Bozkuş, Zeki

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https://hdl.handle.net/20.500.12469/6964
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Bozkuş, Zeki
Z.,Bozkuş
Z. Bozkuş
Zeki, Bozkuş
Bozkus, Zeki
Z.,Bozkus
Z. Bozkus
Zeki, Bozkus
Bozkus,Z.
Job Title
Doç. Dr.
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Zekı[email protected]
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Computer Engineering
Status
Former Staff
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Scholarly Output

29

Articles

7

Views / Downloads

157/3325

Supervised MSc Theses

9

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WoS Citation Count

106

Scopus Citation Count

182

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5

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WoS Citations per Publication

3.66

Scopus Citations per Publication

6.28

Open Access Source

22

Supervised Theses

9

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JournalCount
Journal of Parallel and Distributed Computing2
Frontiers in Neuroinformatics2
2013 High Capacity Optical Networks and Emerging/Enabling Technologies, HONET-CNS 2013 -- 10th International Conference on High Capacity Optical Networks and Emerging/Enabling Technologies, HONET-CNS 2013 -- 11 December 2013 through 13 December 2013 -- Famagusta -- 1028061
2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing1
2015 International Conference on Emerging Technologies (ICET)1
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Now showing 1 - 10 of 29
  • Thumbnail Image
    Master Thesis
    Parallel Programming Techniques by Using Co-Array Fortran
    (Kadir Has Üniversitesi, 2011) Odabaşı, Aşkın; Bozkuş, Zeki
    Co-array Fortran (CAF) is a small set of extensions to Fortran 90. And also CAF is an emerging model for scalable global address space paralel programming. CAF.s global address space programming model simplifies the development of SPMD paralel programs by shifting the burden for managing the details of communication from developers to compilers. in this study i introduce CAF.s Programming Model provide it.s technical specifications explain CAF.s memory model and PGAS (Partitioned Global Address Space) make comparsion between two SPMD language CAF and OpenMP. in case i select Matrix Multiplication as a problem and wrote Co Array Fortran code fort his problem. i ran it on Amazon EC2 Cluster with 16 CPU and CentOS operating system. Finally i showed the performance numbers fort his work.
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    Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Hybrid Mpi Plus Upc Parallel Programming Paradigm on an Smp Cluster
    (TUBITAK Scientific & Technical Research Council Turkey, 2012) Bozkuş, Zeki
    The symmetric multiprocessing (SMP) cluster system which consists of shared memory nodes with several multicore central processing units connected to a high-speed network to form a distributed memory system is the most widely available hardware architecture for the high-performance computing community. Today the Message Passing Interface (MPI) is the most widely used parallel programming paradigm for SMP clusters in which the MPI provides programming both for an SMP node and among nodes simultaneously. However Unified Parallel C (UPC) is an emerging alternative that supports the partitioned global address space model that can be again employed within and across the nodes of a cluster. In this paper we describe a hybrid parallel programming paradigm that was designed to combine MPI and UPC programming models. This paradigm's objective is to mix the MPI's data locality control and scalability strengths with UPC's fine-grain parallelism and ease of programming to achieve multiple-level parallelism at the SMP cluster which itself has multilevel parallel architecture. Utilizing a proposed hybrid model and comparing MPI-only to UPC-only implementations this paper presents a detailed description of Cannon's algorithm benchmark application with performance results of a random-access benchmark and the Barnes-Hut N-Body simulation. Experiments indicate that the hybrid MPI+UPC model can significantly provide performance increases of up to double in comparison with UPC-only implementation and up to 20% increases in comparison to MPI-only implementation. Furthermore an optimization was achieved that improved the hybrid performance by an additional 20%.
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    Master Thesis
    Use of Machine Learning Techniques for Diagnosis of Thyroid Glang Disorder
    (Kadir Has Üniversitesi, 2016) Mofek, İzdihar A.B. El; Bozkuş, Zeki
    The advancements of computer technologies have generated an incredible amount of data and information from numerous sources. Nowadays, the way of implementing health care are being changing by utilizing the benefits of advancements in computer technologies. It is believed that engineering this amount of data can assist in developing predictive tool that can help physicians to diagnosing and predicting some debilitating life-threatening illness such as thyroid gland disease. Our current work focuses on investigating python languages to diagnose thyroid gland disease based on machine learning, and involves developing a new tool to predict the diagnoses of thyroid gland diseases, which we have called as a MLTDD (Machine Learning App for thyroid Disease Diagnosis). MLTDD has been designed with Qt designer and programmed using PyDev, which is python IDE for Eclipse. MLTDD could diagnose with 99.81% accuracy. Decision tree algorithm has been used to create the ML model, in addition to training dataset to learn from. ML model can be used to get predictions on new data for which you do not know the target and that is what we did to predict the diagnosis of thyroid gland disease as a hyperthyroidism or hypothyroidism or a normal condition using CRT decision tree algorithm. MLTDD can minify the cost, the waiting time, and help physicians for more research, as well as decrease the errors and mistakes that can be made by humans on account of exhaustion and tiredness.
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    Master Thesis
