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DESIGN AND APPLICATION OF A NOVEL FPGA DEVELOPMENT BOARD

Year 2022, , 46 - 55, 28.02.2023
https://doi.org/10.54047/bibted.1149594

Abstract

In this study, it is aimed to design a new native FPGA circuit board with the necessary hardware elements in order to realize the basic digital applications and designs in the field of engineering on a real-time FPGA-based basis. In order to reduce the cost of the FPGA development board, the hardware on it is kept to a minimum. Altium PCB Design Software & Tools program was used in the electronic circuit drawings of the FPGA development board. In order to test the designed FPGA development board, sample digital system design projects were coded in VHDL (Very High Speed Integrated Circuit Hardware Description Language) language with Xilinx ISE Design Tools program. The bitstream files obtained after the Place-Route process of the sample digital system design projects were loaded onto the FPGA chip with the JTAG (Joint Test Action Group) interface. After the installation process, it has been observed that the sample digital system design projects work successfully on the FPGA development board. With the design presented in this study, a domestic FPGA development board that can be used in engineering education and applications with a lower cost as an alternative to the FPGA development boards that are currently used with very high costs by being imported from abroad has been successfully developed.

References

  • Abdullah H T, Younis B M, (2019), FPGA Based Bone Fracture Detector, IOP Conference Series: Materials Science and Engineering, 745, Article number 012052.
  • Akkoyun, F. (2011), FPGA Tabanlı Dokunmatik Ekranlı Kullanıcı Arabirimi Tasarlanması ve Gerçekleştirilmesi. Kocaeli Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, 103s, Kocaeli.
  • Alçın, M., Koyuncu, I., Tuna, M., Varan, M., & Pehlivan, I. (2019), A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array. International Journal of Circuit Theory and Applications, 47(3): 365-378
  • Az, I. (2014), Fpga Tabanlı Şifreli Kablosuz Haberleşme Sistemi, Doctoral dissertation, Fen Bilimleri Enstitüsü.
  • Bargsten V, de Gea Fernández J, (2020), Distributed computation and control of robot motion dynamics on FPGAs, International Journal of SN Applied Sciences, 2, Article number 1239.
  • Diao, L., Tang, J., Loh, P. C., Yin, S., Wang, L., & Liu, Z. (2018), An efficient DSP–FPGA-based implementation of hybrid PWM for electric rail traction induction motor control. IEEE Transactions on Power Electronics, 33(4): 3276-3288.
  • Dong, E., Yuan, M., Du, S., & Chen, Z. (2019), A new class of Hamiltonian conservative chaotic systems with multistability and design of pseudo-random number generator. Applied Mathematical Modelling, 73: 40-71
  • Drozd, O. V., & Kapulin, D. V. (2018), The device of secure data transmission based on Magma crypto algorithm with implementation on FPGA. In 2018 Moscow Workshop on Electronic and Networking Technologies (MWENT), (pp. 1-5). IEEE.
  • İsmail, S. M., Said, L. A., Rezk, A. A., Radwan, A. G., Madian, A. H., Abu-Elyazeed, M. F., & Soliman, A. M. (2017), Generalized fractional logistic map encryption system based on FPGA. AEU-International Journal of Electronics and Communications, 80: 114-126
  • Koyuncu, İ., Ozcerit, A. T., & Pehlivan, I. (2014), Implementation of FPGA-based real time novel chaotic oscillator. Nonlinear Dynamics, 77(1-2): 49-59.
  • Koyuncu, İ., Çetin, Ö., Katırcıoğlu, F., & Tuna, M. (2015), Edge dedection application with FPGA based Sobel operator. In 2015 23nd Signal Processing and Communications Applications Conference (SIU), (pp. 1829-1832). IEEE
  • Libano, F., Rech, P., Tambara, L., Tonfat, J., & Kastensmidt, F. (2018), On the reliability of linear regression and pattern recognition feedforward artificial neural networks in FPGAs. IEEE Transactions on Nuclear Science, 65(1): 288-295.
  • Munden, R. (2005), ASIC and FPGA verification: a guide to component modeling. Morgan Kaufmann Publ., Elsevier, San Francisco, USA
