e.g., smart cities and smart factories) will be, among others, generators of huge amounts of data. Currently, this is typically achieved through…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-28 Lorenzo Valerio , Andrea Passarella , Marco Conti

Aneka is a platform for deploying Clouds developing applications on top of it. It provides a runtime environment and a set of APIs that allow developers to build .NET applications that leverage their computation on either public or private…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-07-28 Christian Vecchiola , Xingchen Chu , Rajkumar Buyya

Training an effective Machine learning (ML) model is an iterative process that requires effort in multiple dimensions. Vertically, a single pipeline typically includes an initial ETL (Extract, Transform, Load) of raw datasets, a model…

Machine Learning · Computer Science 2024-01-31 Dachi Chen , Weitian Ding , Chen Liang , Chang Xu , Junwei Zhang , Majd Sakr

Elasticity is a cloud property that enables applications and its execution systems to dynamically acquire and release shared computational resources on demand. Moreover, it unfolds the advantage of economies of scale in the cloud through a…

Software Engineering · Computer Science 2017-02-27 Carlos Mera-Gómez , Francisco Ramírez , Rami Bahsoon , Rajkumar Buyya