    Development of Hybrid Mpi+upc Parallel Programming Model
    (Kadir Has Üniversitesi, 2011) Öztürk, Elif; Bozkuş, Zeki
    Parallel Computing is a form of computation that divides a large set of calculations into tasks and runs on multi-core machines simultaneously. Today, Message Passing Interface (MPI) is the most widely used parallel programming paradigm that provides programming both for symmetric multi-processors (SMPs) which consists of shared memory nodes with several multi-core CPUs connected to a high speed network and among nodes simultaneously. Unified Parallel C (UPC) is an alternative language that supports Partitioned Global Address Space (PGAS) that allows shared memory like programming on distributed memory systems.In this thesis, we describe the MPI, UPC and hybrid parallel programming paradigm which is designed to combine MPI and UPC programming models. The aim of the hybrid model is to utilize the advantages of MPI and UPC; these are, MPI?s data locality control and scalability strengths with UPC?s global address space, fine grain parallelism and ease of programming to achieve multiple level parallelism. This thesis presents a detailed description of hybrid model implementation comparing with pure MPI and pure UPC implementations. Experiments showed that the hybrid MPI+UPC model can significantly provide performance increases up to double with pure UPC implementation and up to 20% increases in comparison to pure MPI implementation. Furthermore, an optimization was achieved which improved the hybrid performance an additional 20%.
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    Article
    Citation - WoS: 27
    Citation - Scopus: 27
    Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library
    (Academic Press Inc Elsevier Science, 2013) Vinas, Moises; Bozkuş, Zeki; Fraguela, Basilio B.
    While recognition of the advantages of heterogeneous computing is steadily growing the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability but its interface is even more complex than that of other approaches. In this paper we present the Heterogeneous Programming Library (HPL) which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance while outlining the programmability advantages of HPL. (C) 2013 Elsevier Inc. All rights reserved.
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    Correction
    Software for Brain Network Simulations: a Comparative Study (vol 11, 46, 2017)
    (Frontiers Media Sa, 2018) Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.
    [No Abstract Available]
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    Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Accelerating Brain Simulations on Graphical Processing Units
    (IEEE, 2015) Kayraklıoğlu, Engin; El-Ghazawi, Tarek A.; Bozkuş, Zeki
    NEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.
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    Conference Object
    Citation - Scopus: 4
    A Software Architecture for Inventory Management System
    (2013) Arsan, Taner; Başkan, Emrah; Ar, Emrah; Bozkuş, Zeki
    Inventory Management is one of the basic problems in almost every company. Before computer age and integration paper tables and paperwork solutions were being used as inventory management tools. These we very far from being a solution took so much time even needed employees just for this section of organization. There was no an efficient solution available in the many companies during these days. Every process was based on paperwork human fault rate was high the process and the tracing the inventory losses were not possible and there was no efficient logging systems. After the computer age every process is started to be integrated into electronic environment. And now we have qualified technology to implement new solutions to these problems. Software based systems bring the advantages of having the most efficient control with less effort and employees. These developments provide new solutions for also inventory management systems in this context. In this paper a new solution for Inventory Management System (IMS) is designed and implemented. Most importantly this system is designed for Kadir Has University and used as Inventory Management System. © 2013 Springer Science+Business Media.
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    Article
    Citation - Scopus: 27
    Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library
    (2013) Viñas,M.; Bozkus,Z.; Fraguela,B.B.
    While recognition of the advantages of heterogeneous computing is steadily growing, the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability, but its interface is even more complex than that of other approaches. In this paper, we present the Heterogeneous Programming Library (HPL), which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance, while outlining the programmability advantages of HPL. © 2013 Elsevier Inc. All rights reserved.
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    Conference Object
    Citation - Scopus: 10
    Big Data Platform Development With a Domain Specific Language for Telecom Industries
    (IEEE Computer Society, 2013) Senbalci,C.; Altuntas,S.; Bozkus,Z.; Arsan,T.
    This paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. This platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. These parts are Domain Specific Language (DSL), Parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. In addition to these main parts, Distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution, standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing, processing, analyzing operations. This infrastructure can be grouped as four different parts, these are infrastructure, programming models, high performance schema free databases, and processing-analyzing. Although there are lots of advantages of Big Data concept, it is still very difficult to manage these systems for many enterprises. Therefore, this study suggest a new higher level language, called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes, a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer. © 2013 IEEE.