  • Özgür, M. (2014), Radar sinyal işleme algoritmalarının FPGA ve GPU üzerinde uygulanmasının başarım analizi, Master's thesis, TOBB Ekonomi ve Teknoloji Üniversitesi Fen Bilimleri Enstitüsü
  • Özkan, İ. A., Sarıtaş, İ., & Herdem, S. (2011), Manyetik filtreler için FPGA tabanlı bulanık kontrolör tasarımı.
  • Rahul, D. (2009), Introduction to Embedded System Design Using Field Programmable Gate Arrays.
  • Rodríguez-Orozco, E., García-Guerrero, E., Inzunza-Gonzalez, E., López-Bonilla, O., Flores-Vergara, A., Cárdenas-Valdez, J., & Tlelo-Cuautle, E. (2018), FPGA-based chaotic cryptosystem by using voice recognition as access key. Electronics, 7(12): 414
  • Savran İ, (2017), Donanım Tanımlama Dili VHDL ve FPGA Uygulamaları, Papatya Yayıncılık Eğitim, İstanbul.
  • Schafer, B. C., Takenaka, T., & Wakabayashi, K. (2009), Adaptive simulated annealer for high level synthesis design space exploration. In 2009 International Symposium on VLSI Design, Automation and Test, (pp. 106-109). IEEE.
  • Sinha, A. Lotia, P. (2015), A study on FPGA based digital modulators. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 4(4), 1935-1942.STMicroelectronics. 2020, AN2867 Application Note, (Rev 12). Oscillator design guide for STM8AF/AL/S, STM32 MCUs and MPUs.
  • Şahin, İ., Gloster, C., Doss, C. (2000), Feasibility of floating-point arithmetic in reconfigurable computing systems. Military and Aerospace Applications of Programmable Devices and Techn. Conf., Washington, DC.
  • Şahin, İ., Koyuncu, İ. (2011), A new module design for 3D graphic transformations using generated floating-point core units. I. Rev. on Modelling and Sim., 4(2):691-698
  • Tengilimoglu, B. Bazlamaçcı, C. F. (2014), Partial reconfiguration on a real-time target detection and tracking system. In 2014 22nd Signal Processing and Communications Applications Conference (SIU) (pp. 1130-1133). IEEE.
  • Tlelo-Cuautle, E., Guillén-Fernández, O., de Jesus Rangel-Magdaleno, J., Melendez-Cano, A., Nuñez-Perez, J. C., & de la Fraga, L. G. (2019), FPGA Implementation of Chaotic Oscillators, Their Synchronization, and Application to Secure Communications. In Re.
  • Tuntas R, (2015), The Modeling and Hardware Implementation of Semiconductor Circuit Elements by Using ANN and FPGA, Acta Physica Polonica Series a, 128(2B), pp. 78-81.
  • Yılmaz, N., (2008), Alan Programlamalı Kapı Dizileri (FPGA) Üzerinde Bir YSA’nın Tasarlanması ve Donanım Olarak Gerçekleştirilmesi, Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Konya.
  • Yılmaz C, Koyuncu I, Alçın M, Tuna M, 2019, Artificial Neural Networks based thermodynamic and economic analysis of a hydrogen production system assisted by geothermal energy on Field Programmable Gate Array, International Journal of Hydrogen Energy, 44, 17443-17459.
  • Alçın, M., Koyuncu, İ., Tuna, M., Varan, M., & Pehlivan, İ. (2019). A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array. International Journal of Circuit Theory and Applications, 47(3), 365-378.
  • Karataş, F., Koyuncu, İ., Alçın, M., Tuna, M. (2020). FPGA based Implementatıon of membership functions for real time fuzzy logic applications, International Asian congress on Contemporary Sciences-3, Konya, Turkey, pp. 62-69.
  • Rajagopal, K., Tuna, M., Karthikeyan, A., Koyuncu, İ., Duraisamy, P., & Akgul, A. (2019). Dynamical analysis, sliding mode synchronization of a fractional-order memristor Hopfield neural network with parameter uncertainties and its non-fractional-order FPGA implementation. The European Physical Journal Special Topics, 228(10), 2065-2080.
  • Tuna, M., Koyuncu, İ., Alçın, M. (2018). Fixed and Floating point-Based High-Speed Chaotic Oscillator Design with Different Numerical Algorithms on FPGA. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. Vol 7, Issue 7.
  • Tuna, M., Alçın, M., Koyuncu, İ., Fidan, C. B., & Pehlivan, İ. (2019). High speed FPGA-based chaotic oscillator design. Microprocessors and Microsystems, 66, 72-80.
  • Yılmaz, C., Koyuncu, İ., Alçın, M., & Tuna, M. (2019). Artificial Neural Networks based thermodynamic and economic analysis of a hydrogen production system assisted by geothermal energy on Field Programmable Gate Array. International Journal of Hydrogen Energy, 44(33), 17443-17459.

