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Showing 1 to 15 of 15 for “"online scheduling"”.
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STANNIC: Systolic Stochastic Online Scheduling Accelerator
Efficient workload scheduling is a critical challenge in modern heterogeneous computing environments, particularly in high-performance computing (HPC) systems. Traditional software-based schedulers struggle to efficiently balance workload distribution due to high scheduling overhead, lack of …
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Online Scheduling on Identical Machines Using SRPT
Item withdrawn by Alexis Thompson (athmpsn1@illinois.edu) on 2010-12-03T19:33:24Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 4 jeffe.sty: 24412 bytes, checksum: 7ff608a5b6c12b98320e3fb918b076e5 (MD5) SRPTidentical.tex: 41117 bytes, checksum: …
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Efficient Online Scheduling in Distributed Stream Data Processing Systems
… manner. A fundamental problem in a DSDPS is the scheduling problem, i.e., assigning threads (carrying workload) to workers/machines with the objective of minimizing average end-to-end tuple processing time (or simply tuple processing time). A widely-used solution is to distribute workload over …
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Online scheduling algorithms for broadcasting and general cost functions
In this thesis we study scheduling problems that occur in the client server setting. In this setting there are a set of jobs that are sent by clients over time to a sever. There is a scheduler at the sever that determines how the jobs should be processed. The goal of the scheduler is to process the …
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Online scheduling algorithms for average flow time and its variants
This dissertation focuses on scheduling problems that are found in a client-server setting where multiple clients and one server (or multiple servers) are the participating entities. Clients send their requests to the server(s) over time, and the server needs to satisfy the requests using its …
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Toward efficient online scheduling for large-scale distributed machine learning system
… a central question is how to design efficient scheduling algorithms to allocate workers and parameter servers across different machines to minimize the overall training time. Toward this end, in this paper, we develop an online scheduling algorithm that jointly optimizes resource allocation and …
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Online t-interval scheduling
This paper deals with non-preemptive online t-interval scheduling. A tinterval is a union of t half-open intervals (segments). In online scheduling the t-intervals are presented incrementally and each presented interval must be accepted or lost forever. A presented t-interval which overlaps a …
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Optimization problems with incomplete information
… completely known. Specifically, we consider two online problems where the problem instance is revealed over time, and one distributed problem involving many computational units, each of which can access only local information. We measure the performance of algorithms by the worst-case ratio …
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Thread Scheduling For Chip Multiprocessors
… the case. The result is poor performance because scheduling decisions fail to properly account for this non-uniform substrate. We investigate how to schedule applications for current and future systems when their performance can be limited by frequency heterogeneity among cores, or by the sharing …
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Frontiers In Operations Research For Overcoming Barriers To Vehicle Electrification
… We proposed an offline optimal mechanism for scheduling and pricing of electric vehicle charging considering incentives of both EV owners and utility companies. In the offline setting, information about future supply and demand is known to the scheduler. By considering uncertainty about future …
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Dynamic online resource allocation problems
Online resource allocation problems consider assigning a limited number of available resources to sequentially arriving requests with the objective to maximize rewards. With the emergence of e-business, applications such as online order fulfillment and customer service require real-time resource …
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Some combinational optimization problems on radio network communication and machine scheduling
… dissertation: network communication and machine scheduling. In the network communication area, the complexity of distributed broadcasting and distributed gossiping is studied in the setting of random networks. Two different models are considered: one is random geometric networks, the main model …
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Performance optimization and energy efficiency of big-data computing workflows
… interactions between workflow mapping and task scheduling on various computing platforms. A workflow optimization architecture is developed to seamlessly integrate three interrelated technical components, i.e., resource allocation, job mapping, and task scheduling. Cloud computing provides a …
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Experience-driven Control for Networking and Computing
… as one cutting-edge application, resource co-scheduling for Deep Neural Network (DNN) models on mobile and edge devices with heterogeneous hardware. </p><p>We first propose DRL-TE, a DRL-based framework that enables experience-driven networking for TE. DRL-TE maximizes a widely-used utility …
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Experience-driven Control For Networking And Computing
… as one cutting-edge application, resource co-scheduling for Deep Neural Network (DNN) models on mobile and edge devices with heterogeneous hardware. </p><p>We first propose DRL-TE, a DRL-based framework that enables experience-driven networking for TE. DRL-TE maximizes a widely-used utility …