Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters

A Master of Science thesis in Computer Engineering by Abid Farhan entitled, “Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters”, submitted in April 2021. Thesis advisor is Dr. Assim Sagahyroon and thesis co-advisor Dr. Raafat Aburukba. Soft copy is available (Thesis, Completi...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Farhan, Abid (author)
التنسيق: doctoralThesis
منشور في: 2021
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/21501
الوسوم: إضافة وسم
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author Farhan, Abid
author_facet Farhan, Abid
author_role author
dc.contributor.none.fl_str_mv Sagahyroon, Assim
Aburukba, Raafat
dc.creator.none.fl_str_mv Farhan, Abid
dc.date.none.fl_str_mv 2021-06-15T09:25:41Z
2021-06-15T09:25:41Z
2021-04
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2021.04
http://hdl.handle.net/11073/21501
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv FPGA
Field-Programmable Gate Arrays (FPGAs)
Cloud computing
Virtualization
Scheduling
CloudSim
dc.title.none.fl_str_mv Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Computer Engineering by Abid Farhan entitled, “Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters”, submitted in April 2021. Thesis advisor is Dr. Assim Sagahyroon and thesis co-advisor Dr. Raafat Aburukba. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/21501
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spelling Virtualizing and Scheduling FPGA Resources in Cloud Computing DatacentersFarhan, AbidFPGAField-Programmable Gate Arrays (FPGAs)Cloud computingVirtualizationSchedulingCloudSimA Master of Science thesis in Computer Engineering by Abid Farhan entitled, “Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters”, submitted in April 2021. Thesis advisor is Dr. Assim Sagahyroon and thesis co-advisor Dr. Raafat Aburukba. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Cloud service providers are consistently leveraging their computing infrastructures by adding reconfigurable hardware platforms such as field-programmable gate arrays (FPGAs) to their existing infrastructures. Adding FPGAs to a cloud environment involves non-trivial challenges. The first challenge is the virtualization of FPGAs in order to enable FPGAs as cloud resources. Since there does not exist a standard virtualization framework, there is a need to devise an efficient framework for virtualizing FPGAs. Moreover, FPGA resources are used in conjunction with central processing units (CPUs) and graphics processing units (GPUs) to accelerate the execution of different tasks. Therefore, to gain the benefits of these powerful accelerating platforms, the second challenge is to optimize the allocation of a batch of tasks to minimize their makespan. Furthermore, the third challenge is for cloud providers to be able to quantify the performance of the various policies implemented in their cloud datacenters. In this work, an FPGA virtualization framework is proposed to abstract physical FPGAs into virtual pools of FPGA resources. Next, an integer linear programming (ILP) model is proposed to optimize the allocation of FPGA resources to cloud tasks requiring acceleration. Preliminary attempts to validate the model indicate that an optimal solution, which is the minimum makespan, is obtained using an exact solution method. Next, a simulated annealing (SA) metaheuristic is developed not only to achieve gains in performance compared to the exact method, but also scale up and handle larger datasets while providing near-optimal solutions. Experimental results show that SA has reduced the makespan of a large dataset with 1000 tasks and 100 resources by up to 30% when compared to first-come-first-serve (FCFS) and shortest-deadline-first (SDF) algorithms. Lastly, in order to quantify the performance of FPGA-enabled cloud datacenters, an existing cloud simulator named CloudSim is extended to enable FPGA as a resource in its environment. The proposed virtualization framework and the SA scheduler are integrated into the environment. Simulation results show that execution time of tasks is reduced by up to 78% when FPGA accelerators are used.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)Sagahyroon, AssimAburukba, Raafat2021-06-15T09:25:41Z2021-06-15T09:25:41Z2021-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2021.04http://hdl.handle.net/11073/21501en_USoai:repository.aus.edu:11073/215012025-06-26T12:34:46Z
spellingShingle Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
Farhan, Abid
FPGA
Field-Programmable Gate Arrays (FPGAs)
Cloud computing
Virtualization
Scheduling
CloudSim
status_str publishedVersion
title Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
title_full Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
title_fullStr Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
title_full_unstemmed Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
title_short Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
title_sort Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
topic FPGA
Field-Programmable Gate Arrays (FPGAs)
Cloud computing
Virtualization
Scheduling
CloudSim
url http://hdl.handle.net/11073/21501