YENİ BİR FPGA GELİŞTİRME KARTI TASARIMI VE UYGULAMASI

Year 2022, , 46 - 55, 28.02.2023
https://doi.org/10.54047/bibted.1149594

Abstract

Sunulan bu çalışmada, üzerinde mühendislik alanındaki temel sayısal uygulama ve tasarımların gerçek zamanlı FPGA tabanlı olarak gerçekleştirilebilmesi için gerekli donanım elemanlarına sahip yeni bir yerli FPGA devre kartı tasarlanmıştır. FPGA geliştirme kartının maliyetinin düşürülmesi amacı ile üzerindeki donanım minimum seviyede tutulmuştur. FPGA geliştirme kartının elektronik devre çizimlerinde Altium PCB Design Software & Tools programı kullanılmıştır. Tasarlanan FPGA geliştirme kartının test edilebilmesi amacı ile Xilinx ISE Design Tools programı ile VHDL (Very High Speed Integrated Circuit Hardware Description Language-Çok Yüksek Hızlı Tümleşik Devre Donanımı Tanımlama Dili) dilinde örnek sayısal sistem tasarımı projeleri kodlanmıştır. Örnek sayısal sistem tasarımı projelerinin Place-Route işleminin ardından elde edilen bitstream dosyaları JTAG (Joint Test Action Group (Ortak Test Eylem Grubu)) ara yüzü ile FPGA çipine yüklenmiştir. Yükleme işleminin ardından örnek sayısal sistem tasarımı projelerinin FPGA geliştirme kartı üzerinde başarılı bir şekilde çalıştığı gözlemlenmiştir. Bu çalışmada sunulan tasarım ile hali hazırda dışa bağımlı bir şekilde yurtdışından temin edilerek çok yüksek maliyetler ile kullanılan FPGA geliştirme kartlarına alternatif olarak daha düşük maliyet ile mühendislik eğitim ve uygulamalarında kullanılabilecek yerli bir FPGA geliştirme kartı başarılı bir şekilde gerçekleştirilmiştir.

