Bozkuş, Zeki

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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.
Email Address
Main Affiliation
Computer Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

13

CLIMATE ACTION
CLIMATE ACTION Logo

0

Research Products

2

ZERO HUNGER
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0

Research Products

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

0

Research Products

15

LIFE ON LAND
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0

Research Products

14

LIFE BELOW WATER
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0

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

0

Research Products

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

1

Research Products

5

GENDER EQUALITY
GENDER EQUALITY Logo

0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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0

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

Research Products

1

NO POVERTY
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0

Research Products

6

CLEAN WATER AND SANITATION
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0

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17

PARTNERSHIPS FOR THE GOALS
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0

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4

QUALITY EDUCATION
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0

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10

REDUCED INEQUALITIES
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This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

29

Articles

7

Views / Downloads

8/0

Supervised MSc Theses

9

Supervised PhD Theses

0

WoS Citation Count

107

Scopus Citation Count

183

WoS h-index

5

Scopus h-index

8

Patents

0

Projects

0

WoS Citations per Publication

3.69

Scopus Citations per Publication

6.31

Open Access Source

22

Supervised Theses

9

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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Scopus Quartile Distribution

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Scholarly Output Search Results

Now showing 1 - 10 of 29
  • 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.
  • 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.
  • Conference Object
    Citation - Scopus: 8
    GPU accelerated molecular docking simulation with genetic algorithms
    (Springer Verlag, 2016) Altuntaş,S.; Bozkus,Z.; Fraguela,B.B.
    Receptor-Ligand Molecular Docking is a very computationally expensive process used to predict possible drug candidates for many diseases. A faster docking technique would help life scientists to discover better therapeutics with less effort and time. The requirement of long execution times may mean using a less accurate evaluation of drug candidates potentially increasing the number of false-positive solutions, which require expensive chemical and biological procedures to be discarded. Thus the development of fast and accurate enough docking algorithms greatly reduces wasted drug development resources, helping life scientists discover better therapeutics with less effort and time. In this article we present the GPU-based acceleration of our recently developed molecular docking code. We focus on offloading the most computationally intensive part of any docking simulation, which is the genetic algorithm, to accelerators, as it is very well suited to them. We show how the main functions of the genetic algorithm can be mapped to the GPU. The GPU-accelerated system achieves a speedup of around ~ 14x with respect to a single CPU core. This makes it very productive to use GPU for small molecule docking cases. © Springer International Publishing Switzerland 2016.
  • Master Thesis
    Use of Machine Learning Techniques for Diagnosis of Thyroid Gland Disorder
    (Kadir Has Üniversitesi, 2016) Mofek, Izdihar; 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.
  • Conference Object
    Citation - Scopus: 15
    Improving OpenCL programmability with the Heterogeneous Programming Library
    (Elsevier B.V., 2015) Viñas,M.; Fraguela,B.B.; Bozkus,Z.; Andrade,D.
    The use of heterogeneous devices is becoming increasingly widespread. Their main drawback is their low programmability due to the large amount of details that must be handled. Another important problem is the reduced code portability, as most of the tools to program them are vendor or device-specific. The exception to this observation is OpenCL, which largely suffers from the reduced programmability problem mentioned, particularly in the host side. The Heterogeneous Programming Library (HPL) is a recent proposal to improve this situation, as it couples portability with good programmability. While the HPL kernels must be written in a language embedded in C++, users may prefer to use OpenCL kernels for several reasons such as their growing availability or a faster development from existing codes. In this paper we extend HPL to support the execution of native OpenCL kernels and we evaluate the resulting solution in terms of performance and programmability, achieving very good results. © The Authors. Published by Elsevier B.V.
  • 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%.
  • 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.
  • Article
    Citation - Scopus: 2
    Developing Adaptive Multi-Device Applications With the Heterogeneous Programming Library
    (Kluwer Academic Publishers, 2015) Viñas,M.; Bozkus,Z.; Fraguela,B.B.; Andrade,D.; Doallo,R.
    The usage of heterogeneous devices presents two main problems. One is their complex programming, a problem that grows when multiple devices are used. The second issue is that even if the codes for these devices can be portable on top of OpenCL, they lack performance portability, effectively requiring specialized implementations for each device to get good performance. In this paper we extend the Heterogeneous Programming Library (HPL), which improves the usability of heterogeneous systems on top of OpenCL, to better handle both issues. First, we provide HPL with mechanisms to support the implementation of any multi-device application that requires arbitrary patterns of communication between several devices and a host memory. In a second stage HPL is improved with an adaptive scheme to optimize communications between devices depending on the execution environment. An evaluation using benchmarks with very different nature shows that HPL reduces the SLOCs and programming effort of OpenCL applications by 27 and 43 %, respectively, while improving the performance of applications that exchange data between devices by 28 % on average. © 2015, Springer Science+Business Media New York.
  • 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.
  • 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.