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Failed workloads that consumed significant computational resources in time and space affect the efficiency of data centers significantly and thus limit the amount of scientific work that can be achieved. While the computational power has…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-13 Jie Li , Rui Wang , Ghazanfar Ali , Tommy Dang , Alan Sill , Yong Chen

Containers offer an array of advantages that benefit research reproducibility and portability across groups and systems. As container tools mature, container security improves, and High-performance computing (HPC) and cloud system tools…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-24 Tiziano Müller , Nina Mujkanovic , Juan J. Durillo , Nicolay Hammer

Modern data centers are tasked with processing heterogeneous workloads consisting of various classes of jobs. These classes differ in their arrival rates, size distributions, and job parallelizability. With respect to paralellizability,…

Performance · Computer Science 2020-05-21 Benjamin Berg , Mor Harchol-Balter , Benjamin Moseley , Weina Wang , Justin Whitehouse

This paper envisions a scenario that hundreds of heterogeneous robots form a robotcenter which can be shared by multiple users and used like a single powerful robot to perform complex tasks. However, current multi-robot systems are either…

Robotics · Computer Science 2018-05-03 Yuan Xu , Zhiyuan Yan , Sa Wang , Cheng Yang , Qingsai Xiao , Yungang Bao

Multi-server jobs are imperative in modern computing clusters. A multi-server job has multiple task components and each of the task components is responsible for processing a specific size of workloads. Efficient online workload dispatching…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-14 Hailiang Zhao , Shuiguang Deng , Jianwei Yin , Schahram Dustdar , Albert Y. Zomaya

The adoption of cloud computing technologies in the industry is paving the way to new manufacturing paradigms. In this paper we propose a model to optimize the orchestration of workloads with differentiated criticality levels on a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-29 Marco Barletta , Marcello Cinque , Davide De Vita

Cloud service providers are distributing data centers geographically to minimize energy costs through intelligent workload distribution. With increasing data volumes in emerging cloud workloads, it is critical to factor in the network costs…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-02 Ninad Hogade , Sudeep Pasricha , Howard Jay Siegel

Large multi-tenant production clusters often have to handle a variety of jobs and applications with a variety of complex resource usage characteristics. It is non-trivial and non-optimal to manually create placement rules for scheduling…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-31 Subrata Mitra , Shanka Subhra Mondal , Nikhil Sheoran , Neeraj Dhake , Ravinder Nehra , Ramanuja Simha

Nowadays most of the cloud applications process large amount of data to provide the desired results. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-05 B. Thirumala Rao , N. V. Sridevi , V. Krishna Reddy , L. S. S. Reddy

Cloud computing infrastructures increasingly rely on geographically distributed data centers to meet the growing demand for low latency, high availability, and cost-efficient service delivery. In this context, load balancing plays a…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-12 Saeid Aghasoleymani Najafabadi , Elaheh Nabavi Nia

In a hierarchically-structured cloud/edge/device computing environment, workload allocation can greatly affect the overall system performance. This paper deals with AI-oriented medical workload generated in emergency rooms (ER) or intensive…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-11 Tianshu Hao , Jianfeng Zhan , Kai Hwang , Wanling Gao , Xu Wen

We consider load balancing in large-scale heterogeneous server systems in the presence of data locality that imposes constraints on which tasks can be assigned to which servers. The constraints are naturally captured by a bipartite graph…

Probability · Mathematics 2022-12-01 Zhisheng Zhao , Debankur Mukherjee , Ruoyu Wu

Virtual clusters are widely used computing platforms than can be deployed in multiple cloud platforms. The ability to dynamically grow and shrink the number of nodes has paved the way for customised elastic computing both for High…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-18 Miguel Caballer , Marica Antonacci , Zdeněk Šustr , Michele Perniola , Germán Moltó

The emergence of cloud computing has made dynamic provisioning of elastic capacity to applications on-demand. Cloud data centers contain thousands of physical servers hosting orders of magnitude more virtual machines that can be allocated…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 Rajkumar Buyya , Kotagiri Ramamohanarao , Chris Leckie , Rodrigo N. Calheiros , Amir Vahid Dastjerdi , Steve Versteeg

This paper introduces the large scale visual search algorithm and system infrastructure at Alibaba. The following challenges are discussed under the E-commercial circumstance at Alibaba (a) how to handle heterogeneous image data and bridge…

Computer Vision and Pattern Recognition · Computer Science 2021-02-10 Yanhao Zhang , Pan Pan , Yun Zheng , Kang Zhao , Yingya Zhang , Xiaofeng Ren , Rong Jin

In data centers, up to dozens of tasks are colocated on a single physical machine. Machines are used more efficiently, but tasks' performance deteriorates, as colocated tasks compete for shared resources. As tasks are heterogeneous, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-29 Fanny Pascual , Krzysztof Rzadca

While scheduling and dispatching of computational workloads is a well-investigated subject, only recently has Google provided publicly a vast high-resolution measurement dataset of its cloud workloads. We revisit dispatching and scheduling…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-27 Mert Yildiz , Alexey Rolich , Andrea Baiocchi

In this paper, we study a data caching problem in the cloud environment, where multiple frequently co-utilised data items could be packed as a single item being transferred to serve a sequence of data requests dynamically with reduced cost.…

Data Structures and Algorithms · Computer Science 2022-08-08 Jiashu Wu , Hao Dai , Yang Wang , Yong Zhang , Dong Huang , Chengzhong Xu

The core of the computer business now offers subscription-based on-demand services with the help of cloud computing. We may now share resources among multiple users by using virtualization, which creates a virtual instance of a computer…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-13 Sakshi Chhabra , Ashutosh Kumar Singh

Cloud Computing is an emerging area for accessing computing resources. In general, Cloud service providers offer services that can be clustered into three categories: SaaS, PaaS and IaaS. This paper discusses the Cloud workload analysis.…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-02-14 Sukhpal Singh , Inderveer Chana