References

  • Abdullah H T, Younis B M, (2019), FPGA Based Bone Fracture Detector, IOP Conference Series: Materials Science and Engineering, 745, Article number 012052.
  • Akkoyun, F. (2011), FPGA Tabanlı Dokunmatik Ekranlı Kullanıcı Arabirimi Tasarlanması ve Gerçekleştirilmesi. Kocaeli Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, 103s, Kocaeli.
  • Alçın, M., Koyuncu, I., Tuna, M., Varan, M., & Pehlivan, I. (2019), A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array. International Journal of Circuit Theory and Applications, 47(3): 365-378
  • Az, I. (2014), Fpga Tabanlı Şifreli Kablosuz Haberleşme Sistemi, Doctoral dissertation, Fen Bilimleri Enstitüsü.
  • Bargsten V, de Gea Fernández J, (2020), Distributed computation and control of robot motion dynamics on FPGAs, International Journal of SN Applied Sciences, 2, Article number 1239.
  • Diao, L., Tang, J., Loh, P. C., Yin, S., Wang, L., & Liu, Z. (2018), An efficient DSP–FPGA-based implementation of hybrid PWM for electric rail traction induction motor control. IEEE Transactions on Power Electronics, 33(4): 3276-3288.
  • Dong, E., Yuan, M., Du, S., & Chen, Z. (2019), A new class of Hamiltonian conservative chaotic systems with multistability and design of pseudo-random number generator. Applied Mathematical Modelling, 73: 40-71
  • Drozd, O. V., & Kapulin, D. V. (2018), The device of secure data transmission based on Magma crypto algorithm with implementation on FPGA. In 2018 Moscow Workshop on Electronic and Networking Technologies (MWENT), (pp. 1-5). IEEE.
  • İsmail, S. M., Said, L. A., Rezk, A. A., Radwan, A. G., Madian, A. H., Abu-Elyazeed, M. F., & Soliman, A. M. (2017), Generalized fractional logistic map encryption system based on FPGA. AEU-International Journal of Electronics and Communications, 80: 114-126
  • Koyuncu, İ., Ozcerit, A. T., & Pehlivan, I. (2014), Implementation of FPGA-based real time novel chaotic oscillator. Nonlinear Dynamics, 77(1-2): 49-59.
  • Koyuncu, İ., Çetin, Ö., Katırcıoğlu, F., & Tuna, M. (2015), Edge dedection application with FPGA based Sobel operator. In 2015 23nd Signal Processing and Communications Applications Conference (SIU), (pp. 1829-1832). IEEE
  • Libano, F., Rech, P., Tambara, L., Tonfat, J., & Kastensmidt, F. (2018), On the reliability of linear regression and pattern recognition feedforward artificial neural networks in FPGAs. IEEE Transactions on Nuclear Science, 65(1): 288-295.
  • Munden, R. (2005), ASIC and FPGA verification: a guide to component modeling. Morgan Kaufmann Publ., Elsevier, San Francisco, USA
  • Özgür, M. (2014), Radar sinyal işleme algoritmalarının FPGA ve GPU üzerinde uygulanmasının başarım analizi, Master's thesis, TOBB Ekonomi ve Teknoloji Üniversitesi Fen Bilimleri Enstitüsü
  • Özkan, İ. A., Sarıtaş, İ., & Herdem, S. (2011), Manyetik filtreler için FPGA tabanlı bulanık kontrolör tasarımı.
  • Rahul, D. (2009), Introduction to Embedded System Design Using Field Programmable Gate Arrays.
  • Rodríguez-Orozco, E., García-Guerrero, E., Inzunza-Gonzalez, E., López-Bonilla, O., Flores-Vergara, A., Cárdenas-Valdez, J., & Tlelo-Cuautle, E. (2018), FPGA-based chaotic cryptosystem by using voice recognition as access key. Electronics, 7(12): 414
  • Savran İ, (2017), Donanım Tanımlama Dili VHDL ve FPGA Uygulamaları, Papatya Yayıncılık Eğitim, İstanbul.
  • Schafer, B. C., Takenaka, T., & Wakabayashi, K. (2009), Adaptive simulated annealer for high level synthesis design space exploration. In 2009 International Symposium on VLSI Design, Automation and Test, (pp. 106-109). IEEE.
  • Sinha, A. Lotia, P. (2015), A study on FPGA based digital modulators. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 4(4), 1935-1942.STMicroelectronics. 2020, AN2867 Application Note, (Rev 12). Oscillator design guide for STM8AF/AL/S, STM32 MCUs and MPUs.
  • Şahin, İ., Gloster, C., Doss, C. (2000), Feasibility of floating-point arithmetic in reconfigurable computing systems. Military and Aerospace Applications of Programmable Devices and Techn. Conf., Washington, DC.
  • Şahin, İ., Koyuncu, İ. (2011), A new module design for 3D graphic transformations using generated floating-point core units. I. Rev. on Modelling and Sim., 4(2):691-698
  • Tengilimoglu, B. Bazlamaçcı, C. F. (2014), Partial reconfiguration on a real-time target detection and tracking system. In 2014 22nd Signal Processing and Communications Applications Conference (SIU) (pp. 1130-1133). IEEE.
  • Tlelo-Cuautle, E., Guillén-Fernández, O., de Jesus Rangel-Magdaleno, J., Melendez-Cano, A., Nuñez-Perez, J. C., & de la Fraga, L. G. (2019), FPGA Implementation of Chaotic Oscillators, Their Synchronization, and Application to Secure Communications. In Re.
  • Tuntas R, (2015), The Modeling and Hardware Implementation of Semiconductor Circuit Elements by Using ANN and FPGA, Acta Physica Polonica Series a, 128(2B), pp. 78-81.
  • Yılmaz, N., (2008), Alan Programlamalı Kapı Dizileri (FPGA) Üzerinde Bir YSA’nın Tasarlanması ve Donanım Olarak Gerçekleştirilmesi, Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Konya.
  • Yılmaz C, Koyuncu I, Alçın M, Tuna M, 2019, Artificial Neural Networks based thermodynamic and economic analysis of a hydrogen production system assisted by geothermal energy on Field Programmable Gate Array, International Journal of Hydrogen Energy, 44, 17443-17459.
  • Alçın, M., Koyuncu, İ., Tuna, M., Varan, M., & Pehlivan, İ. (2019). A novel high speed Artificial Neural Network–based chaotic True Random Number Generator on Field Programmable Gate Array. International Journal of Circuit Theory and Applications, 47(3), 365-378.
  • Karataş, F., Koyuncu, İ., Alçın, M., Tuna, M. (2020). FPGA based Implementatıon of membership functions for real time fuzzy logic applications, International Asian congress on Contemporary Sciences-3, Konya, Turkey, pp. 62-69.
  • Rajagopal, K., Tuna, M., Karthikeyan, A., Koyuncu, İ., Duraisamy, P., & Akgul, A. (2019). Dynamical analysis, sliding mode synchronization of a fractional-order memristor Hopfield neural network with parameter uncertainties and its non-fractional-order FPGA implementation. The European Physical Journal Special Topics, 228(10), 2065-2080.
  • Tuna, M., Koyuncu, İ., Alçın, M. (2018). Fixed and Floating point-Based High-Speed Chaotic Oscillator Design with Different Numerical Algorithms on FPGA. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. Vol 7, Issue 7.
  • Tuna, M., Alçın, M., Koyuncu, İ., Fidan, C. B., & Pehlivan, İ. (2019). High speed FPGA-based chaotic oscillator design. Microprocessors and Microsystems, 66, 72-80.
  • Yılmaz, C., Koyuncu, İ., Alçın, M., & Tuna, M. (2019). Artificial Neural Networks based thermodynamic and economic analysis of a hydrogen production system assisted by geothermal energy on Field Programmable Gate Array. International Journal of Hydrogen Energy, 44(33), 17443-17459.
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Software Architecture
Journal Section Research Articles
Authors

Adem Keskin This is me 0000-0001-9781-4358

İsmail Koyuncu 0000-0003-4725-4879

Publication Date February 28, 2023
Submission Date July 27, 2022
Acceptance Date October 12, 2022
Published in Issue Year 2022

Cite

APA Keskin, A., & Koyuncu, İ. (2023). YENİ BİR FPGA GELİŞTİRME KARTI TASARIMI VE UYGULAMASI. Bilgisayar Bilimleri Ve Teknolojileri Dergisi, 3(2), 46-55. https://doi.org/10.54047/bibted